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the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/recommendation_flow_identifier/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/base",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
],
)
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/tracking_token/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"3rdparty/jvm/com/google/inject/extensions:guice-assistedinject",
"3rdparty/jvm/net/codingwell:scala-guice",
"3rdparty/jvm/org/slf4j:slf4j-api",
"finatra/inject/inject-core/src/main/scala",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/base",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/constants",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/utils",
"hermit/hermit-core/src/main/scala/com/twitter/hermit/constants",
"util/util-slf4j-api/src/main/scala",
],
)
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/tracking_token/TrackingTokenTransform.scala | package com.twitter.follow_recommendations.common.transforms.tracking_token
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.Transform
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.models.HasDisplayLocation
import com.twitter.follow_recommendations.common.models.Session
import com.twitter.follow_recommendations.common.models.TrackingToken
import com.twitter.hermit.constants.AlgorithmFeedbackTokens.AlgorithmToFeedbackTokenMap
import com.twitter.hermit.model.Algorithm
import com.twitter.product_mixer.core.model.common.identifier.CandidateSourceIdentifier
import com.twitter.product_mixer.core.model.marshalling.request.HasClientContext
import com.twitter.stitch.Stitch
import com.twitter.util.logging.Logging
import javax.inject.Inject
import javax.inject.Singleton
/**
* This transform adds the tracking token for all candidates
* Since this happens in the same request, we use the same trace-id for all candidates
* There are no RPC calls in this transform so it's safe to chain it with `andThen` at the end of
* all other product-specific transforms
*/
@Singleton
class TrackingTokenTransform @Inject() (baseStatsReceiver: StatsReceiver)
extends Transform[HasDisplayLocation with HasClientContext, CandidateUser]
with Logging {
def profileResults(
target: HasDisplayLocation with HasClientContext,
candidates: Seq[CandidateUser]
) = {
// Metrics to track # results per candidate source
val stats = baseStatsReceiver.scope(target.displayLocation.toString + "/final_results")
stats.stat("total").add(candidates.size)
stats.counter(target.displayLocation.toString).incr()
val flattenedCandidates: Seq[(CandidateSourceIdentifier, CandidateUser)] = for {
candidate <- candidates
identifier <- candidate.getPrimaryCandidateSource
} yield (identifier, candidate)
val candidatesGroupedBySource: Map[CandidateSourceIdentifier, Seq[CandidateUser]] =
flattenedCandidates.groupBy(_._1).mapValues(_.map(_._2))
candidatesGroupedBySource map {
case (source, candidates) => stats.stat(source.name).add(candidates.size)
}
}
override def transform(
target: HasDisplayLocation with HasClientContext,
candidates: Seq[CandidateUser]
): Stitch[Seq[CandidateUser]] = {
profileResults(target, candidates)
Stitch.value(
target.getOptionalUserId
.map { _ =>
candidates.map {
candidate =>
val token = Some(TrackingToken(
sessionId = Session.getSessionId,
displayLocation = Some(target.displayLocation),
controllerData = None,
algorithmId = candidate.userCandidateSourceDetails.flatMap(_.primaryCandidateSource
.flatMap { identifier =>
Algorithm.withNameOpt(identifier.name).flatMap(AlgorithmToFeedbackTokenMap.get)
})
))
candidate.copy(trackingToken = token)
}
}.getOrElse(candidates))
}
}
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/weighted_sampling/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/base",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/rankers/utils",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/common",
],
)
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/weighted_sampling/SamplingTransform.scala | package com.twitter.follow_recommendations.common.transforms.weighted_sampling
import com.twitter.follow_recommendations.common.base.GatedTransform
import com.twitter.stitch.Stitch
import com.twitter.timelines.configapi.HasParams
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.models.HasDebugOptions
import com.twitter.follow_recommendations.common.models.Score
import com.twitter.follow_recommendations.common.models.Scores
import com.twitter.follow_recommendations.common.rankers.common.RankerId
import com.twitter.follow_recommendations.common.rankers.utils.Utils
import com.twitter.product_mixer.core.model.marshalling.request.HasClientContext
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class SamplingTransform @Inject() ()
extends GatedTransform[HasClientContext with HasParams with HasDebugOptions, CandidateUser] {
val name: String = this.getClass.getSimpleName
/*
Description: This function takes in a set of candidate users and ranks them for a who-to-follow
request by sampling from the Placket-Luce distribution
(https://cran.rstudio.com/web/packages/PlackettLuce/vignettes/Overview.html) with a three
variations. The first variation is that the scores of the candidates are multiplied by
multiplicativeFactor before sampling. The second variation is that the scores are
exponentiated before sampling. The third variation is that depending on how many who-to-follow
positions are being requested, the first k positions are reserved for the candidates with the
highest scores (and they are sorted in decreasing order of score) and the remaining positions
are sampled from a Placket-Luce. We use the efficient algorithm proposed in this blog
https://medium.com/swlh/going-old-school-designing-algorithms-for-fast-weighted-sampling-in-production-c48fc1f40051
to sample from a Plackett-Luce. Because of numerical stability reasons, before sampling from this
distribution, (1) we subtract off the maximum score from all the scores and (2) if after
this subtraction and multiplication by the multiplicative factor the resulting score is <= -10,
we force the candidate's transformed score under the above algorithm to be 0 (so r^(1/w) = 0)
where r is a random number and w is the transformed score.
inputs:
- target: HasClientContext (WTF request)
- candidates: sequence of CandidateUsers (users that need to be ranked from a who-to-follow
request) each of which has a score
inputs accessed through feature switches, i.e. through target.params (see the following file:
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/
transforms/weighted_sampling/SamplingTransformParams.scala"):
- topKFixed: the first k positions of the who-to-follow ranking correspond to the users with the k
highest scores and are not sampled from the Placket-Luce distribution
- multiplicativeFactor: multiplicativeFactor is used to transform the scores of each candidate by
multiplying that user's score by multiplicativeFactor
output:
- Sequence of CandidateUser whose order represents the ranking of users in a who-to-follow request
This ranking is sampled from a Placket-Luce distribution.
*/
override def transform(
target: HasClientContext with HasParams with HasDebugOptions,
candidates: Seq[CandidateUser]
): Stitch[Seq[CandidateUser]] = {
// the first k positions of the who-to-follow ranking correspond to the users with the k
// highest scores and are not sampled from the Placket-Luce distribution
val topKFixed = target.params(SamplingTransformParams.TopKFixed)
// multiplicativeFactor is used to transform the scores of each candidate by
// multiplying that user's score by multiplicativeFactor
val multiplicativeFactor = target.params(SamplingTransformParams.MultiplicativeFactor)
// sort candidates by their score
val candidatesSorted = candidates.sortBy(-1 * _.score.getOrElse(0.0))
// pick the top K candidates by score and the remaining candidates
val (topKFixedCandidates, candidatesOutsideOfTopK) =
candidatesSorted.zipWithIndex.partition { case (value, index) => index < topKFixed }
val randomNumGenerator =
new scala.util.Random(target.getRandomizationSeed.getOrElse(System.currentTimeMillis))
// we need to subtract the maximum score off the scores for numerical stability reasons
// subtracting the max score off does not effect the underlying distribution we are sampling
// the candidates from
// we need the if statement since you cannot take the max of an empty sequence
val maximum_score = if (candidatesOutsideOfTopK.nonEmpty) {
candidatesOutsideOfTopK.map(x => x._1.score.getOrElse(0.0)).max
} else {
0.0
}
// for candidates in candidatesOutsideOfTopK, we transform their score by subtracting off
// maximum_score and then multiply by multiplicativeFactor
val candidatesOutsideOfTopKTransformedScore = candidatesOutsideOfTopK.map(x =>
(x._1, multiplicativeFactor * (x._1.score.getOrElse(0.0) - maximum_score)))
// for each candidate with score transformed and clip score w, sample a random number r,
// create a new score r^(1/w) and sort the candidates to get the final ranking.
// for numerical stability reasons if the score is <=-10, we force r^(1/w) = 0.
// this samples the candidates from the modified Plackett-Luce distribution. See
// https://medium.com/swlh/going-old-school-designing-algorithms-for-fast-weighted-sampling-in-production-c48fc1f40051
val candidatesOutsideOfTopKSampled = candidatesOutsideOfTopKTransformedScore
.map(x =>
(
x._1,
if (x._2 <= -10.0)
0.0
else
scala.math.pow(
randomNumGenerator.nextFloat(),
1 / (scala.math
.exp(x._2))))).sortBy(-1 * _._2)
val topKCandidates: Seq[CandidateUser] = topKFixedCandidates.map(_._1)
val scribeRankingInfo: Boolean =
target.params(SamplingTransformParams.ScribeRankingInfoInSamplingTransform)
val transformedCandidates: Seq[CandidateUser] = if (scribeRankingInfo) {
val topKCandidatesWithRankingInfo: Seq[CandidateUser] =
Utils.addRankingInfo(topKCandidates, name)
val candidatesOutsideOfTopKSampledWithRankingInfo: Seq[CandidateUser] =
candidatesOutsideOfTopKSampled.zipWithIndex.map {
case ((candidate, score), rank) =>
val newScore = Seq(Score(score, Some(RankerId.PlacketLuceSamplingTransformer)))
val newScores: Option[Scores] = candidate.scores
.map { scores =>
scores.copy(scores = scores.scores ++ newScore)
}.orElse(Some(Scores(newScore, Some(RankerId.PlacketLuceSamplingTransformer))))
val globalRank = rank + topKFixed + 1
candidate.addInfoPerRankingStage(name, newScores, globalRank)
}
topKCandidatesWithRankingInfo ++ candidatesOutsideOfTopKSampledWithRankingInfo
} else {
topKCandidates ++ candidatesOutsideOfTopKSampled.map(_._1)
}
Stitch.value(transformedCandidates)
}
}
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/weighted_sampling/SamplingTransformFSConfig.scala | package com.twitter.follow_recommendations.common.transforms.weighted_sampling
import com.twitter.follow_recommendations.configapi.common.FeatureSwitchConfig
import com.twitter.timelines.configapi.FSBoundedParam
import com.twitter.timelines.configapi.FSParam
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class SamplingTransformFSConfig @Inject() () extends FeatureSwitchConfig {
override val intFSParams: Seq[FSBoundedParam[Int]] = Seq(SamplingTransformParams.TopKFixed)
override val doubleFSParams: Seq[FSBoundedParam[Double]] = Seq(
SamplingTransformParams.MultiplicativeFactor)
override val booleanFSParams: Seq[FSParam[Boolean]] = Seq(
SamplingTransformParams.ScribeRankingInfoInSamplingTransform)
}
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/weighted_sampling/SamplingTransformParams.scala | package com.twitter.follow_recommendations.common.transforms.weighted_sampling
import com.twitter.timelines.configapi.FSBoundedParam
import com.twitter.timelines.configapi.FSParam
object SamplingTransformParams {
case object TopKFixed // indicates how many of the fisrt K who-to-follow recommendations are reserved for the candidates with largest K CandidateUser.score where these candidates are sorted in decreasing order of score
extends FSBoundedParam[Int](
name = "post_nux_ml_flow_weighted_sampling_top_k_fixed",
default = 0,
min = 0,
max = 100)
case object MultiplicativeFactor // CandidateUser.score gets transformed to multiplicativeFactor*CandidateUser.score before sampling from the Plackett-Luce distribution
extends FSBoundedParam[Double](
name = "post_nux_ml_flow_weighted_sampling_multiplicative_factor",
default = 1.0,
min = -1000.0,
max = 1000.0)
case object ScribeRankingInfoInSamplingTransform
extends FSParam[Boolean]("sampling_transform_scribe_ranking_info", false)
}
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/utils/BUILD | scala_library(
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"finatra/inject/inject-core/src/main/scala",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/base",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"product-mixer/core/src/main/scala/com/twitter/product_mixer/core/functional_component/marshaller",
"product-mixer/core/src/main/scala/com/twitter/product_mixer/core/functional_component/marshaller/request",
"stitch/stitch-core",
"util/util-slf4j-api/src/main/scala",
],
)
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/utils/CollectionUtil.scala | package com.twitter.follow_recommendations.common.utils
object CollectionUtil {
/**
* Transposes a sequence of sequences. As opposed to the Scala collection library version
* of transpose, the sequences do not have to have the same length.
*
* Example:
* transpose(immutable.Seq(immutable.Seq(1,2,3), immutable.Seq(4,5), immutable.Seq(6,7)))
* => immutable.Seq(immutable.Seq(1, 4, 6), immutable.Seq(2, 5, 7), immutable.Seq(3))
*
* @param seq a sequence of sequences
* @tparam A the type of elements in the seq
* @return the transposed sequence of sequences
*/
def transposeLazy[A](seq: Seq[Seq[A]]): Stream[Seq[A]] =
seq.filter(_.nonEmpty) match {
case Nil => Stream.empty
case ys => ys.map(_.head) #:: transposeLazy(ys.map(_.tail))
}
}
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/utils/DisplayLocationProductConverterUtil.scala | package com.twitter.follow_recommendations.common.utils
import com.twitter.follow_recommendations.common.models.DisplayLocation
import com.twitter.follow_recommendations.common.models.Product
import com.twitter.product_mixer.core.model.marshalling.request.Product
object DisplayLocationProductConverterUtil {
def productToDisplayLocation(product: Product): DisplayLocation = {
product match {
case Product.MagicRecs => DisplayLocation.MagicRecs
case _ =>
throw UnconvertibleProductMixerProductException(
s"Cannot convert Product Mixer Product ${product.identifier.name} into a FRS DisplayLocation.")
}
}
def displayLocationToProduct(displayLocation: DisplayLocation): Product = {
displayLocation match {
case DisplayLocation.MagicRecs => Product.MagicRecs
case _ =>
throw UnconvertibleProductMixerProductException(
s"Cannot convert DisplayLocation ${displayLocation.toFsName} into a Product Mixer Product.")
}
}
}
case class UnconvertibleProductMixerProductException(message: String) extends Exception(message)
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/utils/MergeUtil.scala | package com.twitter.follow_recommendations.common.utils
object MergeUtil {
/**
* Takes a seq of items which have weights. Returns an infinite stream of each item
* by their weights. All weights need to be greater than or equal to zero. In addition,
* the sum of weights should be greater than zero.
*
* Example usage of this function:
* Input weighted Item {{CS1, 3}, {CS2, 2}, {CS3, 5}}
* Output stream: (CS1, CS1, CS1, CS2, CS2, CS3, CS3, CS3, CS3, CS3, CS1, CS1, CS1, CS2,...}
*
* @param items items
* @param weighted provides weights for items
* @tparam T type of item
*
* @return Stream of Ts
*/
def weightedRoundRobin[T](
items: Seq[T]
)(
implicit weighted: Weighted[T]
): Stream[T] = {
if (items.isEmpty) {
Stream.empty
} else {
val weights = items.map { i => weighted(i) }
assert(
weights.forall {
_ >= 0
},
"Negative weight exists for sampling")
val cumulativeWeight = weights.scanLeft(0.0)(_ + _).tail
assert(cumulativeWeight.last > 0, "Sum of the sampling weights is not positive")
var weightIdx = 0
var weight = 0
def next(): Stream[T] = {
val tmpIdx = weightIdx
weight = weight + 1
weight = if (weight >= weights(weightIdx)) 0 else weight
weightIdx = if (weight == 0) weightIdx + 1 else weightIdx
weightIdx = if (weightIdx == weights.length) 0 else weightIdx
items(tmpIdx) #:: next()
}
next()
}
}
}
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/utils/RandomUtil.scala | package com.twitter.follow_recommendations.common.utils
import scala.util.Random
object RandomUtil {
/**
* Takes a seq of items which have weights. Returns an infinite stream that is
* sampled with replacement using the weights for each item. All weights need
* to be greater than or equal to zero. In addition, the sum of weights
* should be greater than zero.
*
* @param items items
* @param weighted provides weights for items
* @tparam T type of item
* @return Stream of Ts
*/
def weightedRandomSamplingWithReplacement[T](
items: Seq[T],
random: Option[Random] = None
)(
implicit weighted: Weighted[T]
): Stream[T] = {
if (items.isEmpty) {
Stream.empty
} else {
val weights = items.map { i => weighted(i) }
assert(weights.forall { _ >= 0 }, "Negative weight exists for sampling")
val cumulativeWeight = weights.scanLeft(0.0)(_ + _).tail
assert(cumulativeWeight.last > 0, "Sum of the sampling weights is not positive")
val cumulativeProbability = cumulativeWeight map (_ / cumulativeWeight.last)
def next(): Stream[T] = {
val rand = random.getOrElse(Random).nextDouble()
val idx = cumulativeProbability.indexWhere(_ >= rand)
items(if (idx == -1) items.length - 1 else idx) #:: next()
}
next()
}
}
/**
* Takes a seq of items and their weights. Returns a lazy weighted shuffle of
* the elements in the list. All weights should be greater than zero.
*
* @param items items
* @param weighted provides weights for items
* @tparam T type of item
* @return Stream of Ts
*/
def weightedRandomShuffle[T](
items: Seq[T],
random: Option[Random] = None
)(
implicit weighted: Weighted[T]
): Stream[T] = {
assert(items.forall { i => weighted(i) > 0 }, "Non-positive weight exists for shuffling")
def next(it: Seq[T]): Stream[T] = {
if (it.isEmpty)
Stream.empty
else {
val cumulativeWeight = it.scanLeft(0.0)((acc: Double, curr: T) => acc + weighted(curr)).tail
val cutoff = random.getOrElse(Random).nextDouble() * cumulativeWeight.last
val idx = cumulativeWeight.indexWhere(_ >= cutoff)
val (left, right) = it.splitAt(idx)
it(if (idx == -1) it.size - 1 else idx) #:: next(left ++ right.drop(1))
}
}
next(items)
}
/**
* Takes a seq of items and a weight function, returns a lazy weighted shuffle of
* the elements in the list.The weight function is based on the rank of the element
* in the original lst.
* @param items
* @param rankToWeight
* @param random
* @tparam T
* @return
*/
def weightedRandomShuffleByRank[T](
items: Seq[T],
rankToWeight: Int => Double,
random: Option[Random] = None
): Stream[T] = {
val candWeights = items.zipWithIndex.map { case (item, rank) => (item, rankToWeight(rank)) }
RandomUtil.weightedRandomShuffle(candWeights, random).map(_._1)
}
}
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/utils/RescueWithStatsUtils.scala | package com.twitter.follow_recommendations.common.utils
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.StatsUtil
import com.twitter.stitch.Stitch
import com.twitter.util.Duration
import com.twitter.util.TimeoutException
object RescueWithStatsUtils {
def rescueWithStats[T](
s: Stitch[Seq[T]],
stats: StatsReceiver,
source: String
): Stitch[Seq[T]] = {
StatsUtil.profileStitchSeqResults(s, stats.scope(source)).rescue {
case _: Exception => Stitch.Nil
}
}
def rescueOptionalWithStats[T](
s: Stitch[Option[T]],
stats: StatsReceiver,
source: String
): Stitch[Option[T]] = {
StatsUtil.profileStitchOptionalResults(s, stats.scope(source)).rescue {
case _: Exception => Stitch.None
}
}
def rescueWithStatsWithin[T](
s: Stitch[Seq[T]],
stats: StatsReceiver,
source: String,
timeout: Duration
): Stitch[Seq[T]] = {
val hydratedScopeSource = stats.scope(source)
StatsUtil
.profileStitchSeqResults(
s.within(timeout)(com.twitter.finagle.util.DefaultTimer),
hydratedScopeSource)
.rescue {
case _: TimeoutException =>
hydratedScopeSource.counter("timeout").incr()
Stitch.Nil
case _: Exception =>
hydratedScopeSource.counter("exception").incr()
Stitch.Nil
}
}
}
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/utils/UserSignupUtil.scala | package com.twitter.follow_recommendations.common.utils
import com.twitter.product_mixer.core.model.marshalling.request.HasClientContext
import com.twitter.snowflake.id.SnowflakeId
import com.twitter.util.Duration
import com.twitter.util.Time
object UserSignupUtil {
def signupTime(hasClientContext: HasClientContext): Option[Time] =
hasClientContext.clientContext.userId.flatMap(SnowflakeId.timeFromIdOpt)
def userSignupAge(hasClientContext: HasClientContext): Option[Duration] =
signupTime(hasClientContext).map(Time.now - _)
}
|
the-algorithm-main/follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/utils/Weighted.scala | package com.twitter.follow_recommendations.common.utils
/**
* Typeclass for any Recommendation type that has a weight
*
*/
trait Weighted[-Rec] {
def apply(rec: Rec): Double
}
object Weighted {
implicit object WeightedTuple extends Weighted[(_, Double)] {
override def apply(rec: (_, Double)): Double = rec._2
}
def fromFunction[Rec](f: Rec => Double): Weighted[Rec] = {
new Weighted[Rec] {
override def apply(rec: Rec): Double = f(rec)
}
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/resources/BUILD | resources(
sources = [
"*.tsv",
"*.xml",
"**/*",
"config/*.yml",
],
)
# Created for Bazel compatibility.
# In Bazel, loose files must be part of a target to be included into a bundle.
files(
name = "frs_resources",
sources = [
"*.tsv",
"*.xml",
"*.yml",
"**/*",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/resources/config/decider.yml | enable_recommendations:
comment: Proportion of requests where we return an actual response as part. Decreasing the value will increase the portion of empty responses (in order to disable the service) as part of the graceful degradation.
default_availability: 10000
enable_score_user_candidates:
comment: Proportion of requests where score user candidates from the scoreUserCandidates endpoint
default_availability: 10000
enable_profile_sidebar_product:
comment: Proportion of requests where we return an actual response for profile sidebar product
default_availability: 10000
enable_magic_recs_product:
comment: Proportion of requests where we return an actual response for magic recs product
default_availability: 10000
enable_rux_landing_page_product:
comment: Proportion of requests where we return an actual response for rux landing page product
default_availability: 10000
enable_rux_pymk_product:
comment: Proportion of requests where we return an actual response for rux pymk product
default_availability: 10000
enable_profile_bonus_follow_product:
comment: Proportion of requests where we return an actual response for profile bonus follow product
default_availability: 10000
enable_election_explore_wtf_product:
comment: Proportion of requests where we return an actual response for election explore wtf product
default_availability: 10000
enable_cluster_follow_product:
comment: Proportion of requests where we return an actual response for cluster follow product
default_availability: 10000
enable_home_timeline_product:
comment: Proportion of requests where we return an actual response for htl wtf product
default_availability: 10000
enable_htl_bonus_follow_product:
comment: Proportion of requests where we return an actual response for htl bonus follow product
default_availability: 10000
enable_explore_tab_product:
comment: Proportion of requests where we return an actual response for explore tab product
default_availability: 10000
enable_sidebar_product:
comment: Proportion of requests where we return an actual response for sidebar product
default_availability: 10000
enable_campaign_form_product:
comment: Proportion of requests where we return an actual response for campaign form product
default_availability: 10000
enable_reactive_follow_product:
comment: Proportion of requests where we return an actual response for reactive follow product
default_availability: 10000
enable_nux_pymk_product:
comment: Proportion of requests where we return an actual response for nux pymk product
default_availability: 10000
enable_nux_interests_product:
comment: Proportion of requests where we return an actual response for nux interests product
default_availability: 10000
enable_nux_topic_bonus_follow_product:
comment: Proportion of requests where we return an actual response for nux topic-based bonus follow product
default_availability: 10000
enable_india_covid19_curated_accounts_wtf_product:
comment: Proportion of requests where we return an actual response for india covid19 curated accounts wtf product
default_availability: 10000
enable_ab_upload_product:
comment: Proportion of requests where we return an actual response for the address book upload product
default_availability: 10000
enable_people_plus_plus_product:
comment: Proportion of requests where we return an actual response for the PeoplePlusPlus/Connect Tab product
default_availability: 10000
enable_tweet_notification_recs_product:
comment: Proportion of requests where we return an actual response for the Tweet Notification Recommendations product
default_availability: 10000
enable_profile_device_follow_product:
comment: Proportion of requests where we return an actual response for the ProfileDeviceFollow product
default_availability: 10000
enable_diffy_module_dark_reading:
comment: Percentage of dark read traffic routed to diffy thrift
default_availability: 0
enable_recos_backfill_product:
comment: Proportion of requests where we return an actual response for the RecosBackfill product
default_availability: 10000
enable_post_nux_follow_task_product:
comment: Proportion of requests where we return an actual response for post NUX follow task product
default_availability: 10000
enable_curated_space_hosts_product:
comment: Proportion of requests where we return an actual response for curated space hosts product
default_availability: 10000
enable_nux_geo_category_product:
comment: Proportion of requests where we return an actual response for nux geo category product
default_availability: 10000
enable_nux_interests_category_product:
comment: Proportion of requests where we return an actual response for nux interests category product
default_availability: 10000
enable_nux_pymk_category_product:
comment: Proportion of requests where we return an actual response for nux pymk category product
default_availability: 10000
enable_home_timeline_tweet_recs_product:
comment: Proportion of requests where we return an actual response for the Home Timeline Tweet Recs product
default_availability: 10000
enable_htl_bulk_friend_follows_product:
comment: Proportion of requests where we return an actual response for the HTL bulk friend follows product
default_availability: 10000
enable_nux_auto_follow_product:
comment: Proportion of requests where we return an actual response for the NUX auto follow product
default_availability: 10000
enable_search_bonus_follow_product:
comment: Proportion of requests where we return an actual response for search bonus follow product
default_availability: 10000
enable_fetch_user_in_request_builder:
comment: Proportion of requests where we fetch user object from gizmoduck in request builder
default_availability: 0
enable_product_mixer_magic_recs_product:
comment: Proportion of requests where we enable the product mixer magic recs product
default_availability: 10000
enable_home_timeline_reverse_chron_product:
comment: Proportion of requests where we return an actual response for Home timeline reverse chron product
default_availability: 10000
enable_product_mixer_pipeline_magic_recs_dark_read:
comment: Compare product mixer pipeline responses to current FRS pipeline responses for Magic Recs
default_availability: 0
enable_experimental_caching:
comment: Proportion of requests we use experimental caching for data caching
default_availability: 0
enable_distributed_caching:
comment: Proportion of requests we use a distributed cache cluster for data caching
default_availability: 10000
enable_gizmoduck_caching:
comment: Proportion of requests we use a distributed cache cluster for data caching in Gizmoduck
default_availability: 10000
enable_traffic_dark_reading:
comment: Proportion of requests where we replicate the request for traffic dark reading
default_availability: 0
enable_graph_feature_service_requests:
comment: Proportion of requests where we allow request calls to Graph Feature Service
default_availability: 10000
|
the-algorithm-main/follow-recommendations-service/server/src/main/resources/logback.xml | <configuration>
<shutdownHook class="ch.qos.logback.core.hook.DelayingShutdownHook"/>
<!-- ===================================================== -->
<!-- Service Config -->
<!-- ===================================================== -->
<property name="DEFAULT_SERVICE_PATTERN"
value="%-16X{traceId} %-12X{serviceIdentifier:--} %-16X{method} %-12X{product:--} %-25logger{0} %msg"/>
<property name="DEFAULT_ACCESS_PATTERN"
value="%msg %-12X{serviceIdentifier:--} %X{traceId} %X{product:--}"/>
<!-- ===================================================== -->
<!-- Common Config -->
<!-- ===================================================== -->
<!-- JUL/JDK14 to Logback bridge -->
<contextListener class="ch.qos.logback.classic.jul.LevelChangePropagator">
<resetJUL>true</resetJUL>
</contextListener>
<!-- Service Log (Rollover every 50MB, max 5 logs) -->
<appender name="SERVICE" class="ch.qos.logback.core.rolling.RollingFileAppender">
<file>${log.service.output}</file>
<rollingPolicy class="ch.qos.logback.core.rolling.FixedWindowRollingPolicy">
<fileNamePattern>${log.service.output}.%i</fileNamePattern>
<minIndex>1</minIndex>
<maxIndex>5</maxIndex>
</rollingPolicy>
<triggeringPolicy class="ch.qos.logback.core.rolling.SizeBasedTriggeringPolicy">
<maxFileSize>50MB</maxFileSize>
</triggeringPolicy>
<encoder>
<pattern>%date %.-3level ${DEFAULT_SERVICE_PATTERN}%n</pattern>
</encoder>
</appender>
<!-- Access Log (Rollover every 50MB, max 5 logs) -->
<appender name="ACCESS" class="ch.qos.logback.core.rolling.RollingFileAppender">
<file>${log.access.output}</file>
<rollingPolicy class="ch.qos.logback.core.rolling.FixedWindowRollingPolicy">
<fileNamePattern>${log.access.output}.%i</fileNamePattern>
<minIndex>1</minIndex>
<maxIndex>5</maxIndex>
</rollingPolicy>
<triggeringPolicy class="ch.qos.logback.core.rolling.SizeBasedTriggeringPolicy">
<maxFileSize>50MB</maxFileSize>
</triggeringPolicy>
<encoder>
<pattern>${DEFAULT_ACCESS_PATTERN}%n</pattern>
</encoder>
</appender>
<!--LogLens -->
<appender name="LOGLENS" class="com.twitter.loglens.logback.LoglensAppender">
<mdcAdditionalContext>true</mdcAdditionalContext>
<category>${log.lens.category}</category>
<index>${log.lens.index}</index>
<tag>${log.lens.tag}/service</tag>
<encoder>
<pattern>%msg</pattern>
</encoder>
</appender>
<!-- LogLens Access -->
<appender name="LOGLENS-ACCESS" class="com.twitter.loglens.logback.LoglensAppender">
<mdcAdditionalContext>true</mdcAdditionalContext>
<category>${log.lens.category}</category>
<index>${log.lens.index}</index>
<tag>${log.lens.tag}/access</tag>
<encoder>
<pattern>%msg</pattern>
</encoder>
</appender>
<!-- ===================================================== -->
<!-- Primary Async Appenders -->
<!-- ===================================================== -->
<property name="async_queue_size" value="${queue.size:-50000}"/>
<property name="async_max_flush_time" value="${max.flush.time:-0}"/>
<appender name="ASYNC-SERVICE" class="com.twitter.inject.logback.AsyncAppender">
<queueSize>${async_queue_size}</queueSize>
<maxFlushTime>${async_max_flush_time}</maxFlushTime>
<appender-ref ref="SERVICE"/>
</appender>
<appender name="ASYNC-ACCESS" class="com.twitter.inject.logback.AsyncAppender">
<queueSize>${async_queue_size}</queueSize>
<maxFlushTime>${async_max_flush_time}</maxFlushTime>
<appender-ref ref="ACCESS"/>
</appender>
<appender name="ASYNC-LOGLENS" class="com.twitter.inject.logback.AsyncAppender">
<queueSize>${async_queue_size}</queueSize>
<maxFlushTime>${async_max_flush_time}</maxFlushTime>
<appender-ref ref="LOGLENS"/>
</appender>
<appender name="ASYNC-LOGLENS-ACCESS" class="com.twitter.inject.logback.AsyncAppender">
<queueSize>${async_queue_size}</queueSize>
<maxFlushTime>${async_max_flush_time}</maxFlushTime>
<appender-ref ref="LOGLENS-ACCESS"/>
</appender>
<!-- ===================================================== -->
<!-- Package Config -->
<!-- ===================================================== -->
<!-- Per-Package Config -->
<logger name="com.twitter" level="info"/>
<logger name="com.twitter.wilyns" level="warn"/>
<logger name="com.twitter.finagle.mux" level="warn"/>
<logger name="com.twitter.finagle.serverset2" level="warn"/>
<logger name="com.twitter.logging.ScribeHandler" level="warn"/>
<logger name="com.twitter.zookeeper.client.internal" level="warn"/>
<!-- Root Config -->
<root level="${log_level:-INFO}">
<appender-ref ref="ASYNC-SERVICE"/>
<appender-ref ref="ASYNC-LOGLENS"/>
</root>
<!-- Access Logging -->
<logger name="com.twitter.finatra.thrift.filters.AccessLoggingFilter"
level="info"
additivity="false">
<appender-ref ref="ASYNC-ACCESS"/>
<appender-ref ref="ASYNC-LOGLENS-ACCESS"/>
</logger>
</configuration>
|
the-algorithm-main/follow-recommendations-service/server/src/main/resources/quality/stp_models/20141223/epModel | # OWNER = jdeng
# Date = 20141223_153423
# Training Size = 16744473
# Testing Size = 16767335
# trained with ElasticNetCV alpha=0.05 cv_folds=5 best_lambda=1.0E-7
# num base features: 10
# num nonzero weights: 30
{bias:-5.67151,featureMetadataMap:["fwd_email":{metadata:{featureWeight:{weight:2.47389}}},"rev_phone":{metadata:{featureWeight:{weight:1.88433}}},"mutual_follow_path":{metadata:{featureWeight:{intervalWeights:[{left:47.0,weight:6.31809},{left:11.0,right:16.0,weight:4.52959},{left:31.0,right:47.0,weight:5.7101},{right:2.0,weight:0.383515},{left:24.0,right:31.0,weight:5.26515},{left:3.0,right:4.0,weight:2.91751},{left:2.0,right:3.0,weight:2.22851},{left:4.0,right:5.0,weight:3.28515},{left:8.0,right:11.0,weight:4.14731},{left:5.0,right:8.0,weight:3.73588},{left:16.0,right:24.0,weight:4.90908}]}}},"fwd_phone":{metadata:{featureWeight:{weight:2.07327}}},"fwd_email_path":{metadata:{featureWeight:{weight:0.961773}}},"rev_phone_path":{metadata:{featureWeight:{weight:0.354484}}},"low_tweepcred_follow_path":{metadata:{featureWeight:{intervalWeights:[{left:4.0,right:5.0,weight:0.177209},{left:7.0,right:8.0,weight:0.12378},{left:3.0,right:4.0,weight:0.197566},{left:5.0,right:6.0,weight:0.15867},{left:2.0,right:3.0,weight:0.196539},{right:2.0,weight:0.1805},{left:75.0,weight:-0.424598},{left:6.0,right:7.0,weight:0.143698},{left:10.0,right:13.0,weight:0.0458502},{left:8.0,right:10.0,weight:0.0919314},{left:13.0,right:75.0,weight:-0.111484}]}}},"rev_email_path":{metadata:{featureWeight:{weight:0.654451}}},"rev_email":{metadata:{featureWeight:{weight:2.33859}}},"fwd_phone_path":{metadata:{featureWeight:{weight:0.210418}}}]}
|
the-algorithm-main/follow-recommendations-service/server/src/main/resources/quality/stp_models/20141223/trainingConfig | {input:{context:"discover.prod",startDateTime:"",endDateTime:"",trainingFeatures:["STP_FEATURES":["fwd_email","mutual_follow_path","fwd_email_path","rev_phone_path","low_tweepcred_follow_path","rev_phone","fwd_phone","rev_email_path","rev_email","fwd_phone_path"]],engagementActions:["click","favorite","open_link","open","send_tweet","send_reply","retweet","reply","profile_click","follow"],impressionActions:["discard","results","impression"],dataFormat:1,dataPath:"",isLabeled:0},sample:{positiveSampleRatio:1.0,negativeSampleRatio:1.0,sampleType:1},split:{trainingDataSplitSize:0.5,testingDataSplitSize:0.5,splitType:2},transform:{},filter:{featureOptions:[]},join:{engagementRules:["discover"],contentIdType:"tweet",groupBucketSize:3600000},discretize:{}}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/org/slf4j:slf4j-api",
"finagle/finagle-http/src/main/scala",
"finagle/finagle-thriftmux/src/main/scala",
"finatra-internal/decider/src/main/scala",
"finatra-internal/international/src/main/scala/com/twitter/finatra/international/modules",
"finatra-internal/mtls-http/src/main/scala",
"finatra-internal/mtls-thriftmux/src/main/scala",
"finatra/http-core/src/main/java/com/twitter/finatra/http",
"finatra/inject/inject-app/src/main/scala",
"finatra/inject/inject-core/src/main/scala",
"finatra/inject/inject-server/src/main/scala",
"finatra/inject/inject-thrift-client",
"finatra/jackson/src/main/scala/com/twitter/finatra/jackson/modules",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/sims",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/addressbook",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/adserver",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/cache",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/deepbirdv2",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/email_storage_service",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/geoduck",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/gizmoduck",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/graph_feature_service",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/phone_storage_service",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/socialgraph",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/strato",
"follow-recommendations-service/server/src/main/resources",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/controllers",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/modules",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/products",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/services",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/services/exceptions",
"follow-recommendations-service/thrift/src/main/thrift:thrift-scala",
"geoduck/service/src/main/scala/com/twitter/geoduck/service/common/clientmodules",
"product-mixer/core/src/main/scala/com/twitter/product_mixer/core/controllers",
"product-mixer/core/src/main/scala/com/twitter/product_mixer/core/functional_component/configapi",
"product-mixer/core/src/main/scala/com/twitter/product_mixer/core/module",
"product-mixer/core/src/main/scala/com/twitter/product_mixer/core/module/stringcenter",
"product-mixer/core/src/main/scala/com/twitter/product_mixer/core/product/guice",
"twitter-server/server/src/main/scala",
"util/util-app/src/main/scala",
"util/util-core:scala",
"util/util-slf4j-api/src/main/scala",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/FollowRecommendationsServiceThriftServer.scala | package com.twitter.follow_recommendations
import com.google.inject.Module
import com.twitter.finagle.ThriftMux
import com.twitter.finatra.decider.modules.DeciderModule
import com.twitter.finatra.http.HttpServer
import com.twitter.finatra.http.routing.HttpRouter
import com.twitter.finatra.international.modules.I18nFactoryModule
import com.twitter.finatra.international.modules.LanguagesModule
import com.twitter.finatra.jackson.modules.ScalaObjectMapperModule
import com.twitter.finatra.mtls.http.{Mtls => HttpMtls}
import com.twitter.finatra.mtls.thriftmux.Mtls
import com.twitter.finatra.thrift.ThriftServer
import com.twitter.finatra.thrift.filters._
import com.twitter.finagle.thrift.Protocols
import com.twitter.finatra.thrift.routing.ThriftRouter
import com.twitter.follow_recommendations.common.clients.addressbook.AddressbookModule
import com.twitter.follow_recommendations.common.clients.adserver.AdserverModule
import com.twitter.follow_recommendations.common.clients.cache.MemcacheModule
import com.twitter.follow_recommendations.common.clients.deepbirdv2.DeepBirdV2PredictionServiceClientModule
import com.twitter.follow_recommendations.common.clients.email_storage_service.EmailStorageServiceModule
import com.twitter.follow_recommendations.common.clients.geoduck.LocationServiceModule
import com.twitter.follow_recommendations.common.clients.gizmoduck.GizmoduckModule
import com.twitter.follow_recommendations.common.clients.graph_feature_service.GraphFeatureStoreModule
import com.twitter.follow_recommendations.common.clients.impression_store.ImpressionStoreModule
import com.twitter.follow_recommendations.common.clients.phone_storage_service.PhoneStorageServiceModule
import com.twitter.follow_recommendations.common.clients.socialgraph.SocialGraphModule
import com.twitter.follow_recommendations.common.clients.strato.StratoClientModule
import com.twitter.follow_recommendations.common.constants.ServiceConstants._
import com.twitter.follow_recommendations.common.feature_hydration.sources.HydrationSourcesModule
import com.twitter.follow_recommendations.controllers.ThriftController
import com.twitter.follow_recommendations.modules._
import com.twitter.follow_recommendations.service.exceptions.UnknownLoggingExceptionMapper
import com.twitter.follow_recommendations.services.FollowRecommendationsServiceWarmupHandler
import com.twitter.follow_recommendations.thriftscala.FollowRecommendationsThriftService
import com.twitter.geoduck.service.common.clientmodules.ReverseGeocoderThriftClientModule
import com.twitter.inject.thrift.filters.DarkTrafficFilter
import com.twitter.inject.thrift.modules.ThriftClientIdModule
import com.twitter.product_mixer.core.controllers.ProductMixerController
import com.twitter.product_mixer.core.module.PipelineExecutionLoggerModule
import com.twitter.product_mixer.core.module.product_mixer_flags.ProductMixerFlagModule
import com.twitter.product_mixer.core.module.stringcenter.ProductScopeStringCenterModule
import com.twitter.product_mixer.core.product.guice.ProductScopeModule
object FollowRecommendationsServiceThriftServerMain extends FollowRecommendationsServiceThriftServer
class FollowRecommendationsServiceThriftServer
extends ThriftServer
with Mtls
with HttpServer
with HttpMtls {
override val name: String = "follow-recommendations-service-server"
override val modules: Seq[Module] =
Seq(
ABDeciderModule,
AddressbookModule,
AdserverModule,
ConfigApiModule,
DeciderModule,
DeepBirdV2PredictionServiceClientModule,
DiffyModule,
EmailStorageServiceModule,
FeaturesSwitchesModule,
FlagsModule,
GizmoduckModule,
GraphFeatureStoreModule,
HydrationSourcesModule,
I18nFactoryModule,
ImpressionStoreModule,
LanguagesModule,
LocationServiceModule,
MemcacheModule,
PhoneStorageServiceModule,
PipelineExecutionLoggerModule,
ProductMixerFlagModule,
ProductRegistryModule,
new ProductScopeModule(),
new ProductScopeStringCenterModule(),
new ReverseGeocoderThriftClientModule,
ScalaObjectMapperModule,
ScorerModule,
ScribeModule,
SocialGraphModule,
StratoClientModule,
ThriftClientIdModule,
TimerModule,
)
def configureThrift(router: ThriftRouter): Unit = {
router
.filter[LoggingMDCFilter]
.filter[TraceIdMDCFilter]
.filter[ThriftMDCFilter]
.filter[StatsFilter]
.filter[AccessLoggingFilter]
.filter[ExceptionMappingFilter]
.exceptionMapper[UnknownLoggingExceptionMapper]
.filter[DarkTrafficFilter[FollowRecommendationsThriftService.ReqRepServicePerEndpoint]]
.add[ThriftController]
}
override def configureThriftServer(server: ThriftMux.Server): ThriftMux.Server = {
server.withProtocolFactory(
Protocols.binaryFactory(
stringLengthLimit = StringLengthLimit,
containerLengthLimit = ContainerLengthLimit))
}
override def configureHttp(router: HttpRouter): Unit = router.add(
ProductMixerController[FollowRecommendationsThriftService.MethodPerEndpoint](
this.injector,
FollowRecommendationsThriftService.ExecutePipeline))
override def warmup(): Unit = {
handle[FollowRecommendationsServiceWarmupHandler]()
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/Action.scala | package com.twitter.follow_recommendations.assembler.models
import com.twitter.follow_recommendations.{thriftscala => t}
case class Action(text: String, actionURL: String) {
lazy val toThrift: t.Action = {
t.Action(text, actionURL)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"follow-recommendations-service/thrift/src/main/thrift:thrift-scala",
"stringcenter/client",
],
exports = [
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/Config.scala | package com.twitter.follow_recommendations.assembler.models
import com.twitter.stringcenter.client.core.ExternalString
case class HeaderConfig(title: TitleConfig)
case class TitleConfig(text: ExternalString)
case class FooterConfig(actionConfig: Option[ActionConfig])
case class ActionConfig(footerText: ExternalString, actionURL: String)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/FeedbackAction.scala | package com.twitter.follow_recommendations.assembler.models
import com.twitter.follow_recommendations.{thriftscala => t}
trait FeedbackAction {
def toThrift: t.FeedbackAction
}
case class DismissUserId() extends FeedbackAction {
override lazy val toThrift: t.FeedbackAction = {
t.FeedbackAction.DismissUserId(t.DismissUserId())
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/Footer.scala | package com.twitter.follow_recommendations.assembler.models
import com.twitter.follow_recommendations.{thriftscala => t}
case class Footer(action: Option[Action]) {
lazy val toThrift: t.Footer = {
t.Footer(action.map(_.toThrift))
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/Header.scala | package com.twitter.follow_recommendations.assembler.models
import com.twitter.follow_recommendations.{thriftscala => t}
case class Header(title: Title) {
lazy val toThrift: t.Header = {
t.Header(title.toThrift)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/Layout.scala | package com.twitter.follow_recommendations.assembler.models
sealed trait Layout
case class UserListLayout(
header: Option[HeaderConfig],
userListOptions: UserListOptions,
socialProofs: Option[Seq[SocialProof]],
footer: Option[FooterConfig])
extends Layout
case class CarouselLayout(
header: Option[HeaderConfig],
carouselOptions: CarouselOptions,
socialProofs: Option[Seq[SocialProof]])
extends Layout
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/RecommendationOptions.scala | package com.twitter.follow_recommendations.assembler.models
sealed trait RecommendationOptions
case class UserListOptions(
userBioEnabled: Boolean,
userBioTruncated: Boolean,
userBioMaxLines: Option[Long],
) extends RecommendationOptions
case class CarouselOptions() extends RecommendationOptions
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/SocialProof.scala | package com.twitter.follow_recommendations.assembler.models
import com.twitter.stringcenter.client.core.ExternalString
sealed trait SocialProof
case class GeoContextProof(popularInCountryText: ExternalString) extends SocialProof
case class FollowedByUsersProof(text1: ExternalString, text2: ExternalString, textN: ExternalString)
extends SocialProof
sealed trait SocialText {
def text: String
}
case class GeoSocialText(text: String) extends SocialText
case class FollowedByUsersText(text: String) extends SocialText
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/Title.scala | package com.twitter.follow_recommendations.assembler.models
import com.twitter.follow_recommendations.{thriftscala => t}
case class Title(text: String) {
lazy val toThrift: t.Title = {
t.Title(text)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models/WTFPresentation.scala | package com.twitter.follow_recommendations.assembler.models
import com.twitter.follow_recommendations.{thriftscala => t}
trait WTFPresentation {
def toThrift: t.WTFPresentation
}
case class UserList(
userBioEnabled: Boolean,
userBioTruncated: Boolean,
userBioMaxLines: Option[Long],
feedbackAction: Option[FeedbackAction])
extends WTFPresentation {
def toThrift: t.WTFPresentation = {
t.WTFPresentation.UserBioList(
t.UserList(userBioEnabled, userBioTruncated, userBioMaxLines, feedbackAction.map(_.toThrift)))
}
}
object UserList {
def fromUserListOptions(
userListOptions: UserListOptions
): UserList = {
UserList(
userListOptions.userBioEnabled,
userListOptions.userBioTruncated,
userListOptions.userBioMaxLines,
None)
}
}
case class Carousel(
feedbackAction: Option[FeedbackAction])
extends WTFPresentation {
def toThrift: t.WTFPresentation = {
t.WTFPresentation.Carousel(t.Carousel(feedbackAction.map(_.toThrift)))
}
}
object Carousel {
def fromCarouselOptions(
carouselOptions: CarouselOptions
): Carousel = {
Carousel(None)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/blenders/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"3rdparty/jvm/com/google/inject/extensions:guice-assistedinject",
"3rdparty/jvm/net/codingwell:scala-guice",
"3rdparty/jvm/org/slf4j:slf4j-api",
"finatra/inject/inject-core/src/main/scala",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/base",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models",
"util/util-slf4j-api/src/main/scala",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/blenders/PromotedAccountsBlender.scala | package com.twitter.follow_recommendations.blenders
import com.google.common.annotations.VisibleForTesting
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.Transform
import com.twitter.follow_recommendations.common.models.AdMetadata
import com.twitter.follow_recommendations.common.models.Recommendation
import com.twitter.inject.Logging
import com.twitter.stitch.Stitch
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class PromotedAccountsBlender @Inject() (statsReceiver: StatsReceiver)
extends Transform[Int, Recommendation]
with Logging {
import PromotedAccountsBlender._
val stats = statsReceiver.scope(Name)
val inputOrganicAccounts = stats.counter(InputOrganic)
val inputPromotedAccounts = stats.counter(InputPromoted)
val outputOrganicAccounts = stats.counter(OutputOrganic)
val outputPromotedAccounts = stats.counter(OutputPromoted)
val promotedAccountsStats = stats.scope(NumPromotedAccounts)
override def transform(
maxResults: Int,
items: Seq[Recommendation]
): Stitch[Seq[Recommendation]] = {
val (promoted, organic) = items.partition(_.isPromotedAccount)
val promotedIds = promoted.map(_.id).toSet
val dedupedOrganic = organic.filterNot(u => promotedIds.contains(u.id))
val blended = blendPromotedAccount(dedupedOrganic, promoted, maxResults)
val (outputPromoted, outputOrganic) = blended.partition(_.isPromotedAccount)
inputOrganicAccounts.incr(dedupedOrganic.size)
inputPromotedAccounts.incr(promoted.size)
outputOrganicAccounts.incr(outputOrganic.size)
val size = outputPromoted.size
outputPromotedAccounts.incr(size)
if (size <= 5) {
promotedAccountsStats.counter(outputPromoted.size.toString).incr()
} else {
promotedAccountsStats.counter(MoreThan5Promoted).incr()
}
Stitch.value(blended)
}
/**
* Merge Promoted results and organic results. Promoted result dictates the position
* in the merge list.
*
* merge a list of positioned users, aka. promoted, and a list of organic
* users. The positioned promoted users are pre-sorted with regards to their
* position ascendingly. Only requirement about position is to be within the
* range, i.e, can not exceed the combined length if merge is successful, ok
* to be at the last position, but not beyond.
* For more detailed description of location position:
* http://confluence.local.twitter.com/display/ADS/Promoted+Tweets+in+Timeline+Design+Document
*/
@VisibleForTesting
private[blenders] def mergePromotedAccounts(
organicUsers: Seq[Recommendation],
promotedUsers: Seq[Recommendation]
): Seq[Recommendation] = {
def mergeAccountWithIndex(
organicUsers: Seq[Recommendation],
promotedUsers: Seq[Recommendation],
index: Int
): Stream[Recommendation] = {
if (promotedUsers.isEmpty) organicUsers.toStream
else {
val promotedHead = promotedUsers.head
val promotedTail = promotedUsers.tail
promotedHead.adMetadata match {
case Some(AdMetadata(position, _)) =>
if (position < 0) mergeAccountWithIndex(organicUsers, promotedTail, index)
else if (position == index)
promotedHead #:: mergeAccountWithIndex(organicUsers, promotedTail, index)
else if (organicUsers.isEmpty) organicUsers.toStream
else {
val organicHead = organicUsers.head
val organicTail = organicUsers.tail
organicHead #:: mergeAccountWithIndex(organicTail, promotedUsers, index + 1)
}
case _ =>
logger.error("Unknown Candidate type in mergePromotedAccounts")
Stream.empty
}
}
}
mergeAccountWithIndex(organicUsers, promotedUsers, 0)
}
private[this] def blendPromotedAccount(
organic: Seq[Recommendation],
promoted: Seq[Recommendation],
maxResults: Int
): Seq[Recommendation] = {
val merged = mergePromotedAccounts(organic, promoted)
val mergedServed = merged.take(maxResults)
val promotedServed = promoted.intersect(mergedServed)
if (isBlendPromotedNeeded(
mergedServed.size - promotedServed.size,
promotedServed.size,
maxResults
)) {
mergedServed
} else {
organic.take(maxResults)
}
}
@VisibleForTesting
private[blenders] def isBlendPromotedNeeded(
organicSize: Int,
promotedSize: Int,
maxResults: Int
): Boolean = {
(organicSize > 1) &&
(promotedSize > 0) &&
(promotedSize < organicSize) &&
(promotedSize <= 2) &&
(maxResults > 1)
}
}
object PromotedAccountsBlender {
val Name = "promoted_accounts_blender"
val InputOrganic = "input_organic_accounts"
val InputPromoted = "input_promoted_accounts"
val OutputOrganic = "output_organic_accounts"
val OutputPromoted = "output_promoted_accounts"
val NumPromotedAccounts = "num_promoted_accounts"
val MoreThan5Promoted = "more_than_5"
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"configapi/configapi-core",
"configapi/configapi-decider",
"configapi/configapi-featureswitches:v2",
"featureswitches/featureswitches-core",
"featureswitches/featureswitches-core:v2",
"featureswitches/featureswitches-core/src/main/scala/com/twitter/featureswitches/v2/builder",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/crowd_search_accounts",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/real_graph",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/recent_engagement",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/sims",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/stp",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/top_organic_follows_accounts",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/triangular_loops",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/rankers/ml_ranker/ranking",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/common",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/deciders",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/params",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/products",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/ConfigBuilder.scala | package com.twitter.follow_recommendations.configapi
import com.twitter.timelines.configapi.CompositeConfig
import com.twitter.timelines.configapi.Config
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class ConfigBuilder @Inject() (
deciderConfigs: DeciderConfigs,
featureSwitchConfigs: FeatureSwitchConfigs) {
// The order of configs added to `CompositeConfig` is important. The config will be matched with
// the first possible rule. So, current setup will give priority to Deciders instead of FS
def build(): Config =
new CompositeConfig(Seq(deciderConfigs.config, featureSwitchConfigs.config))
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/DeciderConfigs.scala | package com.twitter.follow_recommendations.configapi
import com.twitter.decider.Recipient
import com.twitter.decider.SimpleRecipient
import com.twitter.follow_recommendations.configapi.deciders.DeciderKey
import com.twitter.follow_recommendations.configapi.deciders.DeciderParams
import com.twitter.follow_recommendations.products.home_timeline_tweet_recs.configapi.HomeTimelineTweetRecsParams
import com.twitter.servo.decider.DeciderGateBuilder
import com.twitter.timelines.configapi._
import com.twitter.timelines.configapi.decider.DeciderSwitchOverrideValue
import com.twitter.timelines.configapi.decider.GuestRecipient
import com.twitter.timelines.configapi.decider.RecipientBuilder
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class DeciderConfigs @Inject() (deciderGateBuilder: DeciderGateBuilder) {
val overrides: Seq[OptionalOverride[_]] = DeciderConfigs.ParamsToDeciderMap.map {
case (params, deciderKey) =>
params.optionalOverrideValue(
DeciderSwitchOverrideValue(
feature = deciderGateBuilder.keyToFeature(deciderKey),
enabledValue = true,
recipientBuilder = DeciderConfigs.UserOrGuestOrRequest
)
)
}.toSeq
val config: BaseConfig = BaseConfigBuilder(overrides).build("FollowRecommendationServiceDeciders")
}
object DeciderConfigs {
val ParamsToDeciderMap = Map(
DeciderParams.EnableRecommendations -> DeciderKey.EnableRecommendations,
DeciderParams.EnableScoreUserCandidates -> DeciderKey.EnableScoreUserCandidates,
HomeTimelineTweetRecsParams.EnableProduct -> DeciderKey.EnableHomeTimelineTweetRecsProduct,
)
object UserOrGuestOrRequest extends RecipientBuilder {
def apply(requestContext: BaseRequestContext): Option[Recipient] = requestContext match {
case c: WithUserId if c.userId.isDefined =>
c.userId.map(SimpleRecipient)
case c: WithGuestId if c.guestId.isDefined =>
c.guestId.map(GuestRecipient)
case c: WithGuestId =>
RecipientBuilder.Request(c)
case _ =>
throw new UndefinedUserIdNorGuestIDException(requestContext)
}
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/FeatureSwitchConfigs.scala | package com.twitter.follow_recommendations.configapi
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.candidate_sources.base.SocialProofEnforcedCandidateSourceFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.crowd_search_accounts.CrowdSearchAccountsFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopGeoQualityFollowSourceFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.top_organic_follows_accounts.TopOrganicFollowsAccountsFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopGeoSourceFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.ppmi_locale_follow.PPMILocaleFollowSourceFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.real_graph.RealGraphOonFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.recent_engagement.RepeatedProfileVisitsFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.sims.SimsSourceFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentEngagementSimilarUsersFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.SimsExpansionFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.socialgraph.RecentFollowingRecentFollowingExpansionSourceFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.stp.OfflineStpSourceFsConfig
import com.twitter.follow_recommendations.common.candidate_sources.stp.OnlineSTPSourceFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.triangular_loops.TriangularLoopsFSConfig
import com.twitter.follow_recommendations.common.candidate_sources.user_user_graph.UserUserGraphFSConfig
import com.twitter.follow_recommendations.common.feature_hydration.sources.FeatureHydrationSourcesFSConfig
import com.twitter.follow_recommendations.common.rankers.weighted_candidate_source_ranker.WeightedCandidateSourceRankerFSConfig
import com.twitter.follow_recommendations.configapi.common.FeatureSwitchConfig
import com.twitter.follow_recommendations.flows.content_recommender_flow.ContentRecommenderFlowFSConfig
import com.twitter.follow_recommendations.common.predicates.gizmoduck.GizmoduckPredicateFSConfig
import com.twitter.follow_recommendations.common.predicates.hss.HssPredicateFSConfig
import com.twitter.follow_recommendations.common.predicates.sgs.SgsPredicateFSConfig
import com.twitter.follow_recommendations.flows.post_nux_ml.PostNuxMlFlowFSConfig
import com.twitter.logging.Logger
import com.twitter.timelines.configapi.BaseConfigBuilder
import com.twitter.timelines.configapi.FeatureSwitchOverrideUtil
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class FeatureSwitchConfigs @Inject() (
globalFeatureSwitchConfig: GlobalFeatureSwitchConfig,
featureHydrationSourcesFSConfig: FeatureHydrationSourcesFSConfig,
weightedCandidateSourceRankerFSConfig: WeightedCandidateSourceRankerFSConfig,
// Flow related config
contentRecommenderFlowFSConfig: ContentRecommenderFlowFSConfig,
postNuxMlFlowFSConfig: PostNuxMlFlowFSConfig,
// Candidate source related config
crowdSearchAccountsFSConfig: CrowdSearchAccountsFSConfig,
offlineStpSourceFsConfig: OfflineStpSourceFsConfig,
onlineSTPSourceFSConfig: OnlineSTPSourceFSConfig,
popGeoSourceFSConfig: PopGeoSourceFSConfig,
popGeoQualityFollowFSConfig: PopGeoQualityFollowSourceFSConfig,
realGraphOonFSConfig: RealGraphOonFSConfig,
repeatedProfileVisitsFSConfig: RepeatedProfileVisitsFSConfig,
recentEngagementSimilarUsersFSConfig: RecentEngagementSimilarUsersFSConfig,
recentFollowingRecentFollowingExpansionSourceFSConfig: RecentFollowingRecentFollowingExpansionSourceFSConfig,
simsExpansionFSConfig: SimsExpansionFSConfig,
simsSourceFSConfig: SimsSourceFSConfig,
socialProofEnforcedCandidateSourceFSConfig: SocialProofEnforcedCandidateSourceFSConfig,
triangularLoopsFSConfig: TriangularLoopsFSConfig,
userUserGraphFSConfig: UserUserGraphFSConfig,
// Predicate related configs
gizmoduckPredicateFSConfig: GizmoduckPredicateFSConfig,
hssPredicateFSConfig: HssPredicateFSConfig,
sgsPredicateFSConfig: SgsPredicateFSConfig,
ppmiLocaleSourceFSConfig: PPMILocaleFollowSourceFSConfig,
topOrganicFollowsAccountsFSConfig: TopOrganicFollowsAccountsFSConfig,
statsReceiver: StatsReceiver) {
val logger = Logger(classOf[FeatureSwitchConfigs])
val mergedFSConfig =
FeatureSwitchConfig.merge(
Seq(
globalFeatureSwitchConfig,
featureHydrationSourcesFSConfig,
weightedCandidateSourceRankerFSConfig,
// Flow related config
contentRecommenderFlowFSConfig,
postNuxMlFlowFSConfig,
// Candidate source related config
crowdSearchAccountsFSConfig,
offlineStpSourceFsConfig,
onlineSTPSourceFSConfig,
popGeoSourceFSConfig,
popGeoQualityFollowFSConfig,
realGraphOonFSConfig,
repeatedProfileVisitsFSConfig,
recentEngagementSimilarUsersFSConfig,
recentFollowingRecentFollowingExpansionSourceFSConfig,
simsExpansionFSConfig,
simsSourceFSConfig,
socialProofEnforcedCandidateSourceFSConfig,
triangularLoopsFSConfig,
userUserGraphFSConfig,
// Predicate related configs:
gizmoduckPredicateFSConfig,
hssPredicateFSConfig,
sgsPredicateFSConfig,
ppmiLocaleSourceFSConfig,
topOrganicFollowsAccountsFSConfig,
)
)
/**
* enum params have to be listed in this main file together as otherwise we'll have to pass in
* some signature like `Seq[FSEnumParams[_]]` which are generics of generics and won't compile.
* we only have enumFsParams from globalFeatureSwitchConfig at the moment
*/
val enumOverrides = globalFeatureSwitchConfig.enumFsParams.flatMap { enumParam =>
FeatureSwitchOverrideUtil.getEnumFSOverrides(statsReceiver, logger, enumParam)
}
val gatedOverrides = mergedFSConfig.gatedOverridesMap.flatMap {
case (fsName, overrides) =>
FeatureSwitchOverrideUtil.gatedOverrides(fsName, overrides: _*)
}
val enumSeqOverrides = globalFeatureSwitchConfig.enumSeqFsParams.flatMap { enumSeqParam =>
FeatureSwitchOverrideUtil.getEnumSeqFSOverrides(statsReceiver, logger, enumSeqParam)
}
val overrides =
FeatureSwitchOverrideUtil
.getBooleanFSOverrides(mergedFSConfig.booleanFSParams: _*) ++
FeatureSwitchOverrideUtil
.getBoundedIntFSOverrides(mergedFSConfig.intFSParams: _*) ++
FeatureSwitchOverrideUtil
.getBoundedLongFSOverrides(mergedFSConfig.longFSParams: _*) ++
FeatureSwitchOverrideUtil
.getBoundedDoubleFSOverrides(mergedFSConfig.doubleFSParams: _*) ++
FeatureSwitchOverrideUtil
.getDurationFSOverrides(mergedFSConfig.durationFSParams: _*) ++
FeatureSwitchOverrideUtil
.getBoundedOptionalDoubleOverrides(mergedFSConfig.optionalDoubleFSParams: _*) ++
FeatureSwitchOverrideUtil.getStringSeqFSOverrides(mergedFSConfig.stringSeqFSParams: _*) ++
enumOverrides ++
gatedOverrides ++
enumSeqOverrides
val config = BaseConfigBuilder(overrides).build("FollowRecommendationServiceFeatureSwitches")
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/GlobalFeatureSwitchConfig.scala | package com.twitter.follow_recommendations.configapi
import com.twitter.follow_recommendations.common.candidate_sources.crowd_search_accounts.CrowdSearchAccountsParams.AccountsFilteringAndRankingLogics
import com.twitter.follow_recommendations.common.candidate_sources.top_organic_follows_accounts.TopOrganicFollowsAccountsParams.{
AccountsFilteringAndRankingLogics => OrganicAccountsFilteringAndRankingLogics
}
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentEngagementSimilarUsersParams
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.SimsExpansionSourceParams
import com.twitter.follow_recommendations.common.rankers.ml_ranker.ranking.MlRankerParams.CandidateScorerIdParam
import com.twitter.follow_recommendations.configapi.common.FeatureSwitchConfig
import com.twitter.follow_recommendations.configapi.params.GlobalParams.CandidateSourcesToFilter
import com.twitter.follow_recommendations.configapi.params.GlobalParams.EnableCandidateParamHydrations
import com.twitter.follow_recommendations.configapi.params.GlobalParams.EnableGFSSocialProofTransform
import com.twitter.follow_recommendations.configapi.params.GlobalParams.EnableRecommendationFlowLogs
import com.twitter.follow_recommendations.configapi.params.GlobalParams.EnableWhoToFollowProducts
import com.twitter.follow_recommendations.configapi.params.GlobalParams.KeepSocialUserCandidate
import com.twitter.follow_recommendations.configapi.params.GlobalParams.KeepUserCandidate
import com.twitter.timelines.configapi.FSName
import com.twitter.timelines.configapi.Param
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class GlobalFeatureSwitchConfig @Inject() () extends FeatureSwitchConfig {
override val booleanFSParams: Seq[Param[Boolean] with FSName] = {
Seq(
EnableCandidateParamHydrations,
KeepUserCandidate,
KeepSocialUserCandidate,
EnableGFSSocialProofTransform,
EnableWhoToFollowProducts,
EnableRecommendationFlowLogs
)
}
val enumFsParams =
Seq(
CandidateScorerIdParam,
SimsExpansionSourceParams.Aggregator,
RecentEngagementSimilarUsersParams.Aggregator,
CandidateSourcesToFilter,
)
val enumSeqFsParams =
Seq(
AccountsFilteringAndRankingLogics,
OrganicAccountsFilteringAndRankingLogics
)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/ParamsFactory.scala | package com.twitter.follow_recommendations.configapi
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.models.DisplayLocation
import com.twitter.product_mixer.core.model.marshalling.request.ClientContext
import com.twitter.servo.util.MemoizingStatsReceiver
import com.twitter.timelines.configapi.Config
import com.twitter.timelines.configapi.FeatureValue
import com.twitter.timelines.configapi.Params
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class ParamsFactory @Inject() (
config: Config,
requestContextFactory: RequestContextFactory,
statsReceiver: StatsReceiver) {
private val stats = new MemoizingStatsReceiver(statsReceiver.scope("configapi"))
def apply(followRecommendationServiceRequestContext: RequestContext): Params =
config(followRecommendationServiceRequestContext, stats)
def apply(
clientContext: ClientContext,
displayLocation: DisplayLocation,
featureOverrides: Map[String, FeatureValue]
): Params =
apply(requestContextFactory(clientContext, displayLocation, featureOverrides))
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/RequestContext.scala | package com.twitter.follow_recommendations.configapi
import com.twitter.timelines.configapi.BaseRequestContext
import com.twitter.timelines.configapi.FeatureContext
import com.twitter.timelines.configapi.NullFeatureContext
import com.twitter.timelines.configapi.GuestId
import com.twitter.timelines.configapi.UserId
import com.twitter.timelines.configapi.WithFeatureContext
import com.twitter.timelines.configapi.WithGuestId
import com.twitter.timelines.configapi.WithUserId
case class RequestContext(
userId: Option[UserId],
guestId: Option[GuestId],
featureContext: FeatureContext = NullFeatureContext)
extends BaseRequestContext
with WithUserId
with WithGuestId
with WithFeatureContext
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/RequestContextFactory.scala | package com.twitter.follow_recommendations.configapi
import com.google.common.annotations.VisibleForTesting
import com.google.inject.Inject
import com.twitter.decider.Decider
import com.twitter.featureswitches.v2.FeatureSwitches
import com.twitter.featureswitches.{Recipient => FeatureSwitchRecipient}
import com.twitter.follow_recommendations.common.models.DisplayLocation
import com.twitter.product_mixer.core.model.marshalling.request.ClientContext
import com.twitter.snowflake.id.SnowflakeId
import com.twitter.timelines.configapi.FeatureContext
import com.twitter.timelines.configapi.FeatureValue
import com.twitter.timelines.configapi.ForcedFeatureContext
import com.twitter.timelines.configapi.OrElseFeatureContext
import com.twitter.timelines.configapi.featureswitches.v2.FeatureSwitchResultsFeatureContext
import javax.inject.Singleton
/*
* Request Context Factory is used to build RequestContext objects which are used
* by the config api to determine the param overrides to apply to the request.
* The param overrides are determined per request by configs which specify which
* FS/Deciders/AB translate to what param overrides.
*/
@Singleton
class RequestContextFactory @Inject() (featureSwitches: FeatureSwitches, decider: Decider) {
def apply(
clientContext: ClientContext,
displayLocation: DisplayLocation,
featureOverrides: Map[String, FeatureValue]
): RequestContext = {
val featureContext = getFeatureContext(clientContext, displayLocation, featureOverrides)
RequestContext(clientContext.userId, clientContext.guestId, featureContext)
}
private[configapi] def getFeatureContext(
clientContext: ClientContext,
displayLocation: DisplayLocation,
featureOverrides: Map[String, FeatureValue]
): FeatureContext = {
val recipient =
getFeatureSwitchRecipient(clientContext)
.withCustomFields("display_location" -> displayLocation.toFsName)
// userAgeOpt is going to be set to None for logged out users and defaulted to Some(Int.MaxValue) for non-snowflake users
val userAgeOpt = clientContext.userId.map { userId =>
SnowflakeId.timeFromIdOpt(userId).map(_.untilNow.inDays).getOrElse(Int.MaxValue)
}
val recipientWithAccountAge =
userAgeOpt
.map(age => recipient.withCustomFields("account_age_in_days" -> age)).getOrElse(recipient)
val results = featureSwitches.matchRecipient(recipientWithAccountAge)
OrElseFeatureContext(
ForcedFeatureContext(featureOverrides),
new FeatureSwitchResultsFeatureContext(results))
}
@VisibleForTesting
private[configapi] def getFeatureSwitchRecipient(
clientContext: ClientContext
): FeatureSwitchRecipient = {
FeatureSwitchRecipient(
userId = clientContext.userId,
userRoles = clientContext.userRoles,
deviceId = clientContext.deviceId,
guestId = clientContext.guestId,
languageCode = clientContext.languageCode,
countryCode = clientContext.countryCode,
isVerified = None,
clientApplicationId = clientContext.appId,
isTwoffice = clientContext.isTwoffice
)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/candidates/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"configapi/configapi-core",
"configapi/configapi-decider",
"configapi/configapi-featureswitches:v2",
"featureswitches/featureswitches-core",
"featureswitches/featureswitches-core:v2",
"featureswitches/featureswitches-core/src/main/scala/com/twitter/featureswitches/v2/builder",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/base",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/deciders",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/params",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/candidates/CandidateUserContext.scala | package com.twitter.follow_recommendations.configapi.candidates
import com.twitter.timelines.configapi.BaseRequestContext
import com.twitter.timelines.configapi.FeatureContext
import com.twitter.timelines.configapi.NullFeatureContext
import com.twitter.timelines.configapi.WithFeatureContext
import com.twitter.timelines.configapi.WithUserId
/**
* represent the context for a recommendation candidate (producer side)
* @param userId id of the recommended user
* @param featureContext feature context
*/
case class CandidateUserContext(
override val userId: Option[Long],
featureContext: FeatureContext = NullFeatureContext)
extends BaseRequestContext
with WithUserId
with WithFeatureContext
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/candidates/CandidateUserContextFactory.scala | package com.twitter.follow_recommendations.configapi.candidates
import com.google.common.annotations.VisibleForTesting
import com.google.inject.Inject
import com.twitter.decider.Decider
import com.twitter.featureswitches.v2.FeatureSwitches
import com.twitter.featureswitches.{Recipient => FeatureSwitchRecipient}
import com.twitter.follow_recommendations.common.constants.GuiceNamedConstants.PRODUCER_SIDE_FEATURE_SWITCHES
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.models.DisplayLocation
import com.twitter.timelines.configapi.FeatureContext
import com.twitter.timelines.configapi.featureswitches.v2.FeatureSwitchResultsFeatureContext
import javax.inject.Named
import javax.inject.Singleton
@Singleton
class CandidateUserContextFactory @Inject() (
@Named(PRODUCER_SIDE_FEATURE_SWITCHES) featureSwitches: FeatureSwitches,
decider: Decider) {
def apply(
candidateUser: CandidateUser,
displayLocation: DisplayLocation
): CandidateUserContext = {
val featureContext = getFeatureContext(candidateUser, displayLocation)
CandidateUserContext(Some(candidateUser.id), featureContext)
}
private[configapi] def getFeatureContext(
candidateUser: CandidateUser,
displayLocation: DisplayLocation
): FeatureContext = {
val recipient = getFeatureSwitchRecipient(candidateUser).withCustomFields(
"display_location" -> displayLocation.toFsName)
new FeatureSwitchResultsFeatureContext(featureSwitches.matchRecipient(recipient))
}
@VisibleForTesting
private[configapi] def getFeatureSwitchRecipient(
candidateUser: CandidateUser
): FeatureSwitchRecipient = {
FeatureSwitchRecipient(
userId = Some(candidateUser.id),
userRoles = None,
deviceId = None,
guestId = None,
languageCode = None,
countryCode = None,
isVerified = None,
clientApplicationId = None,
isTwoffice = None
)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/candidates/CandidateUserParamsFactory.scala | package com.twitter.follow_recommendations.configapi.candidates
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.models.HasDisplayLocation
import com.twitter.follow_recommendations.configapi.params.GlobalParams
import com.twitter.servo.util.MemoizingStatsReceiver
import com.twitter.timelines.configapi.Config
import com.twitter.timelines.configapi.HasParams
import com.twitter.timelines.configapi.Params
import javax.inject.Inject
import javax.inject.Singleton
/**
* CandidateParamsFactory is primarily used for "producer side" experiments, don't use it on consumer side experiments
*/
@Singleton
class CandidateUserParamsFactory[T <: HasParams with HasDisplayLocation] @Inject() (
config: Config,
candidateContextFactory: CandidateUserContextFactory,
statsReceiver: StatsReceiver) {
private val stats = new MemoizingStatsReceiver(statsReceiver.scope("configapi_candidate_params"))
def apply(candidateContext: CandidateUser, request: T): CandidateUser = {
if (candidateContext.params == Params.Invalid) {
if (request.params(GlobalParams.EnableCandidateParamHydrations)) {
candidateContext.copy(params =
config(candidateContextFactory(candidateContext, request.displayLocation), stats))
} else {
candidateContext.copy(params = Params.Empty)
}
} else {
candidateContext
}
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/candidates/HydrateCandidateParamsTransform.scala | package com.twitter.follow_recommendations.configapi.candidates
import com.google.inject.Inject
import com.google.inject.Singleton
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.models.HasDisplayLocation
import com.twitter.follow_recommendations.common.base.Transform
import com.twitter.stitch.Stitch
import com.twitter.timelines.configapi.HasParams
import com.twitter.util.logging.Logging
@Singleton
class HydrateCandidateParamsTransform[Target <: HasParams with HasDisplayLocation] @Inject() (
candidateParamsFactory: CandidateUserParamsFactory[Target])
extends Transform[Target, CandidateUser]
with Logging {
def transform(target: Target, candidates: Seq[CandidateUser]): Stitch[Seq[CandidateUser]] = {
Stitch.value(candidates.map(candidateParamsFactory.apply(_, target)))
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/common/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"configapi/configapi-core",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/common/FeatureSwitchConfig.scala | package com.twitter.follow_recommendations.configapi.common
import com.twitter.timelines.configapi.FeatureSwitchOverrideUtil.DefinedFeatureName
import com.twitter.timelines.configapi.FeatureSwitchOverrideUtil.ValueFeatureName
import com.twitter.timelines.configapi.BoundedParam
import com.twitter.timelines.configapi.FSBoundedParam
import com.twitter.timelines.configapi.FSName
import com.twitter.timelines.configapi.HasDurationConversion
import com.twitter.timelines.configapi.OptionalOverride
import com.twitter.timelines.configapi.Param
import com.twitter.util.Duration
trait FeatureSwitchConfig {
def booleanFSParams: Seq[Param[Boolean] with FSName] = Nil
def intFSParams: Seq[FSBoundedParam[Int]] = Nil
def longFSParams: Seq[FSBoundedParam[Long]] = Nil
def doubleFSParams: Seq[FSBoundedParam[Double]] = Nil
def durationFSParams: Seq[FSBoundedParam[Duration] with HasDurationConversion] = Nil
def optionalDoubleFSParams: Seq[
(BoundedParam[Option[Double]], DefinedFeatureName, ValueFeatureName)
] = Nil
def stringSeqFSParams: Seq[Param[Seq[String]] with FSName] = Nil
/**
* Apply overrides in list when the given FS Key is enabled.
* This override type does NOT work with experiments. Params here will be evaluated for every
* request IMMEDIATELY, not upon param.apply. If you would like to use an experiment pls use
* the primitive type or ENUM overrides.
*/
def gatedOverridesMap: Map[String, Seq[OptionalOverride[_]]] = Map.empty
}
object FeatureSwitchConfig {
def merge(configs: Seq[FeatureSwitchConfig]): FeatureSwitchConfig = new FeatureSwitchConfig {
override def booleanFSParams: Seq[Param[Boolean] with FSName] =
configs.flatMap(_.booleanFSParams)
override def intFSParams: Seq[FSBoundedParam[Int]] =
configs.flatMap(_.intFSParams)
override def longFSParams: Seq[FSBoundedParam[Long]] =
configs.flatMap(_.longFSParams)
override def durationFSParams: Seq[FSBoundedParam[Duration] with HasDurationConversion] =
configs.flatMap(_.durationFSParams)
override def gatedOverridesMap: Map[String, Seq[OptionalOverride[_]]] =
configs.flatMap(_.gatedOverridesMap).toMap
override def doubleFSParams: Seq[FSBoundedParam[Double]] =
configs.flatMap(_.doubleFSParams)
override def optionalDoubleFSParams: Seq[
(BoundedParam[Option[Double]], DefinedFeatureName, ValueFeatureName)
] =
configs.flatMap(_.optionalDoubleFSParams)
override def stringSeqFSParams: Seq[Param[Seq[String]] with FSName] =
configs.flatMap(_.stringSeqFSParams)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/deciders/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"configapi/configapi-core",
"configapi/configapi-decider",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/deciders/DeciderKey.scala | package com.twitter.follow_recommendations.configapi.deciders
import com.twitter.servo.decider.DeciderKeyEnum
object DeciderKey extends DeciderKeyEnum {
val EnableDiffyModuleDarkReading = Value("enable_diffy_module_dark_reading")
val EnableRecommendations = Value("enable_recommendations")
val EnableScoreUserCandidates = Value("enable_score_user_candidates")
val EnableProfileSidebarProduct = Value("enable_profile_sidebar_product")
val EnableMagicRecsProduct = Value("enable_magic_recs_product")
val EnableRuxLandingPageProduct = Value("enable_rux_landing_page_product")
val EnableRuxPymkProduct = Value("enable_rux_pymk_product")
val EnableProfileBonusFollowProduct = Value("enable_profile_bonus_follow_product")
val EnableElectionExploreWtfProduct = Value("enable_election_explore_wtf_product")
val EnableClusterFollowProduct = Value("enable_cluster_follow_product")
val EnableHomeTimelineProduct = Value("enable_home_timeline_product")
val EnableHtlBonusFollowProduct = Value("enable_htl_bonus_follow_product")
val EnableExploreTabProduct = Value("enable_explore_tab_product")
val EnableSidebarProduct = Value("enable_sidebar_product")
val EnableNuxPymkProduct = Value("enable_nux_pymk_product")
val EnableNuxInterestsProduct = Value("enable_nux_interests_product")
val EnableNuxTopicBonusFollowProduct = Value("enable_nux_topic_bonus_follow_product")
val EnableCampaignFormProduct = Value("enable_campaign_form_product")
val EnableReactiveFollowProduct = Value("enable_reactive_follow_product")
val EnableIndiaCovid19CuratedAccountsWtfProduct = Value(
"enable_india_covid19_curated_accounts_wtf_product")
val EnableAbUploadProduct = Value("enable_ab_upload_product")
val EnablePeolePlusPlusProduct = Value("enable_people_plus_plus_product")
val EnableTweetNotificationRecsProduct = Value("enable_tweet_notification_recs_product")
val EnableProfileDeviceFollow = Value("enable_profile_device_follow_product")
val EnableRecosBackfillProduct = Value("enable_recos_backfill_product")
val EnablePostNuxFollowTaskProduct = Value("enable_post_nux_follow_task_product")
val EnableCuratedSpaceHostsProduct = Value("enable_curated_space_hosts_product")
val EnableNuxGeoCategoryProduct = Value("enable_nux_geo_category_product")
val EnableNuxInterestsCategoryProduct = Value("enable_nux_interests_category_product")
val EnableNuxPymkCategoryProduct = Value("enable_nux_pymk_category_product")
val EnableHomeTimelineTweetRecsProduct = Value("enable_home_timeline_tweet_recs_product")
val EnableHtlBulkFriendFollowsProduct = Value("enable_htl_bulk_friend_follows_product")
val EnableNuxAutoFollowProduct = Value("enable_nux_auto_follow_product")
val EnableSearchBonusFollowProduct = Value("enable_search_bonus_follow_product")
val EnableFetchUserInRequestBuilder = Value("enable_fetch_user_in_request_builder")
val EnableProductMixerMagicRecsProduct = Value("enable_product_mixer_magic_recs_product")
val EnableHomeTimelineReverseChronProduct = Value("enable_home_timeline_reverse_chron_product")
val EnableProductMixerPipelineMagicRecsDarkRead = Value(
"enable_product_mixer_pipeline_magic_recs_dark_read")
val EnableExperimentalCaching = Value("enable_experimental_caching")
val EnableDistributedCaching = Value("enable_distributed_caching")
val EnableGizmoduckCaching = Value("enable_gizmoduck_caching")
val EnableTrafficDarkReading = Value("enable_traffic_dark_reading")
val EnableGraphFeatureServiceRequests = Value("enable_graph_feature_service_requests")
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/deciders/DeciderParams.scala | package com.twitter.follow_recommendations.configapi.deciders
import com.twitter.timelines.configapi.Param
object DeciderParams {
object EnableRecommendations extends Param[Boolean](false)
object EnableScoreUserCandidates extends Param[Boolean](false)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/params/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"configapi/configapi-core",
"configapi/configapi-decider",
"configapi/configapi-featureswitches:v2",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/deciders",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/params/GlobalParams.scala | package com.twitter.follow_recommendations.configapi.params
import com.twitter.follow_recommendations.models.CandidateSourceType
import com.twitter.timelines.configapi.FSEnumParam
import com.twitter.timelines.configapi.FSParam
/**
* When adding Producer side experiments, make sure to register the FS Key in [[ProducerFeatureFilter]]
* in [[FeatureSwitchesModule]], otherwise, the FS will not work.
*/
object GlobalParams {
object EnableCandidateParamHydrations
extends FSParam[Boolean]("frs_receiver_enable_candidate_params", false)
object KeepUserCandidate
extends FSParam[Boolean]("frs_receiver_holdback_keep_user_candidate", true)
object KeepSocialUserCandidate
extends FSParam[Boolean]("frs_receiver_holdback_keep_social_user_candidate", true)
case object EnableGFSSocialProofTransform
extends FSParam("social_proof_transform_use_graph_feature_service", true)
case object EnableWhoToFollowProducts extends FSParam("who_to_follow_product_enabled", true)
case object CandidateSourcesToFilter
extends FSEnumParam[CandidateSourceType.type](
"candidate_sources_type_filter_id",
CandidateSourceType.None,
CandidateSourceType)
object EnableRecommendationFlowLogs
extends FSParam[Boolean]("frs_recommendation_flow_logs_enabled", false)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/controllers/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"3rdparty/jvm/com/google/inject/extensions:guice-assistedinject",
"3rdparty/jvm/javax/inject:javax.inject",
"3rdparty/jvm/net/codingwell:scala-guice",
"3rdparty/jvm/org/slf4j:slf4j-api",
"decider/src/main/scala",
"finagle/finagle-core/src/main",
"finatra/inject/inject-core/src/main/scala",
"finatra/thrift/src/main/scala/com/twitter/finatra/thrift",
"finatra/thrift/src/main/scala/com/twitter/finatra/thrift:controller",
"finatra/thrift/src/main/scala/com/twitter/finatra/thrift/exceptions",
"finatra/thrift/src/main/scala/com/twitter/finatra/thrift/filters",
"finatra/thrift/src/main/scala/com/twitter/finatra/thrift/modules",
"finatra/thrift/src/main/scala/com/twitter/finatra/thrift/response",
"finatra/thrift/src/main/scala/com/twitter/finatra/thrift/routing",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/services",
"follow-recommendations-service/thrift/src/main/thrift:thrift-scala",
"product-mixer/core/src/main/scala/com/twitter/product_mixer/core/service/debug_query",
"scrooge/scrooge-core/src/main/scala",
"util/util-core:scala",
"util/util-slf4j-api/src/main/scala",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/controllers/CandidateUserDebugParamsBuilder.scala | package com.twitter.follow_recommendations.controllers
import com.twitter.follow_recommendations.common.models._
import com.twitter.follow_recommendations.configapi.ParamsFactory
import com.twitter.follow_recommendations.models.CandidateUserDebugParams
import com.twitter.follow_recommendations.models.FeatureValue
import com.twitter.follow_recommendations.{thriftscala => t}
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class CandidateUserDebugParamsBuilder @Inject() (paramsFactory: ParamsFactory) {
def fromThrift(req: t.ScoringUserRequest): CandidateUserDebugParams = {
val clientContext = ClientContextConverter.fromThrift(req.clientContext)
val displayLocation = DisplayLocation.fromThrift(req.displayLocation)
CandidateUserDebugParams(req.candidates.map { candidate =>
candidate.userId -> paramsFactory(
clientContext,
displayLocation,
candidate.featureOverrides
.map(_.mapValues(FeatureValue.fromThrift).toMap).getOrElse(Map.empty))
}.toMap)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/controllers/RecommendationRequestBuilder.scala | package com.twitter.follow_recommendations.controllers
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.models.ClientContextConverter
import com.twitter.follow_recommendations.common.models.DisplayLocation
import com.twitter.follow_recommendations.models.DebugParams
import com.twitter.follow_recommendations.models.DisplayContext
import com.twitter.follow_recommendations.models.RecommendationRequest
import com.twitter.follow_recommendations.{thriftscala => t}
import com.twitter.gizmoduck.thriftscala.UserType
import com.twitter.stitch.Stitch
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class RecommendationRequestBuilder @Inject() (
requestBuilderUserFetcher: RequestBuilderUserFetcher,
statsReceiver: StatsReceiver) {
private val scopedStats = statsReceiver.scope(this.getClass.getSimpleName)
private val isSoftUserCounter = scopedStats.counter("is_soft_user")
def fromThrift(tRequest: t.RecommendationRequest): Stitch[RecommendationRequest] = {
requestBuilderUserFetcher.fetchUser(tRequest.clientContext.userId).map { userOpt =>
val isSoftUser = userOpt.exists(_.userType == UserType.Soft)
if (isSoftUser) isSoftUserCounter.incr()
RecommendationRequest(
clientContext = ClientContextConverter.fromThrift(tRequest.clientContext),
displayLocation = DisplayLocation.fromThrift(tRequest.displayLocation),
displayContext = tRequest.displayContext.map(DisplayContext.fromThrift),
maxResults = tRequest.maxResults,
cursor = tRequest.cursor,
excludedIds = tRequest.excludedIds,
fetchPromotedContent = tRequest.fetchPromotedContent,
debugParams = tRequest.debugParams.map(DebugParams.fromThrift),
userLocationState = tRequest.userLocationState,
isSoftUser = isSoftUser
)
}
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/controllers/RequestBuilderUserFetcher.scala | package com.twitter.follow_recommendations.controllers
import com.twitter.decider.Decider
import com.twitter.decider.SimpleRecipient
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.StatsUtil
import com.twitter.follow_recommendations.configapi.deciders.DeciderKey
import com.twitter.gizmoduck.thriftscala.LookupContext
import com.twitter.gizmoduck.thriftscala.User
import com.twitter.stitch.Stitch
import com.twitter.stitch.gizmoduck.Gizmoduck
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class RequestBuilderUserFetcher @Inject() (
gizmoduck: Gizmoduck,
statsReceiver: StatsReceiver,
decider: Decider) {
private val scopedStats = statsReceiver.scope(this.getClass.getSimpleName)
def fetchUser(userIdOpt: Option[Long]): Stitch[Option[User]] = {
userIdOpt match {
case Some(userId) if enableDecider(userId) =>
val stitch = gizmoduck
.getUserById(
userId = userId,
context = LookupContext(
forUserId = Some(userId),
includeProtected = true,
includeSoftUsers = true
)
).map(user => Some(user))
StatsUtil
.profileStitch(stitch, scopedStats)
.handle {
case _: Throwable => None
}
case _ => Stitch.None
}
}
private def enableDecider(userId: Long): Boolean = {
decider.isAvailable(
DeciderKey.EnableFetchUserInRequestBuilder.toString,
Some(SimpleRecipient(userId)))
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/controllers/ScoringUserRequestBuilder.scala | package com.twitter.follow_recommendations.controllers
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.models.ClientContextConverter
import com.twitter.follow_recommendations.common.models.DebugOptions
import com.twitter.follow_recommendations.common.models.DisplayLocation
import com.twitter.follow_recommendations.models.DebugParams
import com.twitter.follow_recommendations.models.ScoringUserRequest
import com.twitter.timelines.configapi.Params
import javax.inject.Inject
import javax.inject.Singleton
import com.twitter.follow_recommendations.{thriftscala => t}
import com.twitter.gizmoduck.thriftscala.UserType
import com.twitter.stitch.Stitch
@Singleton
class ScoringUserRequestBuilder @Inject() (
requestBuilderUserFetcher: RequestBuilderUserFetcher,
candidateUserDebugParamsBuilder: CandidateUserDebugParamsBuilder,
statsReceiver: StatsReceiver) {
private val scopedStats = statsReceiver.scope(this.getClass.getSimpleName)
private val isSoftUserCounter = scopedStats.counter("is_soft_user")
def fromThrift(req: t.ScoringUserRequest): Stitch[ScoringUserRequest] = {
requestBuilderUserFetcher.fetchUser(req.clientContext.userId).map { userOpt =>
val isSoftUser = userOpt.exists(_.userType == UserType.Soft)
if (isSoftUser) isSoftUserCounter.incr()
val candidateUsersParamsMap = candidateUserDebugParamsBuilder.fromThrift(req)
val candidates = req.candidates.map { candidate =>
CandidateUser
.fromUserRecommendation(candidate).copy(params =
candidateUsersParamsMap.paramsMap.getOrElse(candidate.userId, Params.Invalid))
}
ScoringUserRequest(
clientContext = ClientContextConverter.fromThrift(req.clientContext),
displayLocation = DisplayLocation.fromThrift(req.displayLocation),
params = Params.Empty,
debugOptions = req.debugParams.map(DebugOptions.fromDebugParamsThrift),
recentFollowedUserIds = None,
recentFollowedByUserIds = None,
wtfImpressions = None,
similarToUserIds = Nil,
candidates = candidates,
debugParams = req.debugParams.map(DebugParams.fromThrift),
isSoftUser = isSoftUser
)
}
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/controllers/ThriftController.scala | package com.twitter.follow_recommendations.controllers
import com.twitter.finatra.thrift.Controller
import com.twitter.follow_recommendations.configapi.ParamsFactory
import com.twitter.follow_recommendations.services.ProductPipelineSelector
import com.twitter.follow_recommendations.services.UserScoringService
import com.twitter.follow_recommendations.thriftscala.FollowRecommendationsThriftService
import com.twitter.follow_recommendations.thriftscala.FollowRecommendationsThriftService._
import com.twitter.stitch.Stitch
import javax.inject.Inject
class ThriftController @Inject() (
userScoringService: UserScoringService,
recommendationRequestBuilder: RecommendationRequestBuilder,
scoringUserRequestBuilder: ScoringUserRequestBuilder,
productPipelineSelector: ProductPipelineSelector,
paramsFactory: ParamsFactory)
extends Controller(FollowRecommendationsThriftService) {
handle(GetRecommendations) { args: GetRecommendations.Args =>
val stitch = recommendationRequestBuilder.fromThrift(args.request).flatMap { request =>
val params = paramsFactory(
request.clientContext,
request.displayLocation,
request.debugParams.flatMap(_.featureOverrides).getOrElse(Map.empty))
productPipelineSelector.selectPipeline(request, params).map(_.toThrift)
}
Stitch.run(stitch)
}
handle(ScoreUserCandidates) { args: ScoreUserCandidates.Args =>
val stitch = scoringUserRequestBuilder.fromThrift(args.request).flatMap { request =>
val params = paramsFactory(
request.clientContext,
request.displayLocation,
request.debugParams.flatMap(_.featureOverrides).getOrElse(Map.empty))
userScoringService.get(request.copy(params = params)).map(_.toThrift)
}
Stitch.run(stitch)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/ads/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"3rdparty/jvm/com/google/inject/extensions:guice-assistedinject",
"3rdparty/jvm/net/codingwell:scala-guice",
"3rdparty/jvm/org/slf4j:slf4j-api",
"finatra/inject/inject-core/src/main/scala",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/base",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/promoted_accounts",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/tracking_token",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/common",
"util/util-slf4j-api/src/main/scala",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/ads/PromotedAccountsFlow.scala | package com.twitter.follow_recommendations.flows.ads
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.EnrichedCandidateSource
import com.twitter.follow_recommendations.common.base.IdentityRanker
import com.twitter.follow_recommendations.common.base.IdentityTransform
import com.twitter.follow_recommendations.common.base.ParamPredicate
import com.twitter.follow_recommendations.common.base.Predicate
import com.twitter.follow_recommendations.common.base.Ranker
import com.twitter.follow_recommendations.common.base.RecommendationFlow
import com.twitter.follow_recommendations.common.base.RecommendationResultsConfig
import com.twitter.follow_recommendations.common.base.Transform
import com.twitter.follow_recommendations.common.base.TruePredicate
import com.twitter.follow_recommendations.common.candidate_sources.promoted_accounts.PromotedAccountsCandidateSource
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.predicates.ExcludedUserIdPredicate
import com.twitter.follow_recommendations.common.transforms.tracking_token.TrackingTokenTransform
import com.twitter.inject.annotations.Flag
import com.twitter.product_mixer.core.functional_component.candidate_source.CandidateSource
import com.twitter.util.Duration
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class PromotedAccountsFlow @Inject() (
promotedAccountsCandidateSource: PromotedAccountsCandidateSource,
trackingTokenTransform: TrackingTokenTransform,
baseStatsReceiver: StatsReceiver,
@Flag("fetch_prod_promoted_accounts") fetchProductionPromotedAccounts: Boolean)
extends RecommendationFlow[PromotedAccountsFlowRequest, CandidateUser] {
protected override def targetEligibility: Predicate[PromotedAccountsFlowRequest] =
new ParamPredicate[PromotedAccountsFlowRequest](
PromotedAccountsFlowParams.TargetEligibility
)
protected override def candidateSources(
target: PromotedAccountsFlowRequest
): Seq[CandidateSource[PromotedAccountsFlowRequest, CandidateUser]] = {
import EnrichedCandidateSource._
val candidateSourceStats = statsReceiver.scope("candidate_sources")
val budget: Duration = target.params(PromotedAccountsFlowParams.FetchCandidateSourceBudget)
val candidateSources = Seq(
promotedAccountsCandidateSource
.mapKeys[PromotedAccountsFlowRequest](r =>
Seq(r.toAdsRequest(fetchProductionPromotedAccounts)))
.mapValue(PromotedAccountsUtil.toCandidateUser)
).map { candidateSource =>
candidateSource
.failOpenWithin(budget, candidateSourceStats).observe(candidateSourceStats)
}
candidateSources
}
protected override def preRankerCandidateFilter: Predicate[
(PromotedAccountsFlowRequest, CandidateUser)
] = {
val preRankerFilterStats = statsReceiver.scope("pre_ranker")
ExcludedUserIdPredicate.observe(preRankerFilterStats.scope("exclude_user_id_predicate"))
}
/**
* rank the candidates
*/
protected override def selectRanker(
target: PromotedAccountsFlowRequest
): Ranker[PromotedAccountsFlowRequest, CandidateUser] = {
new IdentityRanker[PromotedAccountsFlowRequest, CandidateUser]
}
/**
* transform the candidates after ranking (e.g. dedupping, grouping and etc)
*/
protected override def postRankerTransform: Transform[
PromotedAccountsFlowRequest,
CandidateUser
] = {
new IdentityTransform[PromotedAccountsFlowRequest, CandidateUser]
}
/**
* filter invalid candidates before returning the results.
*
* Some heavy filters e.g. SGS filter could be applied in this step
*/
protected override def validateCandidates: Predicate[
(PromotedAccountsFlowRequest, CandidateUser)
] = {
new TruePredicate[(PromotedAccountsFlowRequest, CandidateUser)]
}
/**
* transform the candidates into results and return
*/
protected override def transformResults: Transform[PromotedAccountsFlowRequest, CandidateUser] = {
trackingTokenTransform
}
/**
* configuration for recommendation results
*/
protected override def resultsConfig(
target: PromotedAccountsFlowRequest
): RecommendationResultsConfig = {
RecommendationResultsConfig(
target.params(PromotedAccountsFlowParams.ResultSizeParam),
target.params(PromotedAccountsFlowParams.BatchSizeParam)
)
}
override val statsReceiver: StatsReceiver = baseStatsReceiver.scope("promoted_accounts_flow")
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/ads/PromotedAccountsFlowParams.scala | package com.twitter.follow_recommendations.flows.ads
import com.twitter.conversions.DurationOps._
import com.twitter.timelines.configapi.Param
import com.twitter.util.Duration
abstract class PromotedAccountsFlowParams[A](default: A) extends Param[A](default) {
override val statName: String = "ads/" + this.getClass.getSimpleName
}
object PromotedAccountsFlowParams {
// number of total slots returned to the end user, available to put ads
case object TargetEligibility extends PromotedAccountsFlowParams[Boolean](true)
case object ResultSizeParam extends PromotedAccountsFlowParams[Int](Int.MaxValue)
case object BatchSizeParam extends PromotedAccountsFlowParams[Int](Int.MaxValue)
case object FetchCandidateSourceBudget
extends PromotedAccountsFlowParams[Duration](1000.millisecond)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/ads/PromotedAccountsFlowRequest.scala | package com.twitter.follow_recommendations.flows.ads
import com.twitter.follow_recommendations.common.clients.adserver.AdRequest
import com.twitter.follow_recommendations.common.models.DisplayLocation
import com.twitter.follow_recommendations.common.models.HasDisplayLocation
import com.twitter.follow_recommendations.common.models.HasExcludedUserIds
import com.twitter.product_mixer.core.model.marshalling.request.ClientContext
import com.twitter.product_mixer.core.model.marshalling.request.HasClientContext
import com.twitter.timelines.configapi.HasParams
import com.twitter.timelines.configapi.Params
case class PromotedAccountsFlowRequest(
override val clientContext: ClientContext,
override val params: Params,
displayLocation: DisplayLocation,
profileId: Option[Long],
// note we also add userId and profileId to excludeUserIds
excludeIds: Seq[Long])
extends HasParams
with HasClientContext
with HasExcludedUserIds
with HasDisplayLocation {
def toAdsRequest(fetchProductionPromotedAccounts: Boolean): AdRequest = {
AdRequest(
clientContext = clientContext,
displayLocation = displayLocation,
isTest = Some(!fetchProductionPromotedAccounts),
profileUserId = profileId
)
}
override val excludedUserIds: Seq[Long] = {
excludeIds ++ clientContext.userId.toSeq ++ profileId.toSeq
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/ads/PromotedAccountsUtil.scala | package com.twitter.follow_recommendations.flows.ads
import com.twitter.follow_recommendations.common.candidate_sources.promoted_accounts.PromotedCandidateUser
import com.twitter.follow_recommendations.common.models.AccountProof
import com.twitter.follow_recommendations.common.models.AdMetadata
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.models.Reason
import com.twitter.follow_recommendations.common.models.UserCandidateSourceDetails
object PromotedAccountsUtil {
def toCandidateUser(promotedCandidateUser: PromotedCandidateUser): CandidateUser = {
CandidateUser(
id = promotedCandidateUser.id,
score = None,
adMetadata =
Some(AdMetadata(promotedCandidateUser.position, promotedCandidateUser.adImpression)),
reason = Some(
Reason(
accountProof = Some(AccountProof(followProof = Some(promotedCandidateUser.followProof))))
),
userCandidateSourceDetails = Some(
UserCandidateSourceDetails(
promotedCandidateUser.primaryCandidateSource,
Map.empty,
Map.empty,
None))
)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"3rdparty/jvm/com/google/inject/extensions:guice-assistedinject",
"3rdparty/jvm/net/codingwell:scala-guice",
"3rdparty/jvm/org/slf4j:slf4j-api",
"finatra/inject/inject-core/src/main/scala",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/base",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/addressbook",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/crowd_search_accounts",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/real_graph",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/stp",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/top_organic_follows_accounts",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/user_user_graph",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates/gizmoduck",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates/sgs",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/rankers/weighted_candidate_source_ranker",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/dedup",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/tracking_token",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/candidates",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/common",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/params",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/products/common",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/utils",
"util/util-slf4j-api/src/main/scala",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/ContentRecommenderFlow.scala | package com.twitter.follow_recommendations.flows.content_recommender_flow
import com.twitter.conversions.DurationOps._
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.EnrichedCandidateSource
import com.twitter.follow_recommendations.common.base.GatedPredicateBase
import com.twitter.follow_recommendations.common.base.ParamPredicate
import com.twitter.follow_recommendations.common.base.Predicate
import com.twitter.follow_recommendations.common.base.Ranker
import com.twitter.follow_recommendations.common.base.RecommendationFlow
import com.twitter.follow_recommendations.common.base.RecommendationResultsConfig
import com.twitter.follow_recommendations.common.base.Transform
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.predicates.ExcludedUserIdPredicate
import com.twitter.follow_recommendations.common.predicates.InactivePredicate
import com.twitter.follow_recommendations.common.predicates.gizmoduck.GizmoduckPredicate
import com.twitter.follow_recommendations.common.predicates.sgs.InvalidRelationshipPredicate
import com.twitter.follow_recommendations.common.predicates.sgs.InvalidTargetCandidateRelationshipTypesPredicate
import com.twitter.follow_recommendations.common.predicates.sgs.RecentFollowingPredicate
import com.twitter.follow_recommendations.common.rankers.weighted_candidate_source_ranker.WeightedCandidateSourceRanker
import com.twitter.follow_recommendations.common.transforms.dedup.DedupTransform
import com.twitter.follow_recommendations.common.transforms.tracking_token.TrackingTokenTransform
import com.twitter.follow_recommendations.utils.CandidateSourceHoldbackUtil
import com.twitter.follow_recommendations.utils.RecommendationFlowBaseSideEffectsUtil
import com.twitter.product_mixer.core.functional_component.candidate_source.CandidateSource
import com.twitter.product_mixer.core.quality_factor.BoundsWithDefault
import com.twitter.product_mixer.core.quality_factor.LinearLatencyQualityFactor
import com.twitter.product_mixer.core.quality_factor.LinearLatencyQualityFactorConfig
import com.twitter.product_mixer.core.quality_factor.LinearLatencyQualityFactorObserver
import com.twitter.product_mixer.core.quality_factor.QualityFactorObserver
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class ContentRecommenderFlow @Inject() (
contentRecommenderFlowCandidateSourceRegistry: ContentRecommenderFlowCandidateSourceRegistry,
recentFollowingPredicate: RecentFollowingPredicate,
gizmoduckPredicate: GizmoduckPredicate,
inactivePredicate: InactivePredicate,
sgsPredicate: InvalidTargetCandidateRelationshipTypesPredicate,
invalidRelationshipPredicate: InvalidRelationshipPredicate,
trackingTokenTransform: TrackingTokenTransform,
baseStatsReceiver: StatsReceiver)
extends RecommendationFlow[ContentRecommenderRequest, CandidateUser]
with RecommendationFlowBaseSideEffectsUtil[ContentRecommenderRequest, CandidateUser]
with CandidateSourceHoldbackUtil {
override val statsReceiver: StatsReceiver = baseStatsReceiver.scope("content_recommender_flow")
override val qualityFactorObserver: Option[QualityFactorObserver] = {
val config = LinearLatencyQualityFactorConfig(
qualityFactorBounds =
BoundsWithDefault(minInclusive = 0.1, maxInclusive = 1.0, default = 1.0),
initialDelay = 60.seconds,
targetLatency = 100.milliseconds,
targetLatencyPercentile = 95.0,
delta = 0.001
)
val qualityFactor = LinearLatencyQualityFactor(config)
val observer = LinearLatencyQualityFactorObserver(qualityFactor)
statsReceiver.provideGauge("quality_factor")(qualityFactor.currentValue.toFloat)
Some(observer)
}
protected override def targetEligibility: Predicate[ContentRecommenderRequest] =
new ParamPredicate[ContentRecommenderRequest](
ContentRecommenderParams.TargetEligibility
)
protected override def candidateSources(
target: ContentRecommenderRequest
): Seq[CandidateSource[ContentRecommenderRequest, CandidateUser]] = {
import EnrichedCandidateSource._
val identifiers = ContentRecommenderFlowCandidateSourceWeights.getWeights(target.params).keySet
val selected = contentRecommenderFlowCandidateSourceRegistry.select(identifiers)
val budget =
target.params(ContentRecommenderParams.FetchCandidateSourceBudgetInMillisecond).millisecond
filterCandidateSources(target, selected.map(c => c.failOpenWithin(budget, statsReceiver)).toSeq)
}
protected override val preRankerCandidateFilter: Predicate[
(ContentRecommenderRequest, CandidateUser)
] = {
val preRankerFilterStats = statsReceiver.scope("pre_ranker")
val recentFollowingPredicateStats = preRankerFilterStats.scope("recent_following_predicate")
val invalidRelationshipPredicateStats =
preRankerFilterStats.scope("invalid_relationship_predicate")
object recentFollowingGatedPredicate
extends GatedPredicateBase[(ContentRecommenderRequest, CandidateUser)](
recentFollowingPredicate,
recentFollowingPredicateStats
) {
override def gate(item: (ContentRecommenderRequest, CandidateUser)): Boolean =
item._1.params(ContentRecommenderParams.EnableRecentFollowingPredicate)
}
object invalidRelationshipGatedPredicate
extends GatedPredicateBase[(ContentRecommenderRequest, CandidateUser)](
invalidRelationshipPredicate,
invalidRelationshipPredicateStats
) {
override def gate(item: (ContentRecommenderRequest, CandidateUser)): Boolean =
item._1.params(ContentRecommenderParams.EnableInvalidRelationshipPredicate)
}
ExcludedUserIdPredicate
.observe(preRankerFilterStats.scope("exclude_user_id_predicate"))
.andThen(recentFollowingGatedPredicate.observe(recentFollowingPredicateStats))
.andThen(invalidRelationshipGatedPredicate.observe(invalidRelationshipPredicateStats))
}
/**
* rank the candidates
*/
protected override def selectRanker(
target: ContentRecommenderRequest
): Ranker[ContentRecommenderRequest, CandidateUser] = {
val rankersStatsReceiver = statsReceiver.scope("rankers")
WeightedCandidateSourceRanker
.build[ContentRecommenderRequest](
ContentRecommenderFlowCandidateSourceWeights.getWeights(target.params),
randomSeed = target.getRandomizationSeed
).observe(rankersStatsReceiver.scope("weighted_candidate_source_ranker"))
}
/**
* transform the candidates after ranking
*/
protected override def postRankerTransform: Transform[
ContentRecommenderRequest,
CandidateUser
] = {
new DedupTransform[ContentRecommenderRequest, CandidateUser]
.observe(statsReceiver.scope("dedupping"))
}
protected override def validateCandidates: Predicate[
(ContentRecommenderRequest, CandidateUser)
] = {
val stats = statsReceiver.scope("validate_candidates")
val gizmoduckPredicateStats = stats.scope("gizmoduck_predicate")
val inactivePredicateStats = stats.scope("inactive_predicate")
val sgsPredicateStats = stats.scope("sgs_predicate")
val includeGizmoduckPredicate =
new ParamPredicate[ContentRecommenderRequest](
ContentRecommenderParams.EnableGizmoduckPredicate)
.map[(ContentRecommenderRequest, CandidateUser)] {
case (request: ContentRecommenderRequest, _) =>
request
}
val includeInactivePredicate =
new ParamPredicate[ContentRecommenderRequest](
ContentRecommenderParams.EnableInactivePredicate)
.map[(ContentRecommenderRequest, CandidateUser)] {
case (request: ContentRecommenderRequest, _) =>
request
}
val includeInvalidTargetCandidateRelationshipTypesPredicate =
new ParamPredicate[ContentRecommenderRequest](
ContentRecommenderParams.EnableInvalidTargetCandidateRelationshipPredicate)
.map[(ContentRecommenderRequest, CandidateUser)] {
case (request: ContentRecommenderRequest, _) =>
request
}
Predicate
.andConcurrently[(ContentRecommenderRequest, CandidateUser)](
Seq(
gizmoduckPredicate.observe(gizmoduckPredicateStats).gate(includeGizmoduckPredicate),
inactivePredicate.observe(inactivePredicateStats).gate(includeInactivePredicate),
sgsPredicate
.observe(sgsPredicateStats).gate(
includeInvalidTargetCandidateRelationshipTypesPredicate),
)
)
}
/**
* transform the candidates into results and return
*/
protected override def transformResults: Transform[ContentRecommenderRequest, CandidateUser] = {
trackingTokenTransform
}
/**
* configuration for recommendation results
*/
protected override def resultsConfig(
target: ContentRecommenderRequest
): RecommendationResultsConfig = {
RecommendationResultsConfig(
target.maxResults.getOrElse(target.params(ContentRecommenderParams.ResultSizeParam)),
target.params(ContentRecommenderParams.BatchSizeParam)
)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/ContentRecommenderFlowCandidateSourceRegistry.scala | package com.twitter.follow_recommendations.flows.content_recommender_flow
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.CandidateSourceRegistry
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ForwardEmailBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ForwardPhoneBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ReverseEmailBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ReversePhoneBookSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopCountryBackFillSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopCountrySource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopGeohashSource
import com.twitter.follow_recommendations.common.candidate_sources.crowd_search_accounts.CrowdSearchAccountsSource
import com.twitter.follow_recommendations.common.candidate_sources.ppmi_locale_follow.PPMILocaleFollowSource
import com.twitter.follow_recommendations.common.candidate_sources.top_organic_follows_accounts.TopOrganicFollowsAccountsSource
import com.twitter.follow_recommendations.common.candidate_sources.real_graph.RealGraphOonV2Source
import com.twitter.follow_recommendations.common.candidate_sources.recent_engagement.RepeatedProfileVisitsSource
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentEngagementSimilarUsersSource
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentFollowingSimilarUsersSource
import com.twitter.follow_recommendations.common.candidate_sources.socialgraph.RecentFollowingRecentFollowingExpansionSource
import com.twitter.follow_recommendations.common.candidate_sources.stp.OfflineStrongTiePredictionSource
import com.twitter.follow_recommendations.common.candidate_sources.triangular_loops.TriangularLoopsSource
import com.twitter.follow_recommendations.common.candidate_sources.user_user_graph.UserUserGraphCandidateSource
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.product_mixer.core.functional_component.candidate_source.CandidateSource
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class ContentRecommenderFlowCandidateSourceRegistry @Inject() (
// social based
forwardPhoneBookSource: ForwardPhoneBookSource,
forwardEmailBookSource: ForwardEmailBookSource,
reversePhoneBookSource: ReversePhoneBookSource,
reverseEmailBookSource: ReverseEmailBookSource,
offlineStrongTiePredictionSource: OfflineStrongTiePredictionSource,
triangularLoopsSource: TriangularLoopsSource,
userUserGraphCandidateSource: UserUserGraphCandidateSource,
realGraphOonSource: RealGraphOonV2Source,
recentFollowingRecentFollowingExpansionSource: RecentFollowingRecentFollowingExpansionSource,
// activity based
recentFollowingSimilarUsersSource: RecentFollowingSimilarUsersSource,
recentEngagementSimilarUsersSource: RecentEngagementSimilarUsersSource,
repeatedProfileVisitsSource: RepeatedProfileVisitsSource,
// geo based
popCountrySource: PopCountrySource,
popGeohashSource: PopGeohashSource,
popCountryBackFillSource: PopCountryBackFillSource,
crowdSearchAccountsSource: CrowdSearchAccountsSource,
topOrganicFollowsAccountsSource: TopOrganicFollowsAccountsSource,
ppmiLocaleFollowSource: PPMILocaleFollowSource,
baseStatsReceiver: StatsReceiver)
extends CandidateSourceRegistry[ContentRecommenderRequest, CandidateUser] {
override val statsReceiver = baseStatsReceiver
.scope("content_recommender_flow", "candidate_sources")
override val sources: Set[CandidateSource[ContentRecommenderRequest, CandidateUser]] = Seq(
forwardPhoneBookSource,
forwardEmailBookSource,
reversePhoneBookSource,
reverseEmailBookSource,
offlineStrongTiePredictionSource,
triangularLoopsSource,
userUserGraphCandidateSource,
realGraphOonSource,
recentFollowingRecentFollowingExpansionSource,
recentFollowingSimilarUsersSource,
recentEngagementSimilarUsersSource,
repeatedProfileVisitsSource,
popCountrySource,
popGeohashSource,
popCountryBackFillSource,
crowdSearchAccountsSource,
topOrganicFollowsAccountsSource,
ppmiLocaleFollowSource,
).toSet
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/ContentRecommenderFlowCandidateSourceWeights.scala | package com.twitter.follow_recommendations.flows.content_recommender_flow
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ForwardEmailBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ForwardPhoneBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ReverseEmailBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ReversePhoneBookSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopCountryBackFillSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopCountrySource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopGeohashSource
import com.twitter.follow_recommendations.common.candidate_sources.real_graph.RealGraphOonV2Source
import com.twitter.follow_recommendations.common.candidate_sources.recent_engagement.RepeatedProfileVisitsSource
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentEngagementSimilarUsersSource
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentFollowingSimilarUsersSource
import com.twitter.follow_recommendations.common.candidate_sources.stp.OfflineStrongTiePredictionSource
import com.twitter.follow_recommendations.common.candidate_sources.triangular_loops.TriangularLoopsSource
import com.twitter.follow_recommendations.common.candidate_sources.user_user_graph.UserUserGraphCandidateSource
import com.twitter.product_mixer.core.model.common.identifier.CandidateSourceIdentifier
import com.twitter.follow_recommendations.common.candidate_sources.crowd_search_accounts.CrowdSearchAccountsSource
import com.twitter.follow_recommendations.common.candidate_sources.ppmi_locale_follow.PPMILocaleFollowSource
import com.twitter.follow_recommendations.common.candidate_sources.socialgraph.RecentFollowingRecentFollowingExpansionSource
import com.twitter.follow_recommendations.common.candidate_sources.top_organic_follows_accounts.TopOrganicFollowsAccountsSource
import com.twitter.timelines.configapi.Params
object ContentRecommenderFlowCandidateSourceWeights {
def getWeights(
params: Params
): Map[CandidateSourceIdentifier, Double] = {
Map[CandidateSourceIdentifier, Double](
// Social based
UserUserGraphCandidateSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.UserUserGraphSourceWeight),
ForwardPhoneBookSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.ForwardPhoneBookSourceWeight),
ReversePhoneBookSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.ReversePhoneBookSourceWeight),
ForwardEmailBookSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.ForwardEmailBookSourceWeight),
ReverseEmailBookSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.ReverseEmailBookSourceWeight),
TriangularLoopsSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.TriangularLoopsSourceWeight),
OfflineStrongTiePredictionSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.OfflineStrongTiePredictionSourceWeight),
RecentFollowingRecentFollowingExpansionSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.NewFollowingNewFollowingExpansionSourceWeight),
RecentFollowingSimilarUsersSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.NewFollowingSimilarUserSourceWeight),
// Activity based
RealGraphOonV2Source.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.RealGraphOonSourceWeight),
RecentEngagementSimilarUsersSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.RecentEngagementSimilarUserSourceWeight),
RepeatedProfileVisitsSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.RepeatedProfileVisitsSourceWeight),
// Geo based
PopCountrySource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.PopCountrySourceWeight),
PopGeohashSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.PopGeohashSourceWeight),
PopCountryBackFillSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.PopCountryBackfillSourceWeight),
PPMILocaleFollowSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.PPMILocaleFollowSourceWeight),
CrowdSearchAccountsSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.CrowdSearchAccountSourceWeight),
TopOrganicFollowsAccountsSource.Identifier -> params(
ContentRecommenderFlowCandidateSourceWeightsParams.TopOrganicFollowsAccountsSourceWeight),
)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/ContentRecommenderFlowCandidateSourceWeightsParams.scala | package com.twitter.follow_recommendations.flows.content_recommender_flow
import com.twitter.timelines.configapi.FSBoundedParam
object ContentRecommenderFlowCandidateSourceWeightsParams {
// Social based
case object ForwardPhoneBookSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.ForwardPhoneBookSourceWeight,
1d,
0d,
1000d)
case object ForwardEmailBookSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.ForwardEmailBookSourceWeight,
1d,
0d,
1000d)
case object ReversePhoneBookSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.ReversePhoneBookSourceWeight,
1d,
0d,
1000d)
case object ReverseEmailBookSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.ReverseEmailBookSourceWeight,
1d,
0d,
1000d)
case object OfflineStrongTiePredictionSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.OfflineStrongTiePredictionSourceWeight,
1d,
0d,
1000d)
case object TriangularLoopsSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.TriangularLoopsSourceWeight,
1d,
0d,
1000d)
case object UserUserGraphSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.UserUserGraphSourceWeight,
1d,
0d,
1000d)
case object NewFollowingNewFollowingExpansionSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.NewFollowingNewFollowingExpansionSourceWeight,
1d,
0d,
1000d)
// Activity based
case object NewFollowingSimilarUserSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.NewFollowingSimilarUserSourceWeight,
1d,
0d,
1000d)
case object RecentEngagementSimilarUserSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.RecentEngagementSimilarUserSourceWeight,
1d,
0d,
1000d)
case object RepeatedProfileVisitsSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.RepeatedProfileVisitsSourceWeight,
1d,
0d,
1000d)
case object RealGraphOonSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.RealGraphOonSourceWeight,
1d,
0d,
1000d)
// Geo based
case object PopCountrySourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.PopCountrySourceWeight,
1d,
0d,
1000d)
case object PopGeohashSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.PopGeohashSourceWeight,
1d,
0d,
1000d)
case object PopCountryBackfillSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.PopCountryBackfillSourceWeight,
1d,
0d,
1000d)
case object PPMILocaleFollowSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.PPMILocaleFollowSourceWeight,
1d,
0d,
1000d)
case object TopOrganicFollowsAccountsSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.TopOrganicFollowsAccountsSourceWeight,
1d,
0d,
1000d)
case object CrowdSearchAccountSourceWeight
extends FSBoundedParam[Double](
ContentRecommenderFlowFeatureSwitchKeys.CrowdSearchAccountSourceWeight,
1d,
0d,
1000d)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/ContentRecommenderFlowFSConfig.scala | package com.twitter.follow_recommendations.flows.content_recommender_flow
import com.twitter.follow_recommendations.configapi.common.FeatureSwitchConfig
import com.twitter.timelines.configapi.FSBoundedParam
import com.twitter.timelines.configapi.FSName
import com.twitter.timelines.configapi.Param
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class ContentRecommenderFlowFSConfig @Inject() () extends FeatureSwitchConfig {
override val booleanFSParams: Seq[Param[Boolean] with FSName] =
Seq(
ContentRecommenderParams.IncludeActivityBasedCandidateSource,
ContentRecommenderParams.IncludeSocialBasedCandidateSource,
ContentRecommenderParams.IncludeGeoBasedCandidateSource,
ContentRecommenderParams.IncludeHomeTimelineTweetRecsCandidateSource,
ContentRecommenderParams.IncludeSocialProofEnforcedCandidateSource,
ContentRecommenderParams.EnableRecentFollowingPredicate,
ContentRecommenderParams.EnableGizmoduckPredicate,
ContentRecommenderParams.EnableInactivePredicate,
ContentRecommenderParams.EnableInvalidTargetCandidateRelationshipPredicate,
ContentRecommenderParams.IncludeNewFollowingNewFollowingExpansionCandidateSource,
ContentRecommenderParams.IncludeMoreGeoBasedCandidateSource,
ContentRecommenderParams.TargetEligibility,
ContentRecommenderParams.GetFollowersFromSgs,
ContentRecommenderParams.EnableInvalidRelationshipPredicate,
)
override val intFSParams: Seq[FSBoundedParam[Int]] =
Seq(
ContentRecommenderParams.ResultSizeParam,
ContentRecommenderParams.BatchSizeParam,
ContentRecommenderParams.FetchCandidateSourceBudgetInMillisecond,
ContentRecommenderParams.RecentFollowingPredicateBudgetInMillisecond,
)
override val doubleFSParams: Seq[FSBoundedParam[Double]] =
Seq(
ContentRecommenderFlowCandidateSourceWeightsParams.ForwardPhoneBookSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.ForwardEmailBookSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.ReversePhoneBookSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.ReverseEmailBookSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.OfflineStrongTiePredictionSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.TriangularLoopsSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.UserUserGraphSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.NewFollowingNewFollowingExpansionSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.NewFollowingSimilarUserSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.RecentEngagementSimilarUserSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.RepeatedProfileVisitsSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.RealGraphOonSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.PopCountrySourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.PopGeohashSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.PopCountryBackfillSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.PPMILocaleFollowSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.TopOrganicFollowsAccountsSourceWeight,
ContentRecommenderFlowCandidateSourceWeightsParams.CrowdSearchAccountSourceWeight,
)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/ContentRecommenderFlowFeatureSwitchKeys.scala | package com.twitter.follow_recommendations.flows.content_recommender_flow
object ContentRecommenderFlowFeatureSwitchKeys {
val TargetUserEligible = "content_recommender_flow_target_eligible"
val ResultSize = "content_recommender_flow_result_size"
val BatchSize = "content_recommender_flow_batch_size"
val RecentFollowingPredicateBudgetInMillisecond =
"content_recommender_flow_recent_following_predicate_budget_in_ms"
val CandidateGenerationBudgetInMillisecond =
"content_recommender_flow_candidate_generation_budget_in_ms"
val EnableRecentFollowingPredicate = "content_recommender_flow_enable_recent_following_predicate"
val EnableGizmoduckPredicate = "content_recommender_flow_enable_gizmoduck_predicate"
val EnableInactivePredicate = "content_recommender_flow_enable_inactive_predicate"
val EnableInvalidTargetCandidateRelationshipPredicate =
"content_recommender_flow_enable_invalid_target_candidate_relationship_predicate"
val IncludeActivityBasedCandidateSource =
"content_recommender_flow_include_activity_based_candidate_source"
val IncludeSocialBasedCandidateSource =
"content_recommender_flow_include_social_based_candidate_source"
val IncludeGeoBasedCandidateSource =
"content_recommender_flow_include_geo_based_candidate_source"
val IncludeHomeTimelineTweetRecsCandidateSource =
"content_recommender_flow_include_home_timeline_tweet_recs_candidate_source"
val IncludeSocialProofEnforcedCandidateSource =
"content_recommender_flow_include_social_proof_enforced_candidate_source"
val IncludeNewFollowingNewFollowingExpansionCandidateSource =
"content_recommender_flow_include_new_following_new_following_expansion_candidate_source"
val IncludeMoreGeoBasedCandidateSource =
"content_recommender_flow_include_more_geo_based_candidate_source"
val GetFollowersFromSgs = "content_recommender_flow_get_followers_from_sgs"
val EnableInvalidRelationshipPredicate =
"content_recommender_flow_enable_invalid_relationship_predicate"
// Candidate source weight param keys
// Social based
val ForwardPhoneBookSourceWeight =
"content_recommender_flow_candidate_source_weight_forward_phone_book"
val ForwardEmailBookSourceWeight =
"content_recommender_flow_candidate_source_weight_forward_email_book"
val ReversePhoneBookSourceWeight =
"content_recommender_flow_candidate_source_weight_reverse_phone_book"
val ReverseEmailBookSourceWeight =
"content_recommender_flow_candidate_source_weight_reverse_email_book"
val OfflineStrongTiePredictionSourceWeight =
"content_recommender_flow_candidate_source_weight_offline_stp"
val TriangularLoopsSourceWeight =
"content_recommender_flow_candidate_source_weight_triangular_loops"
val UserUserGraphSourceWeight = "content_recommender_flow_candidate_source_weight_user_user_graph"
val NewFollowingNewFollowingExpansionSourceWeight =
"content_recommender_flow_candidate_source_weight_new_following_new_following_expansion"
// Activity based
val NewFollowingSimilarUserSourceWeight =
"content_recommender_flow_candidate_source_weight_new_following_similar_user"
val RecentEngagementSimilarUserSourceWeight =
"content_recommender_flow_candidate_source_weight_recent_engagement_similar_user"
val RepeatedProfileVisitsSourceWeight =
"content_recommender_flow_candidate_source_weight_repeated_profile_visits"
val RealGraphOonSourceWeight = "content_recommender_flow_candidate_source_weight_real_graph_oon"
// Geo based
val PopCountrySourceWeight = "content_recommender_flow_candidate_source_weight_pop_country"
val PopGeohashSourceWeight = "content_recommender_flow_candidate_source_weight_pop_geohash"
val PopCountryBackfillSourceWeight =
"content_recommender_flow_candidate_source_weight_pop_country_backfill"
val PPMILocaleFollowSourceWeight =
"content_recommender_flow_candidate_source_weight_ppmi_locale_follow"
val TopOrganicFollowsAccountsSourceWeight =
"content_recommender_flow_candidate_source_weight_top_organic_follow_account"
val CrowdSearchAccountSourceWeight =
"content_recommender_flow_candidate_source_weight_crowd_search_account"
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/ContentRecommenderParams.scala | package com.twitter.follow_recommendations.flows.content_recommender_flow
import com.twitter.timelines.configapi.FSBoundedParam
import com.twitter.timelines.configapi.FSParam
import com.twitter.timelines.configapi.Param
abstract class ContentRecommenderParams[A](default: A) extends Param[A](default) {
override val statName: String = "content_recommender/" + this.getClass.getSimpleName
}
object ContentRecommenderParams {
case object TargetEligibility
extends FSParam[Boolean](ContentRecommenderFlowFeatureSwitchKeys.TargetUserEligible, true)
case object ResultSizeParam
extends FSBoundedParam[Int](ContentRecommenderFlowFeatureSwitchKeys.ResultSize, 15, 1, 500)
case object BatchSizeParam
extends FSBoundedParam[Int](ContentRecommenderFlowFeatureSwitchKeys.BatchSize, 15, 1, 500)
case object RecentFollowingPredicateBudgetInMillisecond
extends FSBoundedParam[Int](
ContentRecommenderFlowFeatureSwitchKeys.RecentFollowingPredicateBudgetInMillisecond,
8,
1,
50)
case object FetchCandidateSourceBudgetInMillisecond
extends FSBoundedParam[Int](
ContentRecommenderFlowFeatureSwitchKeys.CandidateGenerationBudgetInMillisecond,
60,
1,
80)
case object EnableRecentFollowingPredicate
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.EnableRecentFollowingPredicate,
true)
case object EnableGizmoduckPredicate
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.EnableGizmoduckPredicate,
false)
case object EnableInactivePredicate
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.EnableInactivePredicate,
false)
case object EnableInvalidTargetCandidateRelationshipPredicate
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.EnableInvalidTargetCandidateRelationshipPredicate,
false)
case object IncludeActivityBasedCandidateSource
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.IncludeActivityBasedCandidateSource,
true)
case object IncludeSocialBasedCandidateSource
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.IncludeSocialBasedCandidateSource,
true)
case object IncludeGeoBasedCandidateSource
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.IncludeGeoBasedCandidateSource,
true)
case object IncludeHomeTimelineTweetRecsCandidateSource
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.IncludeHomeTimelineTweetRecsCandidateSource,
false)
case object IncludeSocialProofEnforcedCandidateSource
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.IncludeSocialProofEnforcedCandidateSource,
false)
case object IncludeNewFollowingNewFollowingExpansionCandidateSource
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.IncludeNewFollowingNewFollowingExpansionCandidateSource,
false)
case object IncludeMoreGeoBasedCandidateSource
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.IncludeMoreGeoBasedCandidateSource,
false)
case object GetFollowersFromSgs
extends FSParam[Boolean](ContentRecommenderFlowFeatureSwitchKeys.GetFollowersFromSgs, false)
case object EnableInvalidRelationshipPredicate
extends FSParam[Boolean](
ContentRecommenderFlowFeatureSwitchKeys.EnableInvalidRelationshipPredicate,
false)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/ContentRecommenderRequest.scala | package com.twitter.follow_recommendations.flows.content_recommender_flow
import com.twitter.core_workflows.user_model.thriftscala.UserState
import com.twitter.follow_recommendations.common.models.DebugOptions
import com.twitter.follow_recommendations.common.models.DisplayLocation
import com.twitter.follow_recommendations.common.models.GeohashAndCountryCode
import com.twitter.follow_recommendations.common.models.HasDebugOptions
import com.twitter.follow_recommendations.common.models.HasDisplayLocation
import com.twitter.follow_recommendations.common.models.HasExcludedUserIds
import com.twitter.follow_recommendations.common.models.HasGeohashAndCountryCode
import com.twitter.follow_recommendations.common.models.HasInvalidRelationshipUserIds
import com.twitter.follow_recommendations.common.models.HasRecentFollowedByUserIds
import com.twitter.follow_recommendations.common.models.HasRecentFollowedUserIds
import com.twitter.follow_recommendations.common.models.HasUserState
import com.twitter.product_mixer.core.model.marshalling.request.ClientContext
import com.twitter.product_mixer.core.model.marshalling.request.HasClientContext
import com.twitter.timelines.configapi.HasParams
import com.twitter.timelines.configapi.Params
case class ContentRecommenderRequest(
override val params: Params,
override val clientContext: ClientContext,
inputExcludeUserIds: Seq[Long],
override val recentFollowedUserIds: Option[Seq[Long]],
override val recentFollowedByUserIds: Option[Seq[Long]],
override val invalidRelationshipUserIds: Option[Set[Long]],
override val displayLocation: DisplayLocation,
maxResults: Option[Int] = None,
override val debugOptions: Option[DebugOptions] = None,
override val geohashAndCountryCode: Option[GeohashAndCountryCode] = None,
override val userState: Option[UserState] = None)
extends HasParams
with HasClientContext
with HasDisplayLocation
with HasDebugOptions
with HasRecentFollowedUserIds
with HasRecentFollowedByUserIds
with HasInvalidRelationshipUserIds
with HasExcludedUserIds
with HasUserState
with HasGeohashAndCountryCode {
override val excludedUserIds: Seq[Long] = {
inputExcludeUserIds ++ clientContext.userId.toSeq
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/content_recommender_flow/ContentRecommenderRequestBuilder.scala | package com.twitter.follow_recommendations.flows.content_recommender_flow
import com.twitter.conversions.DurationOps._
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.clients.geoduck.UserLocationFetcher
import com.twitter.follow_recommendations.common.clients.socialgraph.SocialGraphClient
import com.twitter.follow_recommendations.common.clients.user_state.UserStateClient
import com.twitter.follow_recommendations.common.utils.RescueWithStatsUtils.rescueOptionalWithStats
import com.twitter.follow_recommendations.common.utils.RescueWithStatsUtils.rescueWithStats
import com.twitter.follow_recommendations.common.utils.RescueWithStatsUtils.rescueWithStatsWithin
import com.twitter.follow_recommendations.products.common.ProductRequest
import com.twitter.stitch.Stitch
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class ContentRecommenderRequestBuilder @Inject() (
socialGraph: SocialGraphClient,
userLocationFetcher: UserLocationFetcher,
userStateClient: UserStateClient,
statsReceiver: StatsReceiver) {
val stats: StatsReceiver = statsReceiver.scope("content_recommender_request_builder")
val invalidRelationshipUsersStats: StatsReceiver = stats.scope("invalidRelationshipUserIds")
private val invalidRelationshipUsersMaxSizeCounter =
invalidRelationshipUsersStats.counter("maxSize")
private val invalidRelationshipUsersNotMaxSizeCounter =
invalidRelationshipUsersStats.counter("notMaxSize")
def build(req: ProductRequest): Stitch[ContentRecommenderRequest] = {
val userStateStitch = Stitch
.collect(req.recommendationRequest.clientContext.userId.map(userId =>
userStateClient.getUserState(userId))).map(_.flatten)
val recentFollowedUserIdsStitch =
Stitch
.collect(req.recommendationRequest.clientContext.userId.map { userId =>
rescueWithStatsWithin(
socialGraph.getRecentFollowedUserIds(userId),
stats,
"recentFollowedUserIds",
req
.params(
ContentRecommenderParams.RecentFollowingPredicateBudgetInMillisecond).millisecond
)
})
val recentFollowedByUserIdsStitch =
if (req.params(ContentRecommenderParams.GetFollowersFromSgs)) {
Stitch
.collect(
req.recommendationRequest.clientContext.userId.map(userId =>
rescueWithStatsWithin(
socialGraph.getRecentFollowedByUserIdsFromCachedColumn(userId),
stats,
"recentFollowedByUserIds",
req
.params(ContentRecommenderParams.RecentFollowingPredicateBudgetInMillisecond)
.millisecond
)))
} else Stitch.None
val invalidRelationshipUserIdsStitch: Stitch[Option[Seq[Long]]] =
if (req.params(ContentRecommenderParams.EnableInvalidRelationshipPredicate)) {
Stitch
.collect(
req.recommendationRequest.clientContext.userId.map { userId =>
rescueWithStats(
socialGraph
.getInvalidRelationshipUserIdsFromCachedColumn(userId)
.onSuccess(ids =>
if (ids.size >= SocialGraphClient.MaxNumInvalidRelationship) {
invalidRelationshipUsersMaxSizeCounter.incr()
} else {
invalidRelationshipUsersNotMaxSizeCounter.incr()
}),
stats,
"invalidRelationshipUserIds"
)
}
)
} else {
Stitch.None
}
val locationStitch =
rescueOptionalWithStats(
userLocationFetcher.getGeohashAndCountryCode(
req.recommendationRequest.clientContext.userId,
req.recommendationRequest.clientContext.ipAddress
),
stats,
"userLocation"
)
Stitch
.join(
recentFollowedUserIdsStitch,
recentFollowedByUserIdsStitch,
invalidRelationshipUserIdsStitch,
locationStitch,
userStateStitch)
.map {
case (
recentFollowedUserIds,
recentFollowedByUserIds,
invalidRelationshipUserIds,
location,
userState) =>
ContentRecommenderRequest(
req.params,
req.recommendationRequest.clientContext,
req.recommendationRequest.excludedIds.getOrElse(Nil),
recentFollowedUserIds,
recentFollowedByUserIds,
invalidRelationshipUserIds.map(_.toSet),
req.recommendationRequest.displayLocation,
req.recommendationRequest.maxResults,
req.recommendationRequest.debugParams.flatMap(_.debugOptions),
location,
userState
)
}
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"3rdparty/jvm/com/google/inject/extensions:guice-assistedinject",
"3rdparty/jvm/net/codingwell:scala-guice",
"3rdparty/jvm/org/slf4j:slf4j-api",
"finatra/inject/inject-core/src/main/scala",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/base",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/addressbook",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/crowd_search_accounts",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/geo",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/real_graph",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/recent_engagement",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/salsa",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/sims",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/sims_expansion",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/stp",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/top_organic_follows_accounts",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/triangular_loops",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/two_hop_random_walk",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/candidate_sources/user_user_graph",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/deepbirdv2",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/geoduck",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/impression_store",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/interests_service",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/clients/user_state",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/feature_hydration/common",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/feature_hydration/sources",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates/dismiss",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates/gizmoduck",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates/health",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates/sgs",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/predicates/user_activity",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/rankers/fatigue_ranker",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/rankers/first_n_ranker",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/rankers/interleave_ranker",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/rankers/ml_ranker/ranking",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/rankers/ml_ranker/scoring",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/rankers/weighted_candidate_source_ranker",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/dedup",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/modify_social_proof",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/ranker_id",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/tracking_token",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/transforms/weighted_sampling",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/candidates",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/common",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/params",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/logging",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/products/common",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/utils",
"util/util-slf4j-api/src/main/scala",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlCandidateSourceRegistry.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.CandidateSourceRegistry
import com.twitter.follow_recommendations.common.base.EnrichedCandidateSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ForwardEmailBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ForwardPhoneBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ReverseEmailBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ReversePhoneBookSource
import com.twitter.follow_recommendations.common.candidate_sources.crowd_search_accounts.CrowdSearchAccountsSource
import com.twitter.follow_recommendations.common.candidate_sources.top_organic_follows_accounts.TopOrganicFollowsAccountsSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopCountrySource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopCountryBackFillSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopGeohashQualityFollowSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopGeohashSource
import com.twitter.follow_recommendations.common.candidate_sources.ppmi_locale_follow.PPMILocaleFollowSource
import com.twitter.follow_recommendations.common.candidate_sources.real_graph.RealGraphOonV2Source
import com.twitter.follow_recommendations.common.candidate_sources.recent_engagement.RecentEngagementNonDirectFollowSource
import com.twitter.follow_recommendations.common.candidate_sources.recent_engagement.RepeatedProfileVisitsSource
import com.twitter.follow_recommendations.common.candidate_sources.salsa.RecentEngagementDirectFollowSalsaExpansionSource
import com.twitter.follow_recommendations.common.candidate_sources.sims.LinearRegressionFollow2vecNearestNeighborsStore
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentEngagementSimilarUsersSource
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentFollowingSimilarUsersSource
import com.twitter.follow_recommendations.common.candidate_sources.stp.OnlineSTPSourceScorer
import com.twitter.follow_recommendations.common.candidate_sources.stp.OfflineStrongTiePredictionSource
import com.twitter.follow_recommendations.common.candidate_sources.triangular_loops.TriangularLoopsSource
import com.twitter.follow_recommendations.common.candidate_sources.user_user_graph.UserUserGraphCandidateSource
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.product_mixer.core.functional_component.candidate_source.CandidateSource
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class PostNuxMlCandidateSourceRegistry @Inject() (
crowdSearchAccountsCandidateSource: CrowdSearchAccountsSource,
topOrganicFollowsAccountsSource: TopOrganicFollowsAccountsSource,
linearRegressionfollow2vecNearestNeighborsStore: LinearRegressionFollow2vecNearestNeighborsStore,
forwardEmailBookSource: ForwardEmailBookSource,
forwardPhoneBookSource: ForwardPhoneBookSource,
offlineStrongTiePredictionSource: OfflineStrongTiePredictionSource,
onlineSTPSource: OnlineSTPSourceScorer,
popCountrySource: PopCountrySource,
popCountryBackFillSource: PopCountryBackFillSource,
popGeohashSource: PopGeohashSource,
recentEngagementDirectFollowSimilarUsersSource: RecentEngagementSimilarUsersSource,
recentEngagementNonDirectFollowSource: RecentEngagementNonDirectFollowSource,
recentEngagementDirectFollowSalsaExpansionSource: RecentEngagementDirectFollowSalsaExpansionSource,
recentFollowingSimilarUsersSource: RecentFollowingSimilarUsersSource,
realGraphOonV2Source: RealGraphOonV2Source,
repeatedProfileVisitSource: RepeatedProfileVisitsSource,
reverseEmailBookSource: ReverseEmailBookSource,
reversePhoneBookSource: ReversePhoneBookSource,
triangularLoopsSource: TriangularLoopsSource,
userUserGraphCandidateSource: UserUserGraphCandidateSource,
ppmiLocaleFollowSource: PPMILocaleFollowSource,
popGeohashQualityFollowSource: PopGeohashQualityFollowSource,
baseStatsReceiver: StatsReceiver,
) extends CandidateSourceRegistry[PostNuxMlRequest, CandidateUser] {
import EnrichedCandidateSource._
override val statsReceiver = baseStatsReceiver
.scope("post_nux_ml_flow", "candidate_sources")
// sources primarily based on social graph signals
private[this] val socialSources = Seq(
linearRegressionfollow2vecNearestNeighborsStore.mapKeys[PostNuxMlRequest](
_.getOptionalUserId.toSeq),
forwardEmailBookSource,
forwardPhoneBookSource,
offlineStrongTiePredictionSource,
onlineSTPSource,
reverseEmailBookSource,
reversePhoneBookSource,
triangularLoopsSource,
)
// sources primarily based on geo signals
private[this] val geoSources = Seq(
popCountrySource,
popCountryBackFillSource,
popGeohashSource,
popGeohashQualityFollowSource,
topOrganicFollowsAccountsSource,
crowdSearchAccountsCandidateSource,
ppmiLocaleFollowSource,
)
// sources primarily based on recent activity signals
private[this] val activitySources = Seq(
repeatedProfileVisitSource,
recentEngagementDirectFollowSalsaExpansionSource.mapKeys[PostNuxMlRequest](
_.getOptionalUserId.toSeq),
recentEngagementDirectFollowSimilarUsersSource,
recentEngagementNonDirectFollowSource.mapKeys[PostNuxMlRequest](_.getOptionalUserId.toSeq),
recentFollowingSimilarUsersSource,
realGraphOonV2Source,
userUserGraphCandidateSource,
)
override val sources: Set[CandidateSource[PostNuxMlRequest, CandidateUser]] = (
geoSources ++ socialSources ++ activitySources
).toSet
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlCandidateSourceWeightParams.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.twitter.timelines.configapi.FSBoundedParam
import com.twitter.timelines.configapi.Param
abstract class PostNuxMlCandidateSourceWeightParams[A](default: A) extends Param[A](default) {
override val statName: String = "post_nux_ml/" + this.getClass.getSimpleName
}
object PostNuxMlCandidateSourceWeightParams {
case object CandidateWeightCrowdSearch
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightCrowdSearch,
1.0,
0.0,
1000.0
)
case object CandidateWeightTopOrganicFollow
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightTopOrganicFollow,
1.0,
0.0,
1000.0
)
case object CandidateWeightPPMILocaleFollow
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightPPMILocaleFollow,
1.0,
0.0,
1000.0
)
case object CandidateWeightForwardEmailBook
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightForwardEmailBook,
1.0,
0.0,
1000.0
)
case object CandidateWeightForwardPhoneBook
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightForwardPhoneBook,
1.0,
0.0,
1000.0
)
case object CandidateWeightOfflineStrongTiePrediction
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightOfflineStrongTiePrediction,
1.0,
0.0,
1000.0
)
case object CandidateWeightOnlineStp
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightOnlineStp,
1.0,
0.0,
1000.0
)
case object CandidateWeightPopCountry
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightPopCountry,
1.0,
0.0,
1000.0
)
case object CandidateWeightPopGeohash
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightPopGeohash,
1.0,
0.0,
1000.0
)
case object CandidateWeightPopGeohashQualityFollow
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightPopGeohashQualityFollow,
1.0,
0.0,
1000.0
)
case object CandidateWeightPopGeoBackfill
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightPopGeoBackfill,
1,
0.0,
1000.0
)
case object CandidateWeightRecentFollowingSimilarUsers
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightRecentFollowingSimilarUsers,
1.0,
0.0,
1000.0
)
case object CandidateWeightRecentEngagementDirectFollowSalsaExpansion
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightRecentEngagementDirectFollowSalsaExpansion,
1.0,
0.0,
1000.0
)
case object CandidateWeightRecentEngagementNonDirectFollow
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightRecentEngagementNonDirectFollow,
1.0,
0.0,
1000.0
)
case object CandidateWeightRecentEngagementSimilarUsers
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightRecentEngagementSimilarUsers,
1.0,
0.0,
1000.0
)
case object CandidateWeightRepeatedProfileVisits
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightRepeatedProfileVisits,
1.0,
0.0,
1000.0
)
case object CandidateWeightFollow2vecNearestNeighbors
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightFollow2vecNearestNeighbors,
1.0,
0.0,
1000.0
)
case object CandidateWeightReverseEmailBook
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightReverseEmailBook,
1.0,
0.0,
1000.0
)
case object CandidateWeightReversePhoneBook
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightReversePhoneBook,
1.0,
0.0,
1000.0
)
case object CandidateWeightTriangularLoops
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightTriangularLoops,
1.0,
0.0,
1000.0
)
case object CandidateWeightTwoHopRandomWalk
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightTwoHopRandomWalk,
1.0,
0.0,
1000.0
)
case object CandidateWeightUserUserGraph
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightUserUserGraph,
1.0,
0.0,
1000.0
)
case object CandidateWeightRealGraphOonV2
extends FSBoundedParam[Double](
PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.CandidateWeightRealGraphOonV2,
1.0,
0.0,
2000.0
)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlCombinedRankerBuilder.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.google.inject.Inject
import com.google.inject.Singleton
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.IdentityRanker
import com.twitter.follow_recommendations.common.base.IdentityTransform
import com.twitter.follow_recommendations.common.base.Ranker
import com.twitter.follow_recommendations.common.base.Transform
import com.twitter.follow_recommendations.common.feature_hydration.common.HasPreFetchedFeature
import com.twitter.follow_recommendations.common.models._
import com.twitter.follow_recommendations.common.rankers.common.RankerId
import com.twitter.follow_recommendations.common.rankers.fatigue_ranker.ImpressionBasedFatigueRanker
import com.twitter.follow_recommendations.common.rankers.first_n_ranker.FirstNRanker
import com.twitter.follow_recommendations.common.rankers.first_n_ranker.FirstNRankerParams
import com.twitter.follow_recommendations.common.rankers.interleave_ranker.InterleaveRanker
import com.twitter.follow_recommendations.common.rankers.ml_ranker.ranking.HydrateFeaturesTransform
import com.twitter.follow_recommendations.common.rankers.ml_ranker.ranking.MlRanker
import com.twitter.follow_recommendations.common.rankers.ml_ranker.ranking.MlRankerParams
import com.twitter.follow_recommendations.common.rankers.weighted_candidate_source_ranker.WeightedCandidateSourceRanker
import com.twitter.follow_recommendations.configapi.candidates.HydrateCandidateParamsTransform
import com.twitter.product_mixer.core.model.common.identifier.CandidateSourceIdentifier
import com.twitter.product_mixer.core.model.marshalling.request.HasClientContext
import com.twitter.timelines.configapi.HasParams
/**
* Used to build the combined ranker comprising 4 stages of ranking:
* - weighted sampler
* - truncating to the top N merged results for ranking
* - ML ranker
* - Interleaving ranker for producer-side experiments
* - impression-based fatigueing
*/
@Singleton
class PostNuxMlCombinedRankerBuilder[
T <: HasParams with HasSimilarToContext with HasClientContext with HasExcludedUserIds with HasDisplayLocation with HasDebugOptions with HasPreFetchedFeature with HasDismissedUserIds with HasQualityFactor] @Inject() (
firstNRanker: FirstNRanker[T],
hydrateFeaturesTransform: HydrateFeaturesTransform[T],
hydrateCandidateParamsTransform: HydrateCandidateParamsTransform[T],
mlRanker: MlRanker[T],
statsReceiver: StatsReceiver) {
private[this] val stats: StatsReceiver = statsReceiver.scope("post_nux_ml_ranker")
// we construct each ranker independently and chain them together
def build(
request: T,
candidateSourceWeights: Map[CandidateSourceIdentifier, Double]
): Ranker[T, CandidateUser] = {
val displayLocationStats = stats.scope(request.displayLocation.toString)
val weightedRankerStats: StatsReceiver =
displayLocationStats.scope("weighted_candidate_source_ranker")
val firstNRankerStats: StatsReceiver =
displayLocationStats.scope("first_n_ranker")
val hydrateCandidateParamsStats =
displayLocationStats.scope("hydrate_candidate_params")
val fatigueRankerStats = displayLocationStats.scope("fatigue_ranker")
val interleaveRankerStats =
displayLocationStats.scope("interleave_ranker")
val allRankersStats = displayLocationStats.scope("all_rankers")
// Checking if the heavy-ranker is an experimental model.
// If it is, InterleaveRanker and candidate parameter hydration are disabled.
// *NOTE* that consumer-side experiments should at any time take a small % of traffic, less
// than 20% for instance, to leave enough room for producer experiments. Increasing bucket
// size for producer experiments lead to other issues and is not a viable option for faster
// experiments.
val requestRankerId = request.params(MlRankerParams.RequestScorerIdParam)
if (requestRankerId != RankerId.PostNuxProdRanker) {
hydrateCandidateParamsStats.counter(s"disabled_by_${requestRankerId.toString}").incr()
interleaveRankerStats.counter(s"disabled_by_${requestRankerId.toString}").incr()
}
// weighted ranker that samples from the candidate sources
val weightedRanker = WeightedCandidateSourceRanker
.build[T](
candidateSourceWeights,
request.params(PostNuxMlParams.CandidateShuffler).shuffle(request.getRandomizationSeed),
randomSeed = request.getRandomizationSeed
).observe(weightedRankerStats)
// ranker that takes the first n results (ie truncates output) while merging duplicates
val firstNRankerObs = firstNRanker.observe(firstNRankerStats)
// either ML ranker that uses deepbirdv2 to score or no ranking
val mainRanker: Ranker[T, CandidateUser] =
buildMainRanker(request, requestRankerId == RankerId.PostNuxProdRanker, displayLocationStats)
// fatigue ranker that uses wtf impressions to fatigue
val fatigueRanker = buildFatigueRanker(request, fatigueRankerStats).observe(fatigueRankerStats)
// interleaveRanker combines rankings from several rankers and enforces candidates' ranks in
// experiment buckets according to their assigned ranker model.
val interleaveRanker =
buildInterleaveRanker(
request,
requestRankerId == RankerId.PostNuxProdRanker,
interleaveRankerStats)
.observe(interleaveRankerStats)
weightedRanker
.andThen(firstNRankerObs)
.andThen(mainRanker)
.andThen(fatigueRanker)
.andThen(interleaveRanker)
.observe(allRankersStats)
}
def buildMainRanker(
request: T,
isMainRankerPostNuxProd: Boolean,
displayLocationStats: StatsReceiver
): Ranker[T, CandidateUser] = {
// note that we may be disabling heavy ranker for users not bucketed
// (due to empty results from the new candidate source)
// need a better solution in the future
val mlRankerStats = displayLocationStats.scope("ml_ranker")
val noMlRankerStats = displayLocationStats.scope("no_ml_ranker")
val hydrateFeaturesStats =
displayLocationStats.scope("hydrate_features")
val hydrateCandidateParamsStats =
displayLocationStats.scope("hydrate_candidate_params")
val notHydrateCandidateParamsStats =
displayLocationStats.scope("not_hydrate_candidate_params")
val rankerStats = displayLocationStats.scope("ranker")
val mlRankerDisabledByExperimentsCounter =
mlRankerStats.counter("disabled_by_experiments")
val mlRankerDisabledByQualityFactorCounter =
mlRankerStats.counter("disabled_by_quality_factor")
val disabledByQualityFactor = request.qualityFactor
.exists(_ <= request.params(PostNuxMlParams.TurnoffMLScorerQFThreshold))
if (disabledByQualityFactor)
mlRankerDisabledByQualityFactorCounter.incr()
if (request.params(PostNuxMlParams.UseMlRanker) && !disabledByQualityFactor) {
val hydrateFeatures = hydrateFeaturesTransform
.observe(hydrateFeaturesStats)
val optionalHydratedParamsTransform: Transform[T, CandidateUser] = {
// We disable candidate parameter hydration for experimental heavy-ranker models.
if (isMainRankerPostNuxProd &&
request.params(PostNuxMlParams.EnableCandidateParamHydration)) {
hydrateCandidateParamsTransform
.observe(hydrateCandidateParamsStats)
} else {
new IdentityTransform[T, CandidateUser]()
.observe(notHydrateCandidateParamsStats)
}
}
val candidateSize = request.params(FirstNRankerParams.CandidatesToRank)
Ranker
.chain(
hydrateFeatures.andThen(optionalHydratedParamsTransform),
mlRanker.observe(mlRankerStats),
)
.within(
request.params(PostNuxMlParams.MlRankerBudget),
rankerStats.scope(s"n$candidateSize"))
} else {
new IdentityRanker[T, CandidateUser].observe(noMlRankerStats)
}
}
def buildInterleaveRanker(
request: T,
isMainRankerPostNuxProd: Boolean,
interleaveRankerStats: StatsReceiver
): Ranker[T, CandidateUser] = {
// InterleaveRanker is enabled only for display locations powered by the PostNux heavy-ranker.
if (request.params(PostNuxMlParams.EnableInterleaveRanker) &&
// InterleaveRanker is disabled for requests with experimental heavy-rankers.
isMainRankerPostNuxProd) {
new InterleaveRanker[T](interleaveRankerStats)
} else {
new IdentityRanker[T, CandidateUser]()
}
}
def buildFatigueRanker(
request: T,
fatigueRankerStats: StatsReceiver
): Ranker[T, CandidateUser] = {
if (request.params(PostNuxMlParams.EnableFatigueRanker)) {
ImpressionBasedFatigueRanker
.build[T](
fatigueRankerStats
).within(request.params(PostNuxMlParams.FatigueRankerBudget), fatigueRankerStats)
} else {
new IdentityRanker[T, CandidateUser]()
}
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlFlow.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.twitter.conversions.DurationOps._
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.base.EnrichedCandidateSource._
import com.twitter.follow_recommendations.common.base._
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.models.FilterReason
import com.twitter.follow_recommendations.common.predicates.dismiss.DismissedCandidatePredicate
import com.twitter.follow_recommendations.common.predicates.gizmoduck.GizmoduckPredicate
import com.twitter.follow_recommendations.common.transforms.ranker_id.RandomRankerIdTransform
import com.twitter.follow_recommendations.common.predicates.sgs.InvalidTargetCandidateRelationshipTypesPredicate
import com.twitter.follow_recommendations.common.predicates.sgs.RecentFollowingPredicate
import com.twitter.follow_recommendations.common.predicates.CandidateParamPredicate
import com.twitter.follow_recommendations.common.predicates.CandidateSourceParamPredicate
import com.twitter.follow_recommendations.common.predicates.CuratedCompetitorListPredicate
import com.twitter.follow_recommendations.common.predicates.ExcludedUserIdPredicate
import com.twitter.follow_recommendations.common.predicates.InactivePredicate
import com.twitter.follow_recommendations.common.predicates.PreviouslyRecommendedUserIdsPredicate
import com.twitter.follow_recommendations.common.predicates.user_activity.NonNearZeroUserActivityPredicate
import com.twitter.follow_recommendations.common.transforms.dedup.DedupTransform
import com.twitter.follow_recommendations.common.transforms.modify_social_proof.ModifySocialProofTransform
import com.twitter.follow_recommendations.common.transforms.tracking_token.TrackingTokenTransform
import com.twitter.follow_recommendations.common.transforms.weighted_sampling.SamplingTransform
import com.twitter.follow_recommendations.configapi.candidates.CandidateUserParamsFactory
import com.twitter.follow_recommendations.configapi.params.GlobalParams
import com.twitter.follow_recommendations.configapi.params.GlobalParams.EnableGFSSocialProofTransform
import com.twitter.follow_recommendations.utils.CandidateSourceHoldbackUtil
import com.twitter.product_mixer.core.functional_component.candidate_source.CandidateSource
import com.twitter.product_mixer.core.model.common.identifier.CandidateSourceIdentifier
import com.twitter.timelines.configapi.Params
import com.twitter.util.Duration
import javax.inject.Inject
import javax.inject.Singleton
import com.twitter.follow_recommendations.common.clients.socialgraph.SocialGraphClient
import com.twitter.follow_recommendations.common.predicates.hss.HssPredicate
import com.twitter.follow_recommendations.common.predicates.sgs.InvalidRelationshipPredicate
import com.twitter.follow_recommendations.common.transforms.modify_social_proof.RemoveAccountProofTransform
import com.twitter.follow_recommendations.logging.FrsLogger
import com.twitter.follow_recommendations.models.RecommendationFlowData
import com.twitter.follow_recommendations.utils.RecommendationFlowBaseSideEffectsUtil
import com.twitter.product_mixer.core.model.common.identifier.RecommendationPipelineIdentifier
import com.twitter.product_mixer.core.quality_factor.BoundsWithDefault
import com.twitter.product_mixer.core.quality_factor.LinearLatencyQualityFactor
import com.twitter.product_mixer.core.quality_factor.LinearLatencyQualityFactorConfig
import com.twitter.product_mixer.core.quality_factor.LinearLatencyQualityFactorObserver
import com.twitter.product_mixer.core.quality_factor.QualityFactorObserver
import com.twitter.stitch.Stitch
/**
* We use this flow for all post-nux display locations that would use a machine-learning-based-ranker
* eg HTL, Sidebar, etc
* Note that the RankedPostNuxFlow is used primarily for scribing/data collection, and doesn't
* incorporate all of the other components in a flow (candidate source generation, predicates etc)
*/
@Singleton
class PostNuxMlFlow @Inject() (
postNuxMlCandidateSourceRegistry: PostNuxMlCandidateSourceRegistry,
postNuxMlCombinedRankerBuilder: PostNuxMlCombinedRankerBuilder[PostNuxMlRequest],
curatedCompetitorListPredicate: CuratedCompetitorListPredicate,
gizmoduckPredicate: GizmoduckPredicate,
sgsPredicate: InvalidTargetCandidateRelationshipTypesPredicate,
hssPredicate: HssPredicate,
invalidRelationshipPredicate: InvalidRelationshipPredicate,
recentFollowingPredicate: RecentFollowingPredicate,
nonNearZeroUserActivityPredicate: NonNearZeroUserActivityPredicate,
inactivePredicate: InactivePredicate,
dismissedCandidatePredicate: DismissedCandidatePredicate,
previouslyRecommendedUserIdsPredicate: PreviouslyRecommendedUserIdsPredicate,
modifySocialProofTransform: ModifySocialProofTransform,
removeAccountProofTransform: RemoveAccountProofTransform,
trackingTokenTransform: TrackingTokenTransform,
randomRankerIdTransform: RandomRankerIdTransform,
candidateParamsFactory: CandidateUserParamsFactory[PostNuxMlRequest],
samplingTransform: SamplingTransform,
frsLogger: FrsLogger,
baseStatsReceiver: StatsReceiver)
extends RecommendationFlow[PostNuxMlRequest, CandidateUser]
with RecommendationFlowBaseSideEffectsUtil[PostNuxMlRequest, CandidateUser]
with CandidateSourceHoldbackUtil {
override protected val targetEligibility: Predicate[PostNuxMlRequest] =
new ParamPredicate[PostNuxMlRequest](PostNuxMlParams.TargetEligibility)
override val statsReceiver: StatsReceiver = baseStatsReceiver.scope("post_nux_ml_flow")
override val qualityFactorObserver: Option[QualityFactorObserver] = {
val config = LinearLatencyQualityFactorConfig(
qualityFactorBounds =
BoundsWithDefault(minInclusive = 0.1, maxInclusive = 1.0, default = 1.0),
initialDelay = 60.seconds,
targetLatency = 700.milliseconds,
targetLatencyPercentile = 95.0,
delta = 0.001
)
val qualityFactor = LinearLatencyQualityFactor(config)
val observer = LinearLatencyQualityFactorObserver(qualityFactor)
statsReceiver.provideGauge("quality_factor")(qualityFactor.currentValue.toFloat)
Some(observer)
}
override protected def updateTarget(request: PostNuxMlRequest): Stitch[PostNuxMlRequest] = {
Stitch.value(
request.copy(qualityFactor = qualityFactorObserver.map(_.qualityFactor.currentValue))
)
}
private[post_nux_ml] def getCandidateSourceIdentifiers(
params: Params
): Set[CandidateSourceIdentifier] = {
PostNuxMlFlowCandidateSourceWeights.getWeights(params).keySet
}
override protected def candidateSources(
request: PostNuxMlRequest
): Seq[CandidateSource[PostNuxMlRequest, CandidateUser]] = {
val identifiers = getCandidateSourceIdentifiers(request.params)
val selected: Set[CandidateSource[PostNuxMlRequest, CandidateUser]] =
postNuxMlCandidateSourceRegistry.select(identifiers)
val budget: Duration = request.params(PostNuxMlParams.FetchCandidateSourceBudget)
filterCandidateSources(
request,
selected.map(c => c.failOpenWithin(budget, statsReceiver)).toSeq)
}
override protected val preRankerCandidateFilter: Predicate[(PostNuxMlRequest, CandidateUser)] = {
val stats = statsReceiver.scope("pre_ranker")
object excludeNearZeroUserPredicate
extends GatedPredicateBase[(PostNuxMlRequest, CandidateUser)](
nonNearZeroUserActivityPredicate,
stats.scope("exclude_near_zero_predicate")
) {
override def gate(item: (PostNuxMlRequest, CandidateUser)): Boolean =
item._1.params(PostNuxMlParams.ExcludeNearZeroCandidates)
}
object invalidRelationshipGatedPredicate
extends GatedPredicateBase[(PostNuxMlRequest, CandidateUser)](
invalidRelationshipPredicate,
stats.scope("invalid_relationship_predicate")
) {
override def gate(item: (PostNuxMlRequest, CandidateUser)): Boolean =
item._1.params(PostNuxMlParams.EnableInvalidRelationshipPredicate)
}
ExcludedUserIdPredicate
.observe(stats.scope("exclude_user_id_predicate"))
.andThen(
recentFollowingPredicate.observe(stats.scope("recent_following_predicate"))
)
.andThen(
dismissedCandidatePredicate.observe(stats.scope("dismissed_candidate_predicate"))
)
.andThen(
previouslyRecommendedUserIdsPredicate.observe(
stats.scope("previously_recommended_user_ids_predicate"))
)
.andThen(
invalidRelationshipGatedPredicate.observe(stats.scope("invalid_relationship_predicate"))
)
.andThen(
excludeNearZeroUserPredicate.observe(stats.scope("exclude_near_zero_user_state"))
)
.observe(stats.scope("overall_pre_ranker_candidate_filter"))
}
override protected def selectRanker(
request: PostNuxMlRequest
): Ranker[PostNuxMlRequest, CandidateUser] = {
postNuxMlCombinedRankerBuilder.build(
request,
PostNuxMlFlowCandidateSourceWeights.getWeights(request.params))
}
override protected val postRankerTransform: Transform[PostNuxMlRequest, CandidateUser] = {
new DedupTransform[PostNuxMlRequest, CandidateUser]
.observe(statsReceiver.scope("dedupping"))
.andThen(
samplingTransform
.gated(PostNuxMlParams.SamplingTransformEnabled)
.observe(statsReceiver.scope("samplingtransform")))
}
override protected val validateCandidates: Predicate[(PostNuxMlRequest, CandidateUser)] = {
val stats = statsReceiver.scope("validate_candidates")
val competitorPredicate =
curatedCompetitorListPredicate.map[(PostNuxMlRequest, CandidateUser)](_._2)
val producerHoldbackPredicate = new CandidateParamPredicate[CandidateUser](
GlobalParams.KeepUserCandidate,
FilterReason.CandidateSideHoldback
).map[(PostNuxMlRequest, CandidateUser)] {
case (request, user) => candidateParamsFactory(user, request)
}
val pymkProducerHoldbackPredicate = new CandidateSourceParamPredicate(
GlobalParams.KeepSocialUserCandidate,
FilterReason.CandidateSideHoldback,
CandidateSourceHoldbackUtil.SocialCandidateSourceIds
).map[(PostNuxMlRequest, CandidateUser)] {
case (request, user) => candidateParamsFactory(user, request)
}
val sgsPredicateStats = stats.scope("sgs_predicate")
object sgsGatedPredicate
extends GatedPredicateBase[(PostNuxMlRequest, CandidateUser)](
sgsPredicate.observe(sgsPredicateStats),
sgsPredicateStats
) {
/**
* When SGS predicate is turned off, only query SGS exists API for (user, candidate, relationship)
* when the user's number of invalid relationships exceeds the threshold during request
* building step. This is to minimize load to SGS and underlying Flock DB.
*/
override def gate(item: (PostNuxMlRequest, CandidateUser)): Boolean =
item._1.params(PostNuxMlParams.EnableSGSPredicate) ||
SocialGraphClient.enablePostRankerSgsPredicate(
item._1.invalidRelationshipUserIds.getOrElse(Set.empty).size)
}
val hssPredicateStats = stats.scope("hss_predicate")
object hssGatedPredicate
extends GatedPredicateBase[(PostNuxMlRequest, CandidateUser)](
hssPredicate.observe(hssPredicateStats),
hssPredicateStats
) {
override def gate(item: (PostNuxMlRequest, CandidateUser)): Boolean =
item._1.params(PostNuxMlParams.EnableHssPredicate)
}
Predicate
.andConcurrently[(PostNuxMlRequest, CandidateUser)](
Seq(
competitorPredicate.observe(stats.scope("curated_competitor_predicate")),
gizmoduckPredicate.observe(stats.scope("gizmoduck_predicate")),
sgsGatedPredicate,
hssGatedPredicate,
inactivePredicate.observe(stats.scope("inactive_predicate")),
)
)
// to avoid dilutions, we need to apply the receiver holdback predicates at the very last step
.andThen(pymkProducerHoldbackPredicate.observe(stats.scope("pymk_receiver_side_holdback")))
.andThen(producerHoldbackPredicate.observe(stats.scope("receiver_side_holdback")))
.observe(stats.scope("overall_validate_candidates"))
}
override protected val transformResults: Transform[PostNuxMlRequest, CandidateUser] = {
modifySocialProofTransform
.gated(EnableGFSSocialProofTransform)
.andThen(trackingTokenTransform)
.andThen(randomRankerIdTransform.gated(PostNuxMlParams.LogRandomRankerId))
.andThen(removeAccountProofTransform.gated(PostNuxMlParams.EnableRemoveAccountProofTransform))
}
override protected def resultsConfig(request: PostNuxMlRequest): RecommendationResultsConfig = {
RecommendationResultsConfig(
request.maxResults.getOrElse(request.params(PostNuxMlParams.ResultSizeParam)),
request.params(PostNuxMlParams.BatchSizeParam)
)
}
override def applySideEffects(
target: PostNuxMlRequest,
candidateSources: Seq[CandidateSource[PostNuxMlRequest, CandidateUser]],
candidatesFromCandidateSources: Seq[CandidateUser],
mergedCandidates: Seq[CandidateUser],
filteredCandidates: Seq[CandidateUser],
rankedCandidates: Seq[CandidateUser],
transformedCandidates: Seq[CandidateUser],
truncatedCandidates: Seq[CandidateUser],
results: Seq[CandidateUser]
): Stitch[Unit] = {
frsLogger.logRecommendationFlowData[PostNuxMlRequest](
target,
RecommendationFlowData[PostNuxMlRequest](
target,
PostNuxMlFlow.identifier,
candidateSources,
candidatesFromCandidateSources,
mergedCandidates,
filteredCandidates,
rankedCandidates,
transformedCandidates,
truncatedCandidates,
results
)
)
super.applySideEffects(
target,
candidateSources,
candidatesFromCandidateSources,
mergedCandidates,
filteredCandidates,
rankedCandidates,
transformedCandidates,
truncatedCandidates,
results
)
}
}
object PostNuxMlFlow {
val identifier = RecommendationPipelineIdentifier("PostNuxMlFlow")
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlFlowCandidateSourceWeights.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ForwardEmailBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ForwardPhoneBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ReverseEmailBookSource
import com.twitter.follow_recommendations.common.candidate_sources.addressbook.ReversePhoneBookSource
import com.twitter.follow_recommendations.common.candidate_sources.crowd_search_accounts.CrowdSearchAccountsSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopCountryBackFillSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopCountrySource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopGeohashQualityFollowSource
import com.twitter.follow_recommendations.common.candidate_sources.geo.PopGeohashSource
import com.twitter.follow_recommendations.common.candidate_sources.ppmi_locale_follow.PPMILocaleFollowSource
import com.twitter.follow_recommendations.common.candidate_sources.real_graph.RealGraphOonV2Source
import com.twitter.follow_recommendations.common.candidate_sources.recent_engagement.RecentEngagementNonDirectFollowSource
import com.twitter.follow_recommendations.common.candidate_sources.recent_engagement.RepeatedProfileVisitsSource
import com.twitter.follow_recommendations.common.candidate_sources.salsa.RecentEngagementDirectFollowSalsaExpansionSource
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentEngagementSimilarUsersSource
import com.twitter.follow_recommendations.common.candidate_sources.sims_expansion.RecentFollowingSimilarUsersSource
import com.twitter.follow_recommendations.common.candidate_sources.sims.Follow2vecNearestNeighborsStore
import com.twitter.follow_recommendations.common.candidate_sources.stp.BaseOnlineSTPSource
import com.twitter.follow_recommendations.common.candidate_sources.stp.OfflineStrongTiePredictionSource
import com.twitter.follow_recommendations.common.candidate_sources.top_organic_follows_accounts.TopOrganicFollowsAccountsSource
import com.twitter.follow_recommendations.common.candidate_sources.triangular_loops.TriangularLoopsSource
import com.twitter.follow_recommendations.common.candidate_sources.two_hop_random_walk.TwoHopRandomWalkSource
import com.twitter.follow_recommendations.common.candidate_sources.user_user_graph.UserUserGraphCandidateSource
import com.twitter.follow_recommendations.flows.post_nux_ml.PostNuxMlCandidateSourceWeightParams._
import com.twitter.product_mixer.core.model.common.identifier.CandidateSourceIdentifier
import com.twitter.timelines.configapi.Params
object PostNuxMlFlowCandidateSourceWeights {
def getWeights(params: Params): Map[CandidateSourceIdentifier, Double] = {
Map[CandidateSourceIdentifier, Double](
// Social based
PPMILocaleFollowSource.Identifier -> params(CandidateWeightPPMILocaleFollow),
Follow2vecNearestNeighborsStore.IdentifierF2vLinearRegression -> params(
CandidateWeightFollow2vecNearestNeighbors),
RecentFollowingSimilarUsersSource.Identifier -> params(
CandidateWeightRecentFollowingSimilarUsers),
BaseOnlineSTPSource.Identifier -> params(CandidateWeightOnlineStp),
OfflineStrongTiePredictionSource.Identifier -> params(
CandidateWeightOfflineStrongTiePrediction),
ForwardEmailBookSource.Identifier -> params(CandidateWeightForwardEmailBook),
ForwardPhoneBookSource.Identifier -> params(CandidateWeightForwardPhoneBook),
ReverseEmailBookSource.Identifier -> params(CandidateWeightReverseEmailBook),
ReversePhoneBookSource.Identifier -> params(CandidateWeightReversePhoneBook),
TriangularLoopsSource.Identifier -> params(CandidateWeightTriangularLoops),
TwoHopRandomWalkSource.Identifier -> params(CandidateWeightTwoHopRandomWalk),
UserUserGraphCandidateSource.Identifier -> params(CandidateWeightUserUserGraph),
// Geo based
PopCountrySource.Identifier -> params(CandidateWeightPopCountry),
PopCountryBackFillSource.Identifier -> params(CandidateWeightPopGeoBackfill),
PopGeohashSource.Identifier -> params(CandidateWeightPopGeohash),
PopGeohashQualityFollowSource.Identifier -> params(CandidateWeightPopGeohashQualityFollow),
CrowdSearchAccountsSource.Identifier -> params(CandidateWeightCrowdSearch),
TopOrganicFollowsAccountsSource.Identifier -> params(CandidateWeightTopOrganicFollow),
// Engagement based
RealGraphOonV2Source.Identifier -> params(CandidateWeightRealGraphOonV2),
RecentEngagementNonDirectFollowSource.Identifier -> params(
CandidateWeightRecentEngagementNonDirectFollow),
RecentEngagementSimilarUsersSource.Identifier -> params(
CandidateWeightRecentEngagementSimilarUsers),
RepeatedProfileVisitsSource.Identifier -> params(CandidateWeightRepeatedProfileVisits),
RecentEngagementDirectFollowSalsaExpansionSource.Identifier -> params(
CandidateWeightRecentEngagementDirectFollowSalsaExpansion),
)
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
object PostNuxMlFlowCandidateSourceWeightsFeatureSwitchKeys {
val CandidateWeightCrowdSearch = "post_nux_ml_flow_candidate_source_weights_user_crowd_search"
val CandidateWeightTopOrganicFollow =
"post_nux_ml_flow_candidate_source_weights_top_organic_follow"
val CandidateWeightPPMILocaleFollow =
"post_nux_ml_flow_candidate_source_weights_user_ppmi_locale_follow"
val CandidateWeightForwardEmailBook =
"post_nux_ml_flow_candidate_source_weights_user_forward_email_book"
val CandidateWeightForwardPhoneBook =
"post_nux_ml_flow_candidate_source_weights_user_forward_phone_book"
val CandidateWeightOfflineStrongTiePrediction =
"post_nux_ml_flow_candidate_source_weights_user_offline_strong_tie_prediction"
val CandidateWeightOnlineStp = "post_nux_ml_flow_candidate_source_weights_user_online_stp"
val CandidateWeightPopCountry = "post_nux_ml_flow_candidate_source_weights_user_pop_country"
val CandidateWeightPopGeohash = "post_nux_ml_flow_candidate_source_weights_user_pop_geohash"
val CandidateWeightPopGeohashQualityFollow =
"post_nux_ml_flow_candidate_source_weights_user_pop_geohash_quality_follow"
val CandidateWeightPopGeoBackfill =
"post_nux_ml_flow_candidate_source_weights_user_pop_geo_backfill"
val CandidateWeightRecentFollowingSimilarUsers =
"post_nux_ml_flow_candidate_source_weights_user_recent_following_similar_users"
val CandidateWeightRecentEngagementDirectFollowSalsaExpansion =
"post_nux_ml_flow_candidate_source_weights_user_recent_engagement_direct_follow_salsa_expansion"
val CandidateWeightRecentEngagementNonDirectFollow =
"post_nux_ml_flow_candidate_source_weights_user_recent_engagement_non_direct_follow"
val CandidateWeightRecentEngagementSimilarUsers =
"post_nux_ml_flow_candidate_source_weights_user_recent_engagement_similar_users"
val CandidateWeightRepeatedProfileVisits =
"post_nux_ml_flow_candidate_source_weights_user_repeated_profile_visits"
val CandidateWeightFollow2vecNearestNeighbors =
"post_nux_ml_flow_candidate_source_weights_user_follow2vec_nearest_neighbors"
val CandidateWeightReverseEmailBook =
"post_nux_ml_flow_candidate_source_weights_user_reverse_email_book"
val CandidateWeightReversePhoneBook =
"post_nux_ml_flow_candidate_source_weights_user_reverse_phone_book"
val CandidateWeightTriangularLoops =
"post_nux_ml_flow_candidate_source_weights_user_triangular_loops"
val CandidateWeightTwoHopRandomWalk =
"post_nux_ml_flow_candidate_source_weights_user_two_hop_random_walk"
val CandidateWeightUserUserGraph =
"post_nux_ml_flow_candidate_source_weights_user_user_user_graph"
val CandidateWeightRealGraphOonV2 =
"post_nux_ml_flow_candidate_source_weights_user_real_graph_oon_v2"
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlFlowFSConfig.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.rankers.weighted_candidate_source_ranker.NoShuffle
import com.twitter.follow_recommendations.common.rankers.weighted_candidate_source_ranker.RandomShuffler
import com.twitter.follow_recommendations.configapi.common.FeatureSwitchConfig
import com.twitter.timelines.configapi.FSBoundedParam
import com.twitter.timelines.configapi.FSName
import com.twitter.timelines.configapi.HasDurationConversion
import com.twitter.timelines.configapi.Param
import com.twitter.util.Duration
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class PostNuxMlFlowFSConfig @Inject() () extends FeatureSwitchConfig {
override val booleanFSParams: Seq[Param[Boolean] with FSName] = Seq(
PostNuxMlParams.OnlineSTPEnabled,
PostNuxMlParams.SamplingTransformEnabled,
PostNuxMlParams.Follow2VecLinearRegressionEnabled,
PostNuxMlParams.UseMlRanker,
PostNuxMlParams.EnableCandidateParamHydration,
PostNuxMlParams.EnableInterleaveRanker,
PostNuxMlParams.EnableAdhocRanker,
PostNuxMlParams.ExcludeNearZeroCandidates,
PostNuxMlParams.IncludeRepeatedProfileVisitsCandidateSource,
PostNuxMlParams.EnableInterestsOptOutPredicate,
PostNuxMlParams.EnableSGSPredicate,
PostNuxMlParams.EnableInvalidRelationshipPredicate,
PostNuxMlParams.EnableRemoveAccountProofTransform,
PostNuxMlParams.EnablePPMILocaleFollowSourceInPostNux,
PostNuxMlParams.EnableRealGraphOonV2,
PostNuxMlParams.GetFollowersFromSgs,
PostNuxMlRequestBuilderParams.EnableInvalidRelationshipPredicate
)
override val doubleFSParams: Seq[FSBoundedParam[Double]] = Seq(
PostNuxMlCandidateSourceWeightParams.CandidateWeightCrowdSearch,
PostNuxMlCandidateSourceWeightParams.CandidateWeightTopOrganicFollow,
PostNuxMlCandidateSourceWeightParams.CandidateWeightPPMILocaleFollow,
PostNuxMlCandidateSourceWeightParams.CandidateWeightForwardEmailBook,
PostNuxMlCandidateSourceWeightParams.CandidateWeightForwardPhoneBook,
PostNuxMlCandidateSourceWeightParams.CandidateWeightOfflineStrongTiePrediction,
PostNuxMlCandidateSourceWeightParams.CandidateWeightOnlineStp,
PostNuxMlCandidateSourceWeightParams.CandidateWeightPopCountry,
PostNuxMlCandidateSourceWeightParams.CandidateWeightPopGeohash,
PostNuxMlCandidateSourceWeightParams.CandidateWeightPopGeohashQualityFollow,
PostNuxMlCandidateSourceWeightParams.CandidateWeightPopGeoBackfill,
PostNuxMlCandidateSourceWeightParams.CandidateWeightRecentFollowingSimilarUsers,
PostNuxMlCandidateSourceWeightParams.CandidateWeightRecentEngagementDirectFollowSalsaExpansion,
PostNuxMlCandidateSourceWeightParams.CandidateWeightRecentEngagementNonDirectFollow,
PostNuxMlCandidateSourceWeightParams.CandidateWeightRecentEngagementSimilarUsers,
PostNuxMlCandidateSourceWeightParams.CandidateWeightRepeatedProfileVisits,
PostNuxMlCandidateSourceWeightParams.CandidateWeightFollow2vecNearestNeighbors,
PostNuxMlCandidateSourceWeightParams.CandidateWeightReverseEmailBook,
PostNuxMlCandidateSourceWeightParams.CandidateWeightReversePhoneBook,
PostNuxMlCandidateSourceWeightParams.CandidateWeightTriangularLoops,
PostNuxMlCandidateSourceWeightParams.CandidateWeightTwoHopRandomWalk,
PostNuxMlCandidateSourceWeightParams.CandidateWeightUserUserGraph,
PostNuxMlCandidateSourceWeightParams.CandidateWeightRealGraphOonV2,
PostNuxMlParams.TurnoffMLScorerQFThreshold
)
override val durationFSParams: Seq[FSBoundedParam[Duration] with HasDurationConversion] = Seq(
PostNuxMlParams.MlRankerBudget,
PostNuxMlRequestBuilderParams.TopicIdFetchBudget,
PostNuxMlRequestBuilderParams.DismissedIdScanBudget,
PostNuxMlRequestBuilderParams.WTFImpressionsScanBudget
)
override val gatedOverridesMap = Map(
PostNuxMlFlowFeatureSwitchKeys.EnableRandomDataCollection -> Seq(
PostNuxMlParams.CandidateShuffler := new RandomShuffler[CandidateUser],
PostNuxMlParams.LogRandomRankerId := true
),
PostNuxMlFlowFeatureSwitchKeys.EnableNoShuffler -> Seq(
PostNuxMlParams.CandidateShuffler := new NoShuffle[CandidateUser]
),
)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlFlowFeatureSwitchKeys.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
object PostNuxMlFlowFeatureSwitchKeys {
val UseMlRanker = "post_nux_ml_flow_use_ml_ranker"
val EnableCandidateParamHydration = "post_nux_ml_flow_enable_candidate_param_hydration"
val OnlineSTPEnabled = "post_nux_ml_flow_online_stp_source_enabled"
val Follow2VecLinearRegressionEnabled = "post_nux_ml_flow_follow_to_vec_lr_source_enabled"
val EnableRandomDataCollection = "post_nux_ml_flow_random_data_collection_enabled"
val EnableAdhocRanker = "post_nux_ml_flow_adhoc_ranker_enabled"
val EnableFatigueRanker = "post_nux_ml_flow_fatigue_ranker_enabled"
val EnableInterleaveRanker = "post_nux_ml_flow_interleave_ranker_enabled"
val IncludeRepeatedProfileVisitsCandidateSource =
"post_nux_ml_flow_include_repeated_profile_visits_candidate_source"
val MLRankerBudget = "post_nux_ml_flow_ml_ranker_budget_millis"
val EnableNoShuffler = "post_nux_ml_flow_no_shuffler"
val SamplingTransformEnabled = "post_nux_ml_flow_sampling_transform_enabled"
val ExcludeNearZeroCandidates = "post_nux_ml_flow_exclude_near_zero_candidates"
val EnableInterestsOptOutPredicate = "post_nux_ml_flow_enable_interests_opt_out_predicate"
val EnableRemoveAccountProofTransform = "post_nux_ml_flow_enable_remove_account_proof_transform"
val EnablePPMILocaleFollowSourceInPostNux = "post_nux_ml_flow_enable_ppmilocale_follow_source"
val EnableInvalidRelationshipPredicate = "post_nux_ml_flow_enable_invalid_relationship_predicate"
val EnableRealGraphOonV2 = "post_nux_ml_flow_enable_real_graph_oon_v2"
val EnableSGSPredicate = "post_nux_ml_flow_enable_sgs_predicate"
val EnableHssPredicate = "post_nux_ml_flow_enable_hss_predicate"
val GetFollowersFromSgs = "post_nux_ml_flow_get_followers_from_sgs"
val TurnOffMLScorerQFThreshold = "post_nux_ml_flow_turn_off_ml_scorer_threhsold"
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlParams.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.twitter.conversions.DurationOps._
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.rankers.weighted_candidate_source_ranker.CandidateShuffler
import com.twitter.follow_recommendations.common.rankers.weighted_candidate_source_ranker.ExponentialShuffler
import com.twitter.timelines.configapi.DurationConversion
import com.twitter.timelines.configapi.FSBoundedParam
import com.twitter.timelines.configapi.FSParam
import com.twitter.timelines.configapi.HasDurationConversion
import com.twitter.timelines.configapi.Param
import com.twitter.util.Duration
abstract class PostNuxMlParams[A](default: A) extends Param[A](default) {
override val statName: String = "post_nux_ml/" + this.getClass.getSimpleName
}
object PostNuxMlParams {
// infra params:
case object FetchCandidateSourceBudget extends PostNuxMlParams[Duration](90.millisecond)
// WTF Impression Store has very high tail latency (p9990 or p9999), but p99 latency is pretty good (~100ms)
// set the time budget for this step to be 200ms to make the performance of service more predictable
case object FatigueRankerBudget extends PostNuxMlParams[Duration](200.millisecond)
case object MlRankerBudget
extends FSBoundedParam[Duration](
name = PostNuxMlFlowFeatureSwitchKeys.MLRankerBudget,
default = 400.millisecond,
min = 100.millisecond,
max = 800.millisecond)
with HasDurationConversion {
override val durationConversion: DurationConversion = DurationConversion.FromMillis
}
// product params:
case object TargetEligibility extends PostNuxMlParams[Boolean](true)
case object ResultSizeParam extends PostNuxMlParams[Int](3)
case object BatchSizeParam extends PostNuxMlParams[Int](12)
case object CandidateShuffler
extends PostNuxMlParams[CandidateShuffler[CandidateUser]](
new ExponentialShuffler[CandidateUser])
case object LogRandomRankerId extends PostNuxMlParams[Boolean](false)
// whether or not to use the ml ranker at all (feature hydration + ranker)
case object UseMlRanker
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.UseMlRanker, false)
// whether or not to enable candidate param hydration in postnux_ml_flow
case object EnableCandidateParamHydration
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.EnableCandidateParamHydration, false)
// Whether or not OnlineSTP candidates are considered in the final pool of candidates.
// If set to `false`, the candidate source will be removed *after* all other considerations.
case object OnlineSTPEnabled
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.OnlineSTPEnabled, false)
// Whether or not the candidates are sampled from a Plackett-Luce model
case object SamplingTransformEnabled
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.SamplingTransformEnabled, false)
// Whether or not Follow2Vec candidates are considered in the final pool of candidates.
// If set to `false`, the candidate source will be removed *after* all other considerations.
case object Follow2VecLinearRegressionEnabled
extends FSParam[Boolean](
PostNuxMlFlowFeatureSwitchKeys.Follow2VecLinearRegressionEnabled,
false)
// Whether or not to enable AdhocRanker to allow adhoc, non-ML, score modifications.
case object EnableAdhocRanker
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.EnableAdhocRanker, false)
// Whether the impression-based fatigue ranker is enabled or not.
case object EnableFatigueRanker
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.EnableFatigueRanker, true)
// whether or not to enable InterleaveRanker for producer-side experiments.
case object EnableInterleaveRanker
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.EnableInterleaveRanker, false)
// whether to exclude users in near zero user state
case object ExcludeNearZeroCandidates
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.ExcludeNearZeroCandidates, false)
case object EnablePPMILocaleFollowSourceInPostNux
extends FSParam[Boolean](
PostNuxMlFlowFeatureSwitchKeys.EnablePPMILocaleFollowSourceInPostNux,
false)
case object EnableInterestsOptOutPredicate
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.EnableInterestsOptOutPredicate, false)
case object EnableInvalidRelationshipPredicate
extends FSParam[Boolean](
PostNuxMlFlowFeatureSwitchKeys.EnableInvalidRelationshipPredicate,
false)
// Totally disabling SGS predicate need to disable EnableInvalidRelationshipPredicate as well
case object EnableSGSPredicate
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.EnableSGSPredicate, true)
case object EnableHssPredicate
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.EnableHssPredicate, true)
// Whether or not to include RepeatedProfileVisits as one of the candidate sources in the PostNuxMlFlow. If false,
// RepeatedProfileVisitsSource would not be run for the users in candidate_generation.
case object IncludeRepeatedProfileVisitsCandidateSource
extends FSParam[Boolean](
PostNuxMlFlowFeatureSwitchKeys.IncludeRepeatedProfileVisitsCandidateSource,
false)
case object EnableRealGraphOonV2
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.EnableRealGraphOonV2, false)
case object GetFollowersFromSgs
extends FSParam[Boolean](PostNuxMlFlowFeatureSwitchKeys.GetFollowersFromSgs, false)
case object EnableRemoveAccountProofTransform
extends FSParam[Boolean](
PostNuxMlFlowFeatureSwitchKeys.EnableRemoveAccountProofTransform,
false)
// quality factor threshold to turn off ML ranker completely
object TurnoffMLScorerQFThreshold
extends FSBoundedParam[Double](
name = PostNuxMlFlowFeatureSwitchKeys.TurnOffMLScorerQFThreshold,
default = 0.3,
min = 0.1,
max = 1.0)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlRequest.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.twitter.core_workflows.user_model.thriftscala.UserState
import com.twitter.follow_recommendations.common.feature_hydration.common.HasPreFetchedFeature
import com.twitter.follow_recommendations.common.models._
import com.twitter.product_mixer.core.model.marshalling.request.ClientContext
import com.twitter.product_mixer.core.model.marshalling.request.HasClientContext
import com.twitter.timelines.configapi.HasParams
import com.twitter.timelines.configapi.Params
case class PostNuxMlRequest(
override val params: Params,
override val clientContext: ClientContext,
override val similarToUserIds: Seq[Long],
inputExcludeUserIds: Seq[Long],
override val recentFollowedUserIds: Option[Seq[Long]],
override val invalidRelationshipUserIds: Option[Set[Long]],
override val recentFollowedByUserIds: Option[Seq[Long]],
override val dismissedUserIds: Option[Seq[Long]],
override val displayLocation: DisplayLocation,
maxResults: Option[Int] = None,
override val debugOptions: Option[DebugOptions] = None,
override val wtfImpressions: Option[Seq[WtfImpression]],
override val uttInterestIds: Option[Seq[Long]] = None,
override val customInterests: Option[Seq[String]] = None,
override val geohashAndCountryCode: Option[GeohashAndCountryCode] = None,
inputPreviouslyRecommendedUserIds: Option[Set[Long]] = None,
inputPreviouslyFollowedUserIds: Option[Set[Long]] = None,
override val isSoftUser: Boolean = false,
override val userState: Option[UserState] = None,
override val qualityFactor: Option[Double] = None)
extends HasParams
with HasSimilarToContext
with HasClientContext
with HasExcludedUserIds
with HasDisplayLocation
with HasDebugOptions
with HasGeohashAndCountryCode
with HasPreFetchedFeature
with HasDismissedUserIds
with HasInterestIds
with HasPreviousRecommendationsContext
with HasIsSoftUser
with HasUserState
with HasInvalidRelationshipUserIds
with HasQualityFactor {
override val excludedUserIds: Seq[Long] = {
inputExcludeUserIds ++ clientContext.userId.toSeq ++ similarToUserIds
}
override val previouslyRecommendedUserIDs: Set[Long] =
inputPreviouslyRecommendedUserIds.getOrElse(Set.empty)
override val previouslyFollowedUserIds: Set[Long] =
inputPreviouslyFollowedUserIds.getOrElse(Set.empty)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlRequestBuilder.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.clients.dismiss_store.DismissStore
import com.twitter.follow_recommendations.common.clients.geoduck.UserLocationFetcher
import com.twitter.follow_recommendations.common.clients.impression_store.WtfImpressionStore
import com.twitter.follow_recommendations.common.clients.interests_service.InterestServiceClient
import com.twitter.follow_recommendations.common.clients.socialgraph.SocialGraphClient
import com.twitter.follow_recommendations.common.clients.user_state.UserStateClient
import com.twitter.follow_recommendations.common.predicates.dismiss.DismissedCandidatePredicateParams
import com.twitter.follow_recommendations.common.utils.RescueWithStatsUtils._
import com.twitter.follow_recommendations.flows.post_nux_ml.PostNuxMlRequestBuilderParams.DismissedIdScanBudget
import com.twitter.follow_recommendations.flows.post_nux_ml.PostNuxMlRequestBuilderParams.TopicIdFetchBudget
import com.twitter.follow_recommendations.flows.post_nux_ml.PostNuxMlRequestBuilderParams.WTFImpressionsScanBudget
import com.twitter.follow_recommendations.products.common.ProductRequest
import com.twitter.inject.Logging
import com.twitter.stitch.Stitch
import com.twitter.util.Time
import javax.inject.Inject
import javax.inject.Singleton
@Singleton
class PostNuxMlRequestBuilder @Inject() (
socialGraph: SocialGraphClient,
wtfImpressionStore: WtfImpressionStore,
dismissStore: DismissStore,
userLocationFetcher: UserLocationFetcher,
interestServiceClient: InterestServiceClient,
userStateClient: UserStateClient,
statsReceiver: StatsReceiver)
extends Logging {
val stats: StatsReceiver = statsReceiver.scope("post_nux_ml_request_builder")
val invalidRelationshipUsersStats: StatsReceiver = stats.scope("invalidRelationshipUserIds")
private val invalidRelationshipUsersMaxSizeCounter =
invalidRelationshipUsersStats.counter("maxSize")
private val invalidRelationshipUsersNotMaxSizeCounter =
invalidRelationshipUsersStats.counter("notMaxSize")
def build(
req: ProductRequest,
previouslyRecommendedUserIds: Option[Set[Long]] = None,
previouslyFollowedUserIds: Option[Set[Long]] = None
): Stitch[PostNuxMlRequest] = {
val dl = req.recommendationRequest.displayLocation
val resultsStitch = Stitch.collect(
req.recommendationRequest.clientContext.userId
.map { userId =>
val lookBackDuration = req.params(DismissedCandidatePredicateParams.LookBackDuration)
val negativeStartTs = -(Time.now - lookBackDuration).inMillis
val recentFollowedUserIdsStitch =
rescueWithStats(
socialGraph.getRecentFollowedUserIds(userId),
stats,
"recentFollowedUserIds")
val invalidRelationshipUserIdsStitch =
if (req.params(PostNuxMlParams.EnableInvalidRelationshipPredicate)) {
rescueWithStats(
socialGraph
.getInvalidRelationshipUserIds(userId)
.onSuccess(ids =>
if (ids.size >= SocialGraphClient.MaxNumInvalidRelationship) {
invalidRelationshipUsersMaxSizeCounter.incr()
} else {
invalidRelationshipUsersNotMaxSizeCounter.incr()
}),
stats,
"invalidRelationshipUserIds"
)
} else {
Stitch.value(Seq.empty)
}
// recentFollowedByUserIds are only used in experiment candidate sources
val recentFollowedByUserIdsStitch = if (req.params(PostNuxMlParams.GetFollowersFromSgs)) {
rescueWithStats(
socialGraph.getRecentFollowedByUserIdsFromCachedColumn(userId),
stats,
"recentFollowedByUserIds")
} else Stitch.value(Seq.empty)
val wtfImpressionsStitch =
rescueWithStatsWithin(
wtfImpressionStore.get(userId, dl),
stats,
"wtfImpressions",
req.params(WTFImpressionsScanBudget))
val dismissedUserIdsStitch =
rescueWithStatsWithin(
dismissStore.get(userId, negativeStartTs, None),
stats,
"dismissedUserIds",
req.params(DismissedIdScanBudget))
val locationStitch =
rescueOptionalWithStats(
userLocationFetcher.getGeohashAndCountryCode(
Some(userId),
req.recommendationRequest.clientContext.ipAddress),
stats,
"userLocation"
)
val topicIdsStitch =
rescueWithStatsWithin(
interestServiceClient.fetchUttInterestIds(userId),
stats,
"topicIds",
req.params(TopicIdFetchBudget))
val userStateStitch =
rescueOptionalWithStats(userStateClient.getUserState(userId), stats, "userState")
Stitch.join(
recentFollowedUserIdsStitch,
invalidRelationshipUserIdsStitch,
recentFollowedByUserIdsStitch,
dismissedUserIdsStitch,
wtfImpressionsStitch,
locationStitch,
topicIdsStitch,
userStateStitch
)
})
resultsStitch.map {
case Some(
(
recentFollowedUserIds,
invalidRelationshipUserIds,
recentFollowedByUserIds,
dismissedUserIds,
wtfImpressions,
locationInfo,
topicIds,
userState)) =>
PostNuxMlRequest(
params = req.params,
clientContext = req.recommendationRequest.clientContext,
similarToUserIds = Nil,
inputExcludeUserIds = req.recommendationRequest.excludedIds.getOrElse(Nil),
recentFollowedUserIds = Some(recentFollowedUserIds),
invalidRelationshipUserIds = Some(invalidRelationshipUserIds.toSet),
recentFollowedByUserIds = Some(recentFollowedByUserIds),
dismissedUserIds = Some(dismissedUserIds),
displayLocation = dl,
maxResults = req.recommendationRequest.maxResults,
debugOptions = req.recommendationRequest.debugParams.flatMap(_.debugOptions),
wtfImpressions = Some(wtfImpressions),
geohashAndCountryCode = locationInfo,
uttInterestIds = Some(topicIds),
inputPreviouslyRecommendedUserIds = previouslyRecommendedUserIds,
inputPreviouslyFollowedUserIds = previouslyFollowedUserIds,
isSoftUser = req.recommendationRequest.isSoftUser,
userState = userState
)
case _ =>
PostNuxMlRequest(
params = req.params,
clientContext = req.recommendationRequest.clientContext,
similarToUserIds = Nil,
inputExcludeUserIds = req.recommendationRequest.excludedIds.getOrElse(Nil),
recentFollowedUserIds = None,
invalidRelationshipUserIds = None,
recentFollowedByUserIds = None,
dismissedUserIds = None,
displayLocation = dl,
maxResults = req.recommendationRequest.maxResults,
debugOptions = req.recommendationRequest.debugParams.flatMap(_.debugOptions),
wtfImpressions = None,
geohashAndCountryCode = None,
inputPreviouslyRecommendedUserIds = previouslyRecommendedUserIds,
inputPreviouslyFollowedUserIds = previouslyFollowedUserIds,
isSoftUser = req.recommendationRequest.isSoftUser,
userState = None
)
}
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/flows/post_nux_ml/PostNuxMlRequestBuilderParams.scala | package com.twitter.follow_recommendations.flows.post_nux_ml
import com.twitter.timelines.configapi.FSBoundedParam
import com.twitter.util.Duration
import com.twitter.conversions.DurationOps._
import com.twitter.timelines.configapi.DurationConversion
import com.twitter.timelines.configapi.FSParam
import com.twitter.timelines.configapi.HasDurationConversion
object PostNuxMlRequestBuilderParams {
case object TopicIdFetchBudget
extends FSBoundedParam[Duration](
name = "post_nux_ml_request_builder_topic_id_fetch_budget_millis",
default = 200.millisecond,
min = 80.millisecond,
max = 400.millisecond)
with HasDurationConversion {
override val durationConversion: DurationConversion = DurationConversion.FromMillis
}
case object DismissedIdScanBudget
extends FSBoundedParam[Duration](
name = "post_nux_ml_request_builder_dismissed_id_scan_budget_millis",
default = 200.millisecond,
min = 80.millisecond,
max = 400.millisecond)
with HasDurationConversion {
override val durationConversion: DurationConversion = DurationConversion.FromMillis
}
case object WTFImpressionsScanBudget
extends FSBoundedParam[Duration](
name = "post_nux_ml_request_builder_wtf_impressions_scan_budget_millis",
default = 200.millisecond,
min = 80.millisecond,
max = 400.millisecond)
with HasDurationConversion {
override val durationConversion: DurationConversion = DurationConversion.FromMillis
}
case object EnableInvalidRelationshipPredicate
extends FSParam[Boolean](
name = "post_nux_ml_request_builder_enable_invalid_relationship_predicate",
false)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/logging/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"3rdparty/jvm/com/google/inject:guice",
"3rdparty/jvm/com/google/inject/extensions:guice-assistedinject",
"3rdparty/jvm/net/codingwell:scala-guice",
"3rdparty/jvm/org/slf4j:slf4j-api",
"finatra/inject/inject-core/src/main/scala",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/constants",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/configapi/params",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models",
"follow-recommendations-service/thrift/src/main/thrift:thrift-scala",
"scribelib/marshallers/src/main/scala/com/twitter/scribelib/marshallers",
"util/util-slf4j-api/src/main/scala",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/logging/FrsLogger.scala | package com.twitter.follow_recommendations.logging
import com.twitter.finagle.stats.StatsReceiver
import com.twitter.follow_recommendations.common.constants.GuiceNamedConstants
import com.twitter.follow_recommendations.common.models.HasIsSoftUser
import com.twitter.follow_recommendations.configapi.params.GlobalParams
import com.twitter.follow_recommendations.logging.thriftscala.RecommendationLog
import com.twitter.follow_recommendations.models.DebugParams
import com.twitter.follow_recommendations.models.RecommendationFlowData
import com.twitter.follow_recommendations.models.RecommendationRequest
import com.twitter.follow_recommendations.models.RecommendationResponse
import com.twitter.follow_recommendations.models.ScoringUserRequest
import com.twitter.follow_recommendations.models.ScoringUserResponse
import com.twitter.inject.annotations.Flag
import com.twitter.logging.LoggerFactory
import com.twitter.product_mixer.core.model.marshalling.request.ClientContext
import com.twitter.product_mixer.core.model.marshalling.request.HasClientContext
import com.twitter.scribelib.marshallers.ClientDataProvider
import com.twitter.scribelib.marshallers.ExternalRefererDataProvider
import com.twitter.scribelib.marshallers.ScribeSerialization
import com.twitter.timelines.configapi.HasParams
import com.twitter.util.Time
import javax.inject.Inject
import javax.inject.Named
import javax.inject.Singleton
/**
* This is the standard logging class we use to log data into:
* 1) logs.follow_recommendations_logs
*
* This logger logs data for 2 endpoints: getRecommendations, scoreUserCandidates
* All data scribed via this logger have to be converted into the same thrift type: RecommendationLog
*
* 2) logs.frs_recommendation_flow_logs
*
* This logger logs recommendation flow data for getRecommendations requests
* All data scribed via this logger have to be converted into the same thrift type: FrsRecommendationFlowLog
*/
@Singleton
class FrsLogger @Inject() (
@Named(GuiceNamedConstants.REQUEST_LOGGER) loggerFactory: LoggerFactory,
@Named(GuiceNamedConstants.FLOW_LOGGER) flowLoggerFactory: LoggerFactory,
stats: StatsReceiver,
@Flag("log_results") serviceShouldLogResults: Boolean)
extends ScribeSerialization {
private val logger = loggerFactory.apply()
private val flowLogger = flowLoggerFactory.apply()
private val logRecommendationCounter = stats.counter("scribe_recommendation")
private val logScoringCounter = stats.counter("scribe_scoring")
private val logRecommendationFlowCounter = stats.counter("scribe_recommendation_flow")
def logRecommendationResult(
request: RecommendationRequest,
response: RecommendationResponse
): Unit = {
if (!request.isSoftUser) {
val log =
RecommendationLog(request.toOfflineThrift, response.toOfflineThrift, Time.now.inMillis)
logRecommendationCounter.incr()
logger.info(
serializeThrift(
log,
FrsLogger.LogCategory,
FrsLogger.mkProvider(request.clientContext)
))
}
}
def logScoringResult(request: ScoringUserRequest, response: ScoringUserResponse): Unit = {
if (!request.isSoftUser) {
val log =
RecommendationLog(
request.toRecommendationRequest.toOfflineThrift,
response.toRecommendationResponse.toOfflineThrift,
Time.now.inMillis)
logScoringCounter.incr()
logger.info(
serializeThrift(
log,
FrsLogger.LogCategory,
FrsLogger.mkProvider(request.toRecommendationRequest.clientContext)
))
}
}
def logRecommendationFlowData[Target <: HasClientContext with HasIsSoftUser with HasParams](
request: Target,
flowData: RecommendationFlowData[Target]
): Unit = {
if (!request.isSoftUser && request.params(GlobalParams.EnableRecommendationFlowLogs)) {
val log = flowData.toRecommendationFlowLogOfflineThrift
logRecommendationFlowCounter.incr()
flowLogger.info(
serializeThrift(
log,
FrsLogger.FlowLogCategory,
FrsLogger.mkProvider(request.clientContext)
))
}
}
// We prefer the settings given in the user request, and if none provided we default to the
// aurora service configuration.
def shouldLog(debugParamsOpt: Option[DebugParams]): Boolean =
debugParamsOpt match {
case Some(debugParams) =>
debugParams.debugOptions match {
case Some(debugOptions) =>
!debugOptions.doNotLog
case None =>
serviceShouldLogResults
}
case None =>
serviceShouldLogResults
}
}
object FrsLogger {
val LogCategory = "follow_recommendations_logs"
val FlowLogCategory = "frs_recommendation_flow_logs"
def mkProvider(clientContext: ClientContext) = new ClientDataProvider {
/** The id of the current user. When the user is logged out, this method should return None. */
override val userId: Option[Long] = clientContext.userId
/** The id of the guest, which is present in logged-in or loged-out states */
override val guestId: Option[Long] = clientContext.guestId
/** The personalization id (pid) of the user, used to personalize Twitter services */
override val personalizationId: Option[String] = None
/** The id of the individual device the user is currently using. This id will be unique for different users' devices. */
override val deviceId: Option[String] = clientContext.deviceId
/** The OAuth application id of the application the user is currently using */
override val clientApplicationId: Option[Long] = clientContext.appId
/** The OAuth parent application id of the application the user is currently using */
override val parentApplicationId: Option[Long] = None
/** The two-letter, upper-case country code used to designate the country from which the scribe event occurred */
override val countryCode: Option[String] = clientContext.countryCode
/** The two-letter, lower-case language code used to designate the probably language spoken by the scribe event initiator */
override val languageCode: Option[String] = clientContext.languageCode
/** The user-agent header used to identify the client browser or device that the user is currently active on */
override val userAgent: Option[String] = clientContext.userAgent
/** Whether the user is accessing Twitter via a secured connection */
override val isSsl: Option[Boolean] = Some(true)
/** The referring URL to the current page for web-based clients, if applicable */
override val referer: Option[String] = None
/**
* The external site, partner, or email that lead to the current Twitter application. Returned value consists of a
* tuple including the encrypted referral data and the type of referral
*/
override val externalReferer: Option[ExternalRefererDataProvider] = None
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models/BUILD | scala_library(
compiler_option_sets = ["fatal_warnings"],
platform = "java8",
tags = ["bazel-compatible"],
dependencies = [
"configapi/configapi-core/src/main/scala/com/twitter/timelines/configapi",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/feature_hydration/common",
"follow-recommendations-service/common/src/main/scala/com/twitter/follow_recommendations/common/models",
"follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/assembler/models",
"follow-recommendations-service/thrift/src/main/thrift:thrift-scala",
"product-mixer/core/src/main/scala/com/twitter/product_mixer/core/model/marshalling/request",
],
)
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models/CandidateSourceType.scala | package com.twitter.follow_recommendations.models
object CandidateSourceType extends Enumeration {
type CandidateSourceType = Value
val Social = Value("social")
val GeoAndInterests = Value("geo_and_interests")
val ActivityContextual = Value("activity_contextual")
val None = Value("none")
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models/CandidateUserDebugParams.scala | package com.twitter.follow_recommendations.models
import com.twitter.timelines.configapi.Params
case class CandidateUserDebugParams(paramsMap: Map[Long, Params])
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models/DebugParams.scala | package com.twitter.follow_recommendations.models
import com.twitter.follow_recommendations.common.models.DebugOptions
import com.twitter.follow_recommendations.common.models.DebugOptions.fromDebugParamsThrift
import com.twitter.follow_recommendations.logging.{thriftscala => offline}
import com.twitter.follow_recommendations.{thriftscala => t}
import com.twitter.timelines.configapi.{FeatureValue => ConfigApiFeatureValue}
case class DebugParams(
featureOverrides: Option[Map[String, ConfigApiFeatureValue]],
debugOptions: Option[DebugOptions])
object DebugParams {
def fromThrift(thrift: t.DebugParams): DebugParams = DebugParams(
featureOverrides = thrift.featureOverrides.map { map =>
map.mapValues(FeatureValue.fromThrift).toMap
},
debugOptions = Some(
fromDebugParamsThrift(thrift)
)
)
def toOfflineThrift(model: DebugParams): offline.OfflineDebugParams =
offline.OfflineDebugParams(randomizationSeed = model.debugOptions.flatMap(_.randomizationSeed))
}
trait HasFrsDebugParams {
def frsDebugParams: Option[DebugParams]
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models/DisplayContext.scala | package com.twitter.follow_recommendations.models
import com.twitter.follow_recommendations.common.models.FlowContext
import com.twitter.follow_recommendations.common.models.RecentlyEngagedUserId
import com.twitter.follow_recommendations.logging.thriftscala.OfflineDisplayContext
import com.twitter.follow_recommendations.logging.{thriftscala => offline}
import com.twitter.follow_recommendations.{thriftscala => t}
import scala.reflect.ClassTag
import scala.reflect.classTag
trait DisplayContext {
def toOfflineThrift: offline.OfflineDisplayContext
}
object DisplayContext {
case class Profile(profileId: Long) extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.Profile(offline.OfflineProfile(profileId))
}
case class Search(searchQuery: String) extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.Search(offline.OfflineSearch(searchQuery))
}
case class Rux(focalAuthorId: Long) extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.Rux(offline.OfflineRux(focalAuthorId))
}
case class Topic(topicId: Long) extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.Topic(offline.OfflineTopic(topicId))
}
case class ReactiveFollow(followedUserIds: Seq[Long]) extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.ReactiveFollow(offline.OfflineReactiveFollow(followedUserIds))
}
case class NuxInterests(flowContext: Option[FlowContext], uttInterestIds: Option[Seq[Long]])
extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.NuxInterests(
offline.OfflineNuxInterests(flowContext.map(_.toOfflineThrift)))
}
case class PostNuxFollowTask(flowContext: Option[FlowContext]) extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.PostNuxFollowTask(
offline.OfflinePostNuxFollowTask(flowContext.map(_.toOfflineThrift)))
}
case class AdCampaignTarget(similarToUserIds: Seq[Long]) extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.AdCampaignTarget(
offline.OfflineAdCampaignTarget(similarToUserIds))
}
case class ConnectTab(
byfSeedUserIds: Seq[Long],
similarToUserIds: Seq[Long],
engagedUserIds: Seq[RecentlyEngagedUserId])
extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.ConnectTab(
offline.OfflineConnectTab(
byfSeedUserIds,
similarToUserIds,
engagedUserIds.map(user => user.toOfflineThrift)))
}
case class SimilarToUser(similarToUserId: Long) extends DisplayContext {
override val toOfflineThrift: OfflineDisplayContext =
offline.OfflineDisplayContext.SimilarToUser(offline.OfflineSimilarToUser(similarToUserId))
}
def fromThrift(tDisplayContext: t.DisplayContext): DisplayContext = tDisplayContext match {
case t.DisplayContext.Profile(p) => Profile(p.profileId)
case t.DisplayContext.Search(s) => Search(s.searchQuery)
case t.DisplayContext.Rux(r) => Rux(r.focalAuthorId)
case t.DisplayContext.Topic(t) => Topic(t.topicId)
case t.DisplayContext.ReactiveFollow(f) => ReactiveFollow(f.followedUserIds)
case t.DisplayContext.NuxInterests(n) =>
NuxInterests(n.flowContext.map(FlowContext.fromThrift), n.uttInterestIds)
case t.DisplayContext.AdCampaignTarget(a) =>
AdCampaignTarget(a.similarToUserIds)
case t.DisplayContext.ConnectTab(connect) =>
ConnectTab(
connect.byfSeedUserIds,
connect.similarToUserIds,
connect.recentlyEngagedUserIds.map(RecentlyEngagedUserId.fromThrift))
case t.DisplayContext.SimilarToUser(r) =>
SimilarToUser(r.similarToUserId)
case t.DisplayContext.PostNuxFollowTask(p) =>
PostNuxFollowTask(p.flowContext.map(FlowContext.fromThrift))
case t.DisplayContext.UnknownUnionField(t) =>
throw new UnknownDisplayContextException(t.field.name)
}
def getDisplayContextAs[T <: DisplayContext: ClassTag](displayContext: DisplayContext): T =
displayContext match {
case context: T => context
case _ =>
throw new UnexpectedDisplayContextTypeException(
displayContext,
classTag[T].getClass.getSimpleName)
}
}
class UnknownDisplayContextException(name: String)
extends Exception(s"Unknown DisplayContext in Thrift: ${name}")
class UnexpectedDisplayContextTypeException(displayContext: DisplayContext, expectedType: String)
extends Exception(s"DisplayContext ${displayContext} not of expected type ${expectedType}")
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models/FeatureValue.scala | package com.twitter.follow_recommendations.models
import com.twitter.follow_recommendations.{thriftscala => t}
import com.twitter.timelines.configapi._
object FeatureValue {
def fromThrift(thriftFeatureValue: t.FeatureValue): FeatureValue = thriftFeatureValue match {
case t.FeatureValue.PrimitiveValue(t.PrimitiveFeatureValue.BoolValue(bool)) =>
BooleanFeatureValue(bool)
case t.FeatureValue.PrimitiveValue(t.PrimitiveFeatureValue.StrValue(string)) =>
StringFeatureValue(string)
case t.FeatureValue.PrimitiveValue(t.PrimitiveFeatureValue.IntValue(int)) =>
NumberFeatureValue(int)
case t.FeatureValue.PrimitiveValue(t.PrimitiveFeatureValue.LongValue(long)) =>
NumberFeatureValue(long)
case t.FeatureValue.PrimitiveValue(t.PrimitiveFeatureValue.UnknownUnionField(field)) =>
throw new UnknownFeatureValueException(s"Primitive: ${field.field.name}")
case t.FeatureValue.UnknownUnionField(field) =>
throw new UnknownFeatureValueException(field.field.name)
}
}
class UnknownFeatureValueException(fieldName: String)
extends Exception(s"Unknown FeatureValue name in thrift: ${fieldName}")
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models/RecommendationFlowData.scala | package com.twitter.follow_recommendations.models
import com.twitter.follow_recommendations.common.models.CandidateUser
import com.twitter.follow_recommendations.common.models.ClientContextConverter
import com.twitter.follow_recommendations.common.models.HasUserState
import com.twitter.follow_recommendations.common.utils.UserSignupUtil
import com.twitter.follow_recommendations.logging.{thriftscala => offline}
import com.twitter.product_mixer.core.functional_component.candidate_source.CandidateSource
import com.twitter.product_mixer.core.model.common.identifier.CandidateSourceIdentifier
import com.twitter.product_mixer.core.model.common.identifier.RecommendationPipelineIdentifier
import com.twitter.product_mixer.core.model.marshalling.HasMarshalling
import com.twitter.product_mixer.core.model.marshalling.request.HasClientContext
import com.twitter.util.Time
case class RecommendationFlowData[Target <: HasClientContext](
request: Target,
recommendationFlowIdentifier: RecommendationPipelineIdentifier,
candidateSources: Seq[CandidateSource[Target, CandidateUser]],
candidatesFromCandidateSources: Seq[CandidateUser],
mergedCandidates: Seq[CandidateUser],
filteredCandidates: Seq[CandidateUser],
rankedCandidates: Seq[CandidateUser],
transformedCandidates: Seq[CandidateUser],
truncatedCandidates: Seq[CandidateUser],
results: Seq[CandidateUser])
extends HasMarshalling {
import RecommendationFlowData._
lazy val toRecommendationFlowLogOfflineThrift: offline.RecommendationFlowLog = {
val userMetadata = userToOfflineRecommendationFlowUserMetadata(request)
val signals = userToOfflineRecommendationFlowSignals(request)
val filteredCandidateSourceCandidates =
candidatesToOfflineRecommendationFlowCandidateSourceCandidates(
candidateSources,
filteredCandidates
)
val rankedCandidateSourceCandidates =
candidatesToOfflineRecommendationFlowCandidateSourceCandidates(
candidateSources,
rankedCandidates
)
val truncatedCandidateSourceCandidates =
candidatesToOfflineRecommendationFlowCandidateSourceCandidates(
candidateSources,
truncatedCandidates
)
offline.RecommendationFlowLog(
ClientContextConverter.toFRSOfflineClientContextThrift(request.clientContext),
userMetadata,
signals,
Time.now.inMillis,
recommendationFlowIdentifier.name,
Some(filteredCandidateSourceCandidates),
Some(rankedCandidateSourceCandidates),
Some(truncatedCandidateSourceCandidates)
)
}
}
object RecommendationFlowData {
def userToOfflineRecommendationFlowUserMetadata[Target <: HasClientContext](
request: Target
): Option[offline.OfflineRecommendationFlowUserMetadata] = {
val userSignupAge = UserSignupUtil.userSignupAge(request).map(_.inDays)
val userState = request match {
case req: HasUserState => req.userState.map(_.name)
case _ => None
}
Some(offline.OfflineRecommendationFlowUserMetadata(userSignupAge, userState))
}
def userToOfflineRecommendationFlowSignals[Target <: HasClientContext](
request: Target
): Option[offline.OfflineRecommendationFlowSignals] = {
val countryCode = request.getCountryCode
Some(offline.OfflineRecommendationFlowSignals(countryCode))
}
def candidatesToOfflineRecommendationFlowCandidateSourceCandidates[Target <: HasClientContext](
candidateSources: Seq[CandidateSource[Target, CandidateUser]],
candidates: Seq[CandidateUser],
): Seq[offline.OfflineRecommendationFlowCandidateSourceCandidates] = {
val candidatesGroupedByCandidateSources =
candidates.groupBy(
_.getPrimaryCandidateSource.getOrElse(CandidateSourceIdentifier("NoCandidateSource")))
candidateSources.map(candidateSource => {
val candidates =
candidatesGroupedByCandidateSources.get(candidateSource.identifier).toSeq.flatten
val candidateUserIds = candidates.map(_.id)
val candidateUserScores = candidates.map(_.score).exists(_.nonEmpty) match {
case true => Some(candidates.map(_.score.getOrElse(-1.0)))
case false => None
}
offline.OfflineRecommendationFlowCandidateSourceCandidates(
candidateSource.identifier.name,
candidateUserIds,
candidateUserScores
)
})
}
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models/RecommendationRequest.scala | package com.twitter.follow_recommendations.models
import com.twitter.follow_recommendations.common.models.ClientContextConverter
import com.twitter.follow_recommendations.common.models.DisplayLocation
import com.twitter.follow_recommendations.logging.{thriftscala => offline}
import com.twitter.product_mixer.core.model.marshalling.request.ClientContext
case class RecommendationRequest(
clientContext: ClientContext,
displayLocation: DisplayLocation,
displayContext: Option[DisplayContext],
maxResults: Option[Int],
cursor: Option[String],
excludedIds: Option[Seq[Long]],
fetchPromotedContent: Option[Boolean],
debugParams: Option[DebugParams] = None,
userLocationState: Option[String] = None,
isSoftUser: Boolean = false) {
def toOfflineThrift: offline.OfflineRecommendationRequest = offline.OfflineRecommendationRequest(
ClientContextConverter.toFRSOfflineClientContextThrift(clientContext),
displayLocation.toOfflineThrift,
displayContext.map(_.toOfflineThrift),
maxResults,
cursor,
excludedIds,
fetchPromotedContent,
debugParams.map(DebugParams.toOfflineThrift)
)
}
|
the-algorithm-main/follow-recommendations-service/server/src/main/scala/com/twitter/follow_recommendations/models/RecommendationResponse.scala | package com.twitter.follow_recommendations.models
import com.twitter.follow_recommendations.{thriftscala => t}
import com.twitter.follow_recommendations.logging.{thriftscala => offline}
import com.twitter.follow_recommendations.common.models.Recommendation
import com.twitter.product_mixer.core.model.marshalling.HasMarshalling
case class RecommendationResponse(recommendations: Seq[Recommendation]) extends HasMarshalling {
lazy val toThrift: t.RecommendationResponse =
t.RecommendationResponse(recommendations.map(_.toThrift))
lazy val toOfflineThrift: offline.OfflineRecommendationResponse =
offline.OfflineRecommendationResponse(recommendations.map(_.toOfflineThrift))
}
|
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