Typo: Standlone -> Standalone

Author: Andrew Ash <andrew@andrewash.com>

Closes #601 from ash211/typo and squashes the following commits:

9cd43ac [Andrew Ash] Change docs references to metrics.properties, not metrics.conf
3813ff1 [Andrew Ash] Typo: mulitcast -> multicast
873bd2f [Andrew Ash] Typo: Standlone -> Standalone
[SPARK-1092] print warning information if user use SPARK_MEM to regulate executor memory usage

https://spark-project.atlassian.net/browse/SPARK-1092?jql=project%20%3D%20SPARK

print warning information if user set SPARK_MEM to regulate memory usage of executors

----
OUTDATED:

Currently, users will usually set SPARK_MEM to control the memory usage of driver programs, (in spark-class)
91 JAVA_OPTS="$OUR_JAVA_OPTS"
92 JAVA_OPTS="$JAVA_OPTS -Djava.library.path=$SPARK_LIBRARY_PATH"
93 JAVA_OPTS="$JAVA_OPTS -Xms$SPARK_MEM -Xmx$SPARK_MEM"
if they didn't set spark.executor.memory, the value in this environment variable will also affect the memory usage of executors, because the following lines in SparkContext
privatespark val executorMemory = conf.getOption("spark.executor.memory")
.orElse(Option(System.getenv("SPARK_MEM")))
.map(Utils.memoryStringToMb)
.getOrElse(512)
also
since SPARK_MEM has been (proposed to) deprecated in SPARK-929 (https://spark-project.atlassian.net/browse/SPARK-929) and the corresponding PR (https://github.com/apache/incubator-spark/pull/104)
we should remove this line

Author: CodingCat <zhunansjtu@gmail.com>

Closes #602 from CodingCat/clean_spark_mem and squashes the following commits:

302bb28 [CodingCat] print warning information if user use SPARK_MEM to regulate executor memory usage
fix for https://spark-project.atlassian.net/browse/SPARK-1052

Author: Bijay Bisht <bijay.bisht@gmail.com>

Closes #568 from bijaybisht/SPARK-1052 and squashes the following commits:

da70395 [Bijay Bisht] fix for https://spark-project.atlassian.net/browse/SPARK-1052 - comments incorporated
fdb1d94 [Bijay Bisht] fix for https://spark-project.atlassian.net/browse/SPARK-1052

(cherry picked from commit e797c1abd9692f1b7ec290e4c83d31fd106e6b05)
Signed-off-by: Aaron Davidson <aaron@databricks.com>
Add subtractByKey to the JavaPairRDD wrapper

Author: Punya Biswal <pbiswal@palantir.com>

Closes #600 from punya/subtractByKey-java and squashes the following commits:

e961913 [Punya Biswal] Hide implicit ClassTags from Java API
c5d317b [Punya Biswal] Add subtractByKey to the JavaPairRDD wrapper
Worker registration logging fix

Author: Andrew Ash <andrew@andrewash.com>

Closes #608 from ash211/patch-7 and squashes the following commits:

bd85f2a [Andrew Ash] Worker registration logging fix
Fix typos in Spark Streaming programming guide

Author: Andrew Or <andrewor14@gmail.com>

Closes #536 from andrewor14/streaming-typos and squashes the following commits:

a05faa6 [Andrew Or] Fix broken link and wording
bc2e4bc [Andrew Or] Merge github.com:apache/incubator-spark into streaming-typos
d5515b4 [Andrew Or] TD's comments
767ef12 [Andrew Or] Fix broken links
8f4c731 [Andrew Or] Fix typos in programming guide
[SPARK-1090] improvement on spark_shell (help information, configure memory)

https://spark-project.atlassian.net/browse/SPARK-1090

spark-shell should print help information about parameters and should allow user to configure exe memory
there is no document about hot to set --cores/-c in spark-shell

and also

users should be able to set executor memory through command line options

In this PR I also check the format of the options passed by the user

Author: CodingCat <zhunansjtu@gmail.com>

Closes #599 from CodingCat/spark_shell_improve and squashes the following commits:

de5aa38 [CodingCat] add parameter to set driver memory
915cbf8 [CodingCat] improvement on spark_shell (help information, configure memory)
SPARK-1098: Minor cleanup of ClassTag usage in Java API

Our usage of fake ClassTags in this manner is probably not healthy, but I'm not sure if there's a better solution available, so I just cleaned up and documented the current one.

Author: Aaron Davidson <aaron@databricks.com>

Closes #604 from aarondav/master and squashes the following commits:

b398e89 [Aaron Davidson] SPARK-1098: Minor cleanup of ClassTag usage in Java API
Optimized imports

Optimized imports and arranged according to scala style guide @
https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide#SparkCodeStyleGuide-Imports

Author: NirmalReddy <nirmal.reddy@imaginea.com>
Author: NirmalReddy <nirmal_reddy2000@yahoo.com>

Closes #613 from NirmalReddy/opt-imports and squashes the following commits:

578b4f5 [NirmalReddy] imported java.lang.Double as JDouble
a2cbcc5 [NirmalReddy] addressed the comments
776d664 [NirmalReddy] Optimized imports in core
[SPARK-1105] fix site scala version error in doc

https://spark-project.atlassian.net/browse/SPARK-1105

fix site scala version error

Author: CodingCat <zhunansjtu@gmail.com>

Closes #616 from CodingCat/doc_version and squashes the following commits:

eafd99a [CodingCat] fix site scala version error in doc
Revert "[SPARK-1105] fix site scala version error in doc"

This reverts commit d99773d5bba674cc1434c86435b6d9b3739314c8.
SPARK-1106: check key name and identity file before launch a cluster

I launched an EC2 cluster without providing a key name and an identity file. The error showed up after two minutes. It would be good to check those options before launch, given the fact that EC2 billing rounds up to hours.

JIRA: https://spark-project.atlassian.net/browse/SPARK-1106

Author: Xiangrui Meng <meng@databricks.com>

Closes #617 from mengxr/ec2 and squashes the following commits:

2dfb316 [Xiangrui Meng] check key name and identity file before launch a cluster
[SPARK-1105] fix site scala version error in docs

https://spark-project.atlassian.net/browse/SPARK-1105

fix site scala version error

Author: CodingCat <zhunansjtu@gmail.com>

Closes #618 from CodingCat/doc_version and squashes the following commits:

39bb8aa [CodingCat] more fixes
65bedb0 [CodingCat] fix site scala version error in doc
MLLIB-24:  url of "Collaborative Filtering for Implicit Feedback Datasets" in ALS is invalid now

url of "Collaborative Filtering for Implicit Feedback Datasets"  is invalid now. A new url is provided. http://research.yahoo.com/files/HuKorenVolinsky-ICDM08.pdf

Author: Chen Chao <crazyjvm@gmail.com>

Closes #619 from CrazyJvm/master and squashes the following commits:

a0b54e4 [Chen Chao] change url to IEEE
9e0e9f0 [Chen Chao] correct spell mistale
fcfab5d [Chen Chao] wrap line to to fit within 100 chars
590d56e [Chen Chao] url error
MLLIB-22. Support negative implicit input in ALS

I'm back with another less trivial suggestion for ALS:

In ALS for implicit feedback, input values are treated as weights on squared-errors in a loss function (or rather, the weight is a simple function of the input r, like c = 1 + alpha*r). The paper on which it's based assumes that the input is positive. Indeed, if the input is negative, it will create a negative weight on squared-errors, which causes things to go haywire. The optimization will try to make the error in a cell as large possible, and the result is silently bogus.

There is a good use case for negative input values though. Implicit feedback is usually collected from signals of positive interaction like a view or like or buy, but equally, can come from "not interested" signals. The natural representation is negative values.

The algorithm can be extended quite simply to provide a sound interpretation of these values: negative values should encourage the factorization to come up with 0 for cells with large negative input values, just as much as positive values encourage it to come up with 1.

The implications for the algorithm are simple:
* the confidence function value must not be negative, and so can become 1 + alpha*|r|
* the matrix P should have a value 1 where the input R is _positive_, not merely where it is non-zero. Actually, that's what the paper already says, it's just that we can't assume P = 1 when a cell in R is specified anymore, since it may be negative

This in turn entails just a few lines of code change in `ALS.scala`:
* `rs(i)` becomes `abs(rs(i))`
* When constructing `userXy(us(i))`, it's implicitly only adding where P is 1. That had been true for any us(i) that is iterated over, before, since these are exactly the ones for which P is 1. But now P is zero where rs(i) <= 0, and should not be added

I think it's a safe change because:
* It doesn't change any existing behavior (unless you're using negative values, in which case results are already borked)
* It's the simplest direct extension of the paper's algorithm
* (I've used it to good effect in production FWIW)

Tests included.

I tweaked minor things en route:
* `ALS.scala` javadoc writes "R = Xt*Y" when the paper and rest of code defines it as "R = X*Yt"
* RMSE in the ALS tests uses a confidence-weighted mean, but the denominator is not actually sum of weights

Excuse my Scala style; I'm sure it needs tweaks.

Author: Sean Owen <sowen@cloudera.com>

Closes #500 from srowen/ALSNegativeImplicitInput and squashes the following commits:

cf902a9 [Sean Owen] Support negative implicit input in ALS
953be1c [Sean Owen] Make weighted RMSE in ALS test actually weighted; adjust comment about R = X*Yt
Super minor: Add require for mergeCombiners in combineByKey

We changed the behavior in 0.9.0 from requiring that mergeCombiners be null when mapSideCombine was false to requiring that mergeCombiners *never* be null, for external sorting. This patch adds a require() to make this behavior change explicitly messaged rather than resulting in a NPE.

Author: Aaron Davidson <aaron@databricks.com>

Closes #623 from aarondav/master and squashes the following commits:

520b80c [Aaron Davidson] Super minor: Add require for mergeCombiners in combineByKey
SPARK-1114: Allow PySpark to use existing JVM and Gateway

Patch to allow PySpark to use existing JVM and Gateway. Changes to PySpark implementation of SparkConf to take existing SparkConf JVM handle. Change to PySpark SparkContext to allow subclass specific context initialization.

Author: Ahir Reddy <ahirreddy@gmail.com>

Closes #622 from ahirreddy/pyspark-existing-jvm and squashes the following commits:

a86f457 [Ahir Reddy] Patch to allow PySpark to use existing JVM and Gateway. Changes to PySpark implementation of SparkConf to take existing SparkConf JVM handle. Change to PySpark SparkContext to allow subclass specific context initialization.
SPARK-1111: URL Validation Throws Error for HDFS URL's

Fixes an error where HDFS URL's cause an exception. Should be merged into master and 0.9.

Author: Patrick Wendell <pwendell@gmail.com>

Closes #625 from pwendell/url-validation and squashes the following commits:

d14bfe3 [Patrick Wendell] SPARK-1111: URL Validation Throws Error for HDFS URL's
MLLIB-25: Implicit ALS runs out of memory for moderately large numbers of features

There's a step in implicit ALS where the matrix `Yt * Y` is computed. It's computed as the sum of matrices; an f x f matrix is created for each of n user/item rows in a partition. In `ALS.scala:214`:

```
        factors.flatMapValues{ case factorArray =>
          factorArray.map{ vector =>
            val x = new DoubleMatrix(vector)
            x.mmul(x.transpose())
          }
        }.reduceByKeyLocally((a, b) => a.addi(b))
         .values
         .reduce((a, b) => a.addi(b))
```

Completely correct, but there's a subtle but quite large memory problem here. map() is going to create all of these matrices in memory at once, when they don't need to ever all exist at the same time.
For example, if a partition has n = 100000 rows, and f = 200, then this intermediate product requires 32GB of heap. The computation will never work unless you can cough up workers with (more than) that much heap.

Fortunately there's a trivial change that fixes it; just add `.view` in there.

Author: Sean Owen <sowen@cloudera.com>

Closes #629 from srowen/ALSMatrixAllocationOptimization and squashes the following commits:

062cda9 [Sean Owen] Update style per review comments
e9a5d63 [Sean Owen] Avoid unnecessary out of memory situation by not simultaneously allocating lots of matrices
[SPARK-1113] External spilling - fix Int.MaxValue hash code collision bug

The original poster of this bug is @guojc, who opened a PR that preceded this one at https://github.com/apache/incubator-spark/pull/612.

ExternalAppendOnlyMap uses key hash code to order the buffer streams from which spilled files are read back into memory. When a buffer stream is empty, the default hash code for that stream is equal to Int.MaxValue. This is, however, a perfectly legitimate candidate for a key hash code. When reading from a spilled map containing such a key, a hash collision may occur, in which case we attempt to read from an empty stream and throw NoSuchElementException.

The fix is to maintain the invariant that empty buffer streams are never added back to the merge queue to be considered. This guarantees that we never read from an empty buffer stream, ever again.

This PR also includes two new tests for hash collisions.

Author: Andrew Or <andrewor14@gmail.com>

Closes #624 from andrewor14/spilling-bug and squashes the following commits:

9e7263d [Andrew Or] Slightly optimize next()
2037ae2 [Andrew Or] Move a few comments around...
cf95942 [Andrew Or] Remove default value of Int.MaxValue for minKeyHash
c11f03b [Andrew Or] Fix Int.MaxValue hash collision bug in ExternalAppendOnlyMap
21c1a39 [Andrew Or] Add hash collision tests to ExternalAppendOnlyMapSuite