[SPARK-3121] Wrong implementation of implicit bytesWritableConverter

val path = ... //path to seq file with BytesWritable as type of both key and value
val file = sc.sequenceFile[Array[Byte],Array[Byte]](path)
file.take(1)(0)._1

This prints incorrect content of byte array. Actual content starts with correct one and some "random" bytes and zeros are appended. BytesWritable has two methods:

getBytes() - return content of all internal array which is often longer then actual value stored. It usually contains the rest of previous longer values

copyBytes() - return just begining of internal array determined by internal length property

It looks like in implicit conversion between BytesWritable and Array[byte] getBytes is used instead of correct copyBytes.

dbtsai

Author: Jakub Dubovský <james64@inMail.sk>
Author: Dubovsky Jakub <dubovsky@avast.com>

Closes #2712 from james64/3121-bugfix and squashes the following commits:

f85d24c [Jakub Dubovský] Test name changed, comments added
1b20d51 [Jakub Dubovský] Import placed correctly
406e26c [Jakub Dubovský] Scala style fixed
f92ffa6 [Dubovsky Jakub] performance tuning
480f9cd [Dubovsky Jakub] Bug 3121 fixed
[SPARK-3905][Web UI]The keys for sorting the columns of Executor page ,Stage page Storage page are incorrect

Author: GuoQiang Li <witgo@qq.com>

Closes #2763 from witgo/SPARK-3905 and squashes the following commits:

17d7990 [GuoQiang Li] The keys for sorting the columns of Executor page ,Stage page Storage page are incorrect
Add echo "Run streaming tests ..."

Author: Ken Takagiwa <ugw.gi.world@gmail.com>

Closes #2778 from giwa/patch-2 and squashes the following commits:

a59f9a1 [Ken Takagiwa] Add echo "Run streaming tests ..."
[SPARK-3899][Doc]fix wrong links in streaming doc

There are three  [Custom Receiver Guide] links in streaming doc, the first is wrong.

Author: w00228970 <wangfei1@huawei.com>
Author: wangfei <wangfei1@huawei.com>

Closes #2749 from scwf/streaming-doc and squashes the following commits:

0cd76b7 [wangfei] update link tojump to the Akka-specific section
45b0646 [w00228970] wrong link in streaming doc
Bug Fix: without unpersist method in RandomForest.scala

During trainning Gradient Boosting Decision Tree on large-scale sparse data, spark spill hundreds of data onto disk. And find the bug below:
    In version 1.1.0 DecisionTree.scala, train Method, treeInput has been persisted in Memory, but without unpersist. It caused heavy DISK usage.
    In github version(1.2.0 maybe), RandomForest.scala, train Method, baggedInput has been persisted but without unpersisted too.

After added unpersist, it works right.
https://issues.apache.org/jira/browse/SPARK-3918

Author: omgteam <Kimlong.Liu@gmail.com>

Closes #2775 from omgteam/master and squashes the following commits:

815d543 [omgteam] adjust tab to spaces
1a36f83 [omgteam] Bug: fix without unpersist baggedInput in RandomForest.scala
[SPARK-3861][SQL] Avoid rebuilding hash tables for broadcast joins on each partition

Author: Reynold Xin <rxin@apache.org>

Closes #2727 from rxin/SPARK-3861-broadcast-hash-2 and squashes the following commits:

9c7b1a2 [Reynold Xin] Revert "Reuse CompactBuffer in UniqueKeyHashedRelation."
97626a1 [Reynold Xin] Reuse CompactBuffer in UniqueKeyHashedRelation.
7fcffb5 [Reynold Xin] Make UniqueKeyHashedRelation private[joins].
18eb214 [Reynold Xin] Merge branch 'SPARK-3861-broadcast-hash' into SPARK-3861-broadcast-hash-1
4b9d0c9 [Reynold Xin] UniqueKeyHashedRelation.get should return null if the value is null.
e0ebdd1 [Reynold Xin] Added a test case.
90b58c0 [Reynold Xin] [SPARK-3861] Avoid rebuilding hash tables on each partition
0c0082b [Reynold Xin] Fix line length.
cbc664c [Reynold Xin] Rename join -> joins package.
a070d44 [Reynold Xin] Fix line length in HashJoin
a39be8c [Reynold Xin] [SPARK-3857] Create a join package for various join operators.
[Spark] RDD take() method: overestimate too much

In the comment (Line 1083), it says: "Otherwise, interpolate the number of partitions we need to try, but overestimate it by 50%."

`(1.5 * num * partsScanned / buf.size).toInt` is the guess of "num of total partitions needed". In every iteration, we should consider the increment `(1.5 * num * partsScanned / buf.size).toInt - partsScanned`
Existing implementation 'exponentially' grows `partsScanned ` ( roughly: `x_{n+1} >= (1.5 + 1) x_n`)

This could be a performance problem. (unless this is the intended behavior)

Author: yingjieMiao <yingjie@42go.com>

Closes #2648 from yingjieMiao/rdd_take and squashes the following commits:

d758218 [yingjieMiao] scala style fix
a8e74bb [yingjieMiao] python style fix
4b6e777 [yingjieMiao] infix operator style fix
4391d3b [yingjieMiao] typo fix.
692f4e6 [yingjieMiao] cap numPartsToTry
c4483dc [yingjieMiao] style fix
1d2c410 [yingjieMiao] also change in rdd.py and AsyncRDD
d31ff7e [yingjieMiao] handle the edge case after 1 iteration
a2aa36b [yingjieMiao] RDD take method: overestimate too much
[SPARK-3892][SQL] remove redundant type name

Author: Daoyuan Wang <daoyuan.wang@intel.com>

Closes #2747 from adrian-wang/typename and squashes the following commits:

2824216 [Daoyuan Wang] remove redundant typeName
fbaf340 [Daoyuan Wang] typename
[SPARK-3407][SQL]Add Date type support

Author: Daoyuan Wang <daoyuan.wang@intel.com>

Closes #2344 from adrian-wang/date and squashes the following commits:

f15074a [Daoyuan Wang] remove outdated lines
2038085 [Daoyuan Wang] update return type
00fe81f [Daoyuan Wang] address lian cheng's comments
0df6ea1 [Daoyuan Wang] rebase and remove simple string
bb1b1ef [Daoyuan Wang] remove failing test
aa96735 [Daoyuan Wang] not cast for same type compare
30bf48b [Daoyuan Wang] resolve rebase conflict
617d1a8 [Daoyuan Wang] add date_udf case to white list
c37e848 [Daoyuan Wang] comment update
5429212 [Daoyuan Wang] change to long
f8f219f [Daoyuan Wang] revise according to Cheng Hao
0e0a4f5 [Daoyuan Wang] minor format
4ddcb92 [Daoyuan Wang] add java api for date
0e3110e [Daoyuan Wang] try to fix timezone issue
17fda35 [Daoyuan Wang] set test list
2dfbb5b [Daoyuan Wang] support date type
[SPARK-2066][SQL] Adds checks for non-aggregate attributes with aggregation

This PR adds a new rule `CheckAggregation` to the analyzer to provide better error message for non-aggregate attributes with aggregation.

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #2774 from liancheng/non-aggregate-attr and squashes the following commits:

5246004 [Cheng Lian] Passes test suites
bf1878d [Cheng Lian] Adds checks for non-aggregate attributes with aggregation
[SPARK-3529] [SQL] Delete the temp files after test exit

There are lots of temporal files created by TestHive under the /tmp by default, which may cause potential performance issue for testing. This PR will automatically delete them after test exit.

Author: Cheng Hao <hao.cheng@intel.com>

Closes #2393 from chenghao-intel/delete_temp_on_exit and squashes the following commits:

3a6511f [Cheng Hao] Remove the temp dir after text exit
[SPARK-3771][SQL] AppendingParquetOutputFormat should use reflection to prevent from breaking binary-compatibility.

Original problem is [SPARK-3764](https://issues.apache.org/jira/browse/SPARK-3764).

`AppendingParquetOutputFormat` uses a binary-incompatible method `context.getTaskAttemptID`.
This causes binary-incompatible of Spark itself, i.e. if Spark itself is built against hadoop-1, the artifact is for only hadoop-1, and vice versa.

Author: Takuya UESHIN <ueshin@happy-camper.st>

Closes #2638 from ueshin/issues/SPARK-3771 and squashes the following commits:

efd3784 [Takuya UESHIN] Add a comment to explain the reason to use reflection.
ec213c1 [Takuya UESHIN] Use reflection to prevent breaking binary-compatibility.
[SPARK-3559][SQL] Remove unnecessary columns from List of needed Column Ids in Hive Conf

Author: Venkata Ramana G <ramana.gollamudihuawei.com>

Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>

Closes #2713 from gvramana/remove_unnecessary_columns and squashes the following commits:

b7ba768 [Venkata Ramana Gollamudi] Added comment and checkstyle fix
6a93459 [Venkata Ramana Gollamudi] cloned hiveconf for each TableScanOperators so that only required columns are added
[SQL] Add type checking debugging functions

Adds some functions that were very useful when trying to track down the bug from #2656.  This change also changes the tree output for query plans to include the `'` prefix to unresolved nodes and `!` prefix to nodes that refer to non-existent attributes.

Author: Michael Armbrust <michael@databricks.com>

Closes #2657 from marmbrus/debugging and squashes the following commits:

654b926 [Michael Armbrust] Clean-up, add tests
763af15 [Michael Armbrust] Add typeChecking debugging functions
8c69303 [Michael Armbrust] Add inputSet, references to QueryPlan. Improve tree string with a prefix to denote invalid or unresolved nodes.
fbeab54 [Michael Armbrust] Better toString, factories for AttributeSet.
SPARK-3807: SparkSql does not work for tables created using custom serde

SparkSql crashes on selecting tables using custom serde.

Example:
----------------

CREATE EXTERNAL TABLE table_name PARTITIONED BY ( a int) ROW FORMAT 'SERDE "org.apache.hadoop.hive.serde2.thrift.ThriftDeserializer" with serdeproperties("serialization.format"="org.apache.thrift.protocol.TBinaryProtocol","serialization.class"="ser_class") STORED AS SEQUENCEFILE;

The following exception is seen on running a query like 'select * from table_name limit 1':

ERROR CliDriver: org.apache.hadoop.hive.serde2.SerDeException: java.lang.NullPointerException
at org.apache.hadoop.hive.serde2.thrift.ThriftDeserializer.initialize(ThriftDeserializer.java:68)
at org.apache.hadoop.hive.ql.plan.TableDesc.getDeserializer(TableDesc.java:80)
at org.apache.spark.sql.hive.execution.HiveTableScan.addColumnMetadataToConf(HiveTableScan.scala:86)
at org.apache.spark.sql.hive.execution.HiveTableScan.<init>(HiveTableScan.scala:100)
at org.apache.spark.sql.hive.HiveStrategies$HiveTableScans$$anonfun$14.apply(HiveStrategies.scala:188)
at org.apache.spark.sql.hive.HiveStrategies$HiveTableScans$$anonfun$14.apply(HiveStrategies.scala:188)
at org.apache.spark.sql.SQLContext$SparkPlanner.pruneFilterProject(SQLContext.scala:364)
at org.apache.spark.sql.hive.HiveStrategies$HiveTableScans$.apply(HiveStrategies.scala:184)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at org.apache.spark.sql.catalyst.planning.QueryPlanner.apply(QueryPlanner.scala:59)
at org.apache.spark.sql.catalyst.planning.QueryPlanner.planLater(QueryPlanner.scala:54)
at org.apache.spark.sql.execution.SparkStrategies$BasicOperators$.apply(SparkStrategies.scala:280)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
at org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:58)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at org.apache.spark.sql.catalyst.planning.QueryPlanner.apply(QueryPlanner.scala:59)
at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:402)
at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:400)
at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:406)
at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:406)
at org.apache.spark.sql.hive.HiveContext$QueryExecution.stringResult(HiveContext.scala:406)
at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:59)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:291)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:413)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:226)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:328)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.NullPointerException

Author: chirag <chirag.aggarwal@guavus.com>

Closes #2674 from chiragaggarwal/branch-1.1 and squashes the following commits:

370c31b [chirag] SPARK-3807: Add a test case to validate the fix.
1f26805 [chirag] SPARK-3807: SparkSql does not work for tables created using custom serde (Incorporated Review Comments)
ba4bc0c [chirag] SPARK-3807: SparkSql does not work for tables created using custom serde
5c73b72 [chirag] SPARK-3807: SparkSql does not work for tables created using custom serde

(cherry picked from commit 925e22d3132b983a2fcee31e3878b680c7ff92da)
Signed-off-by: Michael Armbrust <michael@databricks.com>
[SQL]Small bug in unresolved.scala

name should throw exception with name instead of exprId.

Author: Liquan Pei <liquanpei@gmail.com>

Closes #2758 from Ishiihara/SparkSQL-bug and squashes the following commits:

aa36a3b [Liquan Pei] small bug
[SPARK-3809][SQL] Fixes test suites in hive-thriftserver

As scwf pointed out, `HiveThriftServer2Suite` isn't effective anymore after the Thrift server was made a daemon. On the other hand, these test suites were known flaky, PR #2214 tried to fix them but failed because of unknown Jenkins build error. This PR fixes both sets of issues.

In this PR, instead of watching `start-thriftserver.sh` output, the test code start a `tail` process to watch the log file. A `Thread.sleep` has to be introduced because the `kill` command used in `stop-thriftserver.sh` is not synchronous.

As for the root cause of the mysterious Jenkins build failure. Please refer to [this comment](https://github.com/apache/spark/pull/2675#issuecomment-58464189) below for details.

----

(Copied from PR description of #2214)

This PR fixes two issues of `HiveThriftServer2Suite` and brings 1 enhancement:

1. Although metastore, warehouse directories and listening port are randomly chosen, all test cases share the same configuration. Due to parallel test execution, one of the two test case is doomed to fail
2. We caught any exceptions thrown from a test case and print diagnosis information, but forgot to re-throw the exception...
3. When the forked server process ends prematurely (e.g., fails to start), the `serverRunning` promise is completed with a failure, preventing the test code to keep waiting until timeout.

So, embarrassingly, this test suite was failing continuously for several days but no one had ever noticed it... Fortunately no bugs in the production code were covered under the hood.

Author: Cheng Lian <lian.cs.zju@gmail.com>
Author: wangfei <wangfei1@huawei.com>

Closes #2675 from liancheng/fix-thriftserver-tests and squashes the following commits:

1c384b7 [Cheng Lian] Minor code cleanup, restore the logging level hack in TestHive.scala
7805c33 [wangfei]  reset SPARK_TESTING to avoid loading Log4J configurations in testing class paths
af2b5a9 [Cheng Lian] Removes log level hacks from TestHiveContext
d116405 [wangfei] make sure that log4j level is INFO
ee92a82 [Cheng Lian] Relaxes timeout
7fd6757 [Cheng Lian] Fixes test suites in hive-thriftserver
[SPARK-3912][Streaming] Fixed flakyFlumeStreamSuite

@harishreedharan @pwendell
See JIRA for diagnosis of the problem
https://issues.apache.org/jira/browse/SPARK-3912

The solution was to reimplement it.
1. Find a free port (by binding and releasing a server-scoket), and then use that port
2. Remove thread.sleep()s, instead repeatedly try to create a sender and send data and check whether data was sent. Use eventually() to minimize waiting time.
3. Check whether all the data was received, without caring about batches.

Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #2773 from tdas/flume-test-fix and squashes the following commits:

93cd7f6 [Tathagata Das] Reimplimented FlumeStreamSuite to be more robust.
[SPARK-3921] Fix CoarseGrainedExecutorBackend's arguments for Standalone mode

The goal of this patch is to fix the swapped arguments in standalone mode, which was caused by  https://github.com/apache/spark/commit/79e45c9323455a51f25ed9acd0edd8682b4bbb88#diff-79391110e9f26657e415aa169a004998R153.

More details can be found in the JIRA: [SPARK-3921](https://issues.apache.org/jira/browse/SPARK-3921)

Tested in Standalone mode, but not in Mesos.

Author: Aaron Davidson <aaron@databricks.com>

Closes #2779 from aarondav/fix-standalone and squashes the following commits:

725227a [Aaron Davidson] Fix ExecutorRunnerTest
9d703fe [Aaron Davidson] [SPARK-3921] Fix CoarseGrainedExecutorBackend's arguments for Standalone mode
SPARK-3178  setting SPARK_WORKER_MEMORY to a value without a label (m or g) sets the worker memory limit to zero

Validate the memory is greater than zero when set from the SPARK_WORKER_MEMORY environment variable or command line without a g or m label.  Added unit tests. If memory is 0 an IllegalStateException is thrown. Updated unit tests to mock environment variables by subclassing SparkConf (tip provided by Josh Rosen).   Updated WorkerArguments to use SparkConf.getenv instead of System.getenv for reading the SPARK_WORKER_MEMORY environment variable.

Author: Bill Bejeck <bbejeck@gmail.com>

Closes #2309 from bbejeck/spark-memory-worker and squashes the following commits:

51cf915 [Bill Bejeck] SPARK-3178 - Validate the memory is greater than zero when set from the SPARK_WORKER_MEMORY environment variable or command line without a g or m label.  Added unit tests. If memory is 0 an IllegalStateException is thrown. Updated unit tests to mock environment variables by subclassing SparkConf (tip provided by Josh Rosen).   Updated WorkerArguments to use SparkConf.getenv instead of System.getenv for reading the SPARK_WORKER_MEMORY environment variable.