This patch removes `spark.driver.allowMultipleContexts=true` from our test configuration. The multiple SparkContexts check was originally disabled because certain tests suites in SQL needed to create multiple contexts. As far as I know, this configuration change is no longer necessary, so we should remove it in order to make it easier to find test cleanup bugs.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #9865 from JoshRosen/SPARK-4424.

[SPARK-4557][STREAMING] Spark Streaming foreachRDD Java API method should accept a VoidFunction<...>

Currently streaming foreachRDD Java API uses a function prototype requiring a return value of null.  This PR deprecates the old method and uses VoidFunction to allow for more concise declaration.  Also added VoidFunction2 to Java API in order to use in Streaming methods.  Unit test is added for using foreachRDD with VoidFunction, and changes have been tested with Java 7 and Java 8 using lambdas.

Author: Bryan Cutler <bjcutler@us.ibm.com>

Closes #9488 from BryanCutler/foreachRDD-VoidFunction-SPARK-4557.

Fixed the merge conflicts in #7410

Closes #7410

Author: Shixiong Zhu <shixiong@databricks.com>
Author: jerryshao <saisai.shao@intel.com>
Author: jerryshao <sshao@hortonworks.com>

Closes #9742 from zsxwing/pr7410.

This adds an extra filter for private or protected classes. We only filter for package private right now.

Author: Timothy Hunter <timhunter@databricks.com>

Closes #9697 from thunterdb/spark-11732.

This is to support JSON serialization of Param[Vector] in the pipeline API. It could be used for other purposes too. The schema is the same as `VectorUDT`. jkbradley

Author: Xiangrui Meng <meng@databricks.com>

Closes #9751 from mengxr/SPARK-11766.

Remove some old yarn related building codes, please review, thanks a lot.

Author: jerryshao <sshao@hortonworks.com>

Closes #9625 from jerryshao/remove-old-module.

This patch modifies Spark's closure cleaner (and a few other places) to use ASM 5, which is necessary in order to support cleaning of closures that were compiled by Java 8.

In order to avoid ASM dependency conflicts, Spark excludes ASM from all of its dependencies and uses a shaded version of ASM 4 that comes from `reflectasm` (see [SPARK-782](https://issues.apache.org/jira/browse/SPARK-782) and #232). This patch updates Spark to use a shaded version of ASM 5.0.4 that was published by the Apache XBean project; the POM used to create the shaded artifact can be found at https://github.com/apache/geronimo-xbean/blob/xbean-4.4/xbean-asm5-shaded/pom.xml.

http://movingfulcrum.tumblr.com/post/80826553604/asm-framework-50-the-missing-migration-guide was a useful resource while upgrading the code to use the new ASM5 opcodes.

I also added a new regression tests in the `java8-tests` subproject; the existing tests were insufficient to catch this bug, which only affected Scala 2.11 user code which was compiled targeting Java 8.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #9512 from JoshRosen/SPARK-6152.

This patch re-enables tests for the Docker JDBC data source. These tests were reverted in #4872 due to transitive dependency conflicts introduced by the `docker-client` library. This patch should avoid those problems by using a version of `docker-client` which shades its transitive dependencies and by performing some build-magic to work around problems with that shaded JAR.

In addition, I significantly refactored the tests to simplify the setup and teardown code and to fix several Docker networking issues which caused problems when running in `boot2docker`.

Closes #8101.

Author: Josh Rosen <joshrosen@databricks.com>
Author: Yijie Shen <henry.yijieshen@gmail.com>

Closes #9503 from JoshRosen/docker-jdbc-tests.

This patch modifies Spark's SBT build so that it no longer uses `retrieveManaged` / `lib_managed` to store its dependencies. The motivations for this change are nicely described on the JIRA ticket ([SPARK-7841](https://issues.apache.org/jira/browse/SPARK-7841)); my personal interest in doing this stems from the fact that `lib_managed` has caused me some pain while debugging dependency issues in another PR of mine.

Removing our use of `lib_managed` would be trivial except for one snag: the Datanucleus JARs, required by Spark SQL's Hive integration, cannot be included in assembly JARs due to problems with merging OSGI `plugin.xml` files. As a result, several places in the packaging and deployment pipeline assume that these Datanucleus JARs are copied to `lib_managed/jars`. In the interest of maintaining compatibility, I have chosen to retain the `lib_managed/jars` directory _only_ for these Datanucleus JARs and have added custom code to `SparkBuild.scala` to automatically copy those JARs to that folder as part of the `assembly` task.

`dev/mima` also depended on `lib_managed` in a hacky way in order to set classpaths when generating MiMa excludes; I've updated this to obtain the classpaths directly from SBT instead.

/cc dragos marmbrus pwendell srowen

Author: Josh Rosen <joshrosen@databricks.com>

Closes #9575 from JoshRosen/SPARK-7841.

I looked at the other endpoints, and they don't seem to be missing any fields.
Added fields:
![image](https://cloud.githubusercontent.com/assets/613879/10948801/58159982-82e4-11e5-86dc-62da201af910.png)

Author: Charles Yeh <charlesyeh@dropbox.com>

Closes #9472 from CharlesYeh/api_vars.

[SPARK-11541][SQL] Break JdbcDialects.scala into multiple files and mark various dialects as private.

Author: Reynold Xin <rxin@databricks.com>

Closes #9511 from rxin/SPARK-11541.

sbt's version resolution code always picks the most recent version, and we
don't want that for guava.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #9508 from vanzin/SPARK-11538.

This reverts commit 9cf56c96.

Spark should build against Scala 2.10.5, since that includes a fix for Scaladoc that will fix doc snapshot publishing: https://issues.scala-lang.org/browse/SI-8479

Author: Josh Rosen <joshrosen@databricks.com>

Closes #9450 from JoshRosen/upgrade-to-scala-2.10.5.

These two classes should be public, since they are used in public code.

Author: Reynold Xin <rxin@databricks.com>

Closes #9445 from rxin/SPARK-11485.

Like ml ```LinearRegression```, ```LogisticRegression``` should provide a training summary including feature names and their coefficients.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #9303 from yanboliang/spark-9492.

This is the first task (https://issues.apache.org/jira/browse/SPARK-11469) of https://issues.apache.org/jira/browse/SPARK-11438

Author: Yin Huai <yhuai@databricks.com>

Closes #9393 from yhuai/udfNondeterministic.

Since we do not need to preserve a page before calling compute(), MapPartitionsWithPreparationRDD is not needed anymore.

This PR basically revert #8543, #8511, #8038, #8011

Author: Davies Liu <davies@databricks.com>

Closes #9381 from davies/remove_prepare2.

There's a lot of duplication between SortShuffleManager and UnsafeShuffleManager. Given that these now provide the same set of functionality, now that UnsafeShuffleManager supports large records, I think that we should replace SortShuffleManager's serialized shuffle implementation with UnsafeShuffleManager's and should merge the two managers together.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #8829 from JoshRosen/consolidate-sort-shuffle-implementations.

…redNodeLocationData

Author: Jacek Laskowski <jacek.laskowski@deepsense.io>

Closes #8976 from jaceklaskowski/SPARK-10921.

Shows that an error is actually due to a fatal warning.

Author: Jakob Odersky <jodersky@gmail.com>

Closes #9128 from jodersky/fatalwarnings.

Modify the SBT build script to include GitHub source links for generated Scaladocs, on releases only (no snapshots).

Author: Jakob Odersky <jodersky@gmail.com>

Closes #9110 from jodersky/unidoc.

This PR improve the sessions management by replacing the thread-local based to one SQLContext per session approach, introduce separated temporary tables and UDFs/UDAFs for each session.

A new session of SQLContext could be created by:

1) create an new SQLContext
2) call newSession() on existing SQLContext

For HiveContext, in order to reduce the cost for each session, the classloader and Hive client are shared across multiple sessions (created by newSession).

CacheManager is also shared by multiple sessions, so cache a table multiple times in different sessions will not cause multiple copies of in-memory cache.

Added jars are still shared by all the sessions, because SparkContext does not support sessions.

cc marmbrus yhuai rxin

Author: Davies Liu <davies@databricks.com>

Closes #8909 from davies/sessions.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #8775 from vanzin/SPARK-10300.

This PR remove the typeId in columnar cache, it's not needed anymore, it also remove DATE and TIMESTAMP (use INT/LONG instead).

Author: Davies Liu <davies@databricks.com>

Closes #8989 from davies/refactor_cache.

In many modeling application, data points are not necessarily sampled with equal probabilities. Linear regression should support weighting which account the over or under sampling.

work in progress.

Author: Meihua Wu <meihuawu@umich.edu>

Closes #8631 from rotationsymmetry/SPARK-9642.

Author: Reynold Xin <rxin@databricks.com>

Closes #8812 from rxin/SPARK-9808-1.

When speculative execution is enabled, consider a scenario where the authorized committer of a particular output partition fails during the OutputCommitter.commitTask() call. In this case, the OutputCommitCoordinator is supposed to release that committer's exclusive lock on committing once that task fails. However, due to a unit mismatch (we used task attempt number in one place and task attempt id in another) the lock will not be released, causing Spark to go into an infinite retry loop.

This bug was masked by the fact that the OutputCommitCoordinator does not have enough end-to-end tests (the current tests use many mocks). Other factors contributing to this bug are the fact that we have many similarly-named identifiers that have different semantics but the same data types (e.g. attemptNumber and taskAttemptId, with inconsistent variable naming which makes them difficult to distinguish).

This patch adds a regression test and fixes this bug by always using task attempt numbers throughout this code.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #8544 from JoshRosen/SPARK-10381.

In fraud detection dataset, almost all the samples are negative while only couple of them are positive. This type of high imbalanced data will bias the models toward negative resulting poor performance. In python-scikit, they provide a correction allowing users to Over-/undersample the samples of each class according to the given weights. In auto mode, selects weights inversely proportional to class frequencies in the training set. This can be done in a more efficient way by multiplying the weights into loss and gradient instead of doing actual over/undersampling in the training dataset which is very expensive.
http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html
On the other hand, some of the training data maybe more important like the training samples from tenure users while the training samples from new users maybe less important. We should be able to provide another "weight: Double" information in the LabeledPoint to weight them differently in the learning algorithm.

Author: DB Tsai <dbt@netflix.com>
Author: DB Tsai <dbt@dbs-mac-pro.corp.netflix.com>

Closes #7884 from dbtsai/SPARK-7685.

This reverts commit 8abef21d.

This change does two things:

- tag a few tests and adds the mechanism in the build to be able to disable those tags,
  both in maven and sbt, for both junit and scalatest suites.
- add some logic to run-tests.py to disable some tags depending on what files have
  changed; that's used to disable expensive tests when a module hasn't explicitly
  been changed, to speed up testing for changes that don't directly affect those
  modules.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #8437 from vanzin/test-tags.

Author: Reynold Xin <rxin@databricks.com>

Closes #8350 from rxin/1.6.

Previously, project/plugins.sbt explicitly set scalaVersion to 2.10.4. This can cause issues when using a version of sbt that is compiled against a different version of Scala (for example sbt 0.13.9 uses 2.10.5). Removing this explicit setting will cause build files to be compiled and run against the same version of Scala that sbt is compiled against.

Note that this only applies to the project build files (items in project/), it is distinct from the version of Scala we target for the actual spark compilation.

Author: Ahir Reddy <ahirreddy@gmail.com>

Closes #8709 from ahirreddy/sbt-scala-version-fix.

We introduced the Netty network module for shuffle in Spark 1.2, and has turned it on by default for 3 releases. The old ConnectionManager is difficult to maintain. If we merge the patch now, by the time it is released, it would be 1 yr for which ConnectionManager is off by default. It's time to remove it.

Author: Reynold Xin <rxin@databricks.com>

Closes #8161 from rxin/SPARK-9767.

To correctly isolate applications, when requests to read shuffle data
arrive at the shuffle service, proper authorization checks need to
be performed. This change makes sure that only the application that
created the shuffle data can read from it.

Such checks are only enabled when "spark.authenticate" is enabled,
otherwise there's no secure way to make sure that the client is really
who it says it is.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #8218 from vanzin/SPARK-10004.

This change aims at speeding up the dev cycle a little bit, by making
sure that all tests behave the same w.r.t. where the code to be tested
is loaded from. Namely, that means that tests don't rely on the assembly
anymore, rather loading all needed classes from the build directories.

The main change is to make sure all build directories (classes and test-classes)
are added to the classpath of child processes when running tests.

YarnClusterSuite required some custom code since the executors are run
differently (i.e. not through the launcher library, like standalone and
Mesos do).

I also found a couple of tests that could leak a SparkContext on failure,
and added code to handle those.

With this patch, it's possible to run the following command from a clean
source directory and have all tests pass:

  mvn -Pyarn -Phadoop-2.4 -Phive-thriftserver install

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #7629 from vanzin/SPARK-9284.

Replace `JavaConversions` implicits with `JavaConverters`

Most occurrences I've seen so far are necessary conversions; a few have been avoidable. None are in critical code as far as I see, yet.

Author: Sean Owen <sowen@cloudera.com>

Closes #8033 from srowen/SPARK-9613.

A fundamental limitation of the existing SQL tests is that *there is simply no way to create your own `SparkContext`*. This is a serious limitation because the user may wish to use a different master or config. As a case in point, `BroadcastJoinSuite` is entirely commented out because there is no way to make it pass with the existing infrastructure.

This patch removes the singletons `TestSQLContext` and `TestData`, and instead introduces a `SharedSQLContext` that starts a context per suite. Unfortunately the singletons were so ingrained in the SQL tests that this patch necessarily needed to touch *all* the SQL test files.

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Author: Andrew Or <andrew@databricks.com>

Closes #8111 from andrewor14/sql-tests-refactor.

Made ProbabilisticClassifier, Identifiable, VectorUDT public.  All are annotated as DeveloperApi.

CC: mengxr EronWright

Author: Joseph K. Bradley <joseph@databricks.com>

Closes #8004 from jkbradley/ml-api-public-items and squashes the following commits:

7ebefda [Joseph K. Bradley] update per code review
7ff0768 [Joseph K. Bradley] attepting to add mima fix
756d84c [Joseph K. Bradley] VectorUDT annotated as AlphaComponent
ae7767d [Joseph K. Bradley] added another warning
94fd553 [Joseph K. Bradley] Made ProbabilisticClassifier, Identifiable, VectorUDT public APIs

The REST server is not actually used in most tests and so we can disable it. It is a source of flakiness because it tries to bind to a specific port in vain. There was also some code that avoided the shuffle service in tests. This is actually not necessary because the shuffle service is already off by default.

Author: Andrew Or <andrew@databricks.com>

Closes #8084 from andrewor14/fix-master-suite-again.