Fix SparkR package copy regex. The existing code leads to
```
Copying release tarballs to /home/****/public_html/spark-nightly/spark-branch-2.1-bin/spark-2.1.1-SNAPSHOT-2016_12_08_22_38-e8f351f-bin
mput: SparkR-*: no files found
```
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#16231 from shivaram/typo-sparkr-build.
## What changes were proposed in this pull request?
Copy pyspark and SparkR packages to latest release dir, as per comment [here](https://github.com/apache/spark/pull/16226#discussion_r91664822)
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#16227 from felixcheung/pyrftp.
This PR adds a line in release-build.sh to copy the SparkR source archive using LFTP
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#16226 from shivaram/fix-sparkr-copy-build.
## What changes were proposed in this pull request?
Fixes name of R source package so that the `cp` in release-build.sh works correctly.
Issue discussed in https://github.com/apache/spark/pull/16014#issuecomment-265867125
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#16221 from shivaram/fix-sparkr-release-build-name.
This PR changes the SparkR source release tarball to be built using the Hadoop 2.6 profile. Previously it was using the without hadoop profile which leads to an error as discussed in https://github.com/apache/spark/pull/16014#issuecomment-265843991
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#16218 from shivaram/fix-sparkr-release-build.
## What changes were proposed in this pull request?
This PR has 2 key changes. One, we are building source package (aka bundle package) for SparkR which could be released on CRAN. Two, we should include in the official Spark binary distributions SparkR installed from this source package instead (which would have help/vignettes rds needed for those to work when the SparkR package is loaded in R, whereas earlier approach with devtools does not)
But, because of various differences in how R performs different tasks, this PR is a fair bit more complicated. More details below.
This PR also includes a few minor fixes.
### more details
These are the additional steps in make-distribution; please see [here](https://github.com/apache/spark/blob/master/R/CRAN_RELEASE.md) on what's going to a CRAN release, which is now run during make-distribution.sh.
1. package needs to be installed because the first code block in vignettes is `library(SparkR)` without lib path
2. `R CMD build` will build vignettes (this process runs Spark/SparkR code and captures outputs into pdf documentation)
3. `R CMD check` on the source package will install package and build vignettes again (this time from source packaged) - this is a key step required to release R package on CRAN
(will skip tests here but tests will need to pass for CRAN release process to success - ideally, during release signoff we should install from the R source package and run tests)
4. `R CMD Install` on the source package (this is the only way to generate doc/vignettes rds files correctly, not in step # 1)
(the output of this step is what we package into Spark dist and sparkr.zip)
Alternatively,
R CMD build should already be installing the package in a temp directory though it might just be finding this location and set it to lib.loc parameter; another approach is perhaps we could try calling `R CMD INSTALL --build pkg` instead.
But in any case, despite installing the package multiple times this is relatively fast.
Building vignettes takes a while though.
## How was this patch tested?
Manually, CI.
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#16014 from felixcheung/rdist.
## What changes were proposed in this pull request?
To be able to restart StreamingQueries across Spark version, we have already made the logs (offset log, file source log, file sink log) use json. We should added tests with actual json files in the Spark such that any incompatible changes in reading the logs is immediately caught. This PR add tests for FileStreamSourceLog, FileStreamSinkLog, and OffsetSeqLog.
## How was this patch tested?
new unit tests
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#16128 from tdas/SPARK-18671.
## What changes were proposed in this pull request?
Force update to latest Netty 3.9.x, for dependencies like Flume, to resolve two CVEs. 3.9.2 is the first version that resolves both, and, this is the latest in the 3.9.x line.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#16102 from srowen/SPARK-18586.
## What changes were proposed in this pull request?
We current build 5 separate pip binary tar balls, doubling the release script runtime. It'd be better to build one, especially for use cases that are just using Spark locally. In the long run, it would make more sense to have Hadoop support be pluggable.
## How was this patch tested?
N/A - this is a release build script that doesn't have any automated test coverage. We will know if it goes wrong when we prepare releases.
Author: Reynold Xin <rxin@databricks.com>
Closes#16072 from rxin/SPARK-18639.
## What changes were proposed in this pull request?
org.codehaus.janino:janino depends on org.codehaus.janino:commons-compiler and we have been upgraded to org.codehaus.janino:janino 3.0.0.
However, seems we are still pulling in org.codehaus.janino:commons-compiler 2.7.6 because of calcite. It looks like an accident because we exclude janino from calcite (see here https://github.com/apache/spark/blob/branch-2.1/pom.xml#L1759). So, this PR upgrades org.codehaus.janino:commons-compiler to 3.0.0.
## How was this patch tested?
jenkins
Author: Yin Huai <yhuai@databricks.com>
Closes#16025 from yhuai/janino-commons-compile.
## What changes were proposed in this pull request?
Updates links to the wiki to links to the new location of content on spark.apache.org.
## How was this patch tested?
Doc builds
Author: Sean Owen <sowen@cloudera.com>
Closes#15967 from srowen/SPARK-18073.1.
## What changes were proposed in this pull request?
This PR aims to provide a pip installable PySpark package. This does a bunch of work to copy the jars over and package them with the Python code (to prevent challenges from trying to use different versions of the Python code with different versions of the JAR). It does not currently publish to PyPI but that is the natural follow up (SPARK-18129).
Done:
- pip installable on conda [manual tested]
- setup.py installed on a non-pip managed system (RHEL) with YARN [manual tested]
- Automated testing of this (virtualenv)
- packaging and signing with release-build*
Possible follow up work:
- release-build update to publish to PyPI (SPARK-18128)
- figure out who owns the pyspark package name on prod PyPI (is it someone with in the project or should we ask PyPI or should we choose a different name to publish with like ApachePySpark?)
- Windows support and or testing ( SPARK-18136 )
- investigate details of wheel caching and see if we can avoid cleaning the wheel cache during our test
- consider how we want to number our dev/snapshot versions
Explicitly out of scope:
- Using pip installed PySpark to start a standalone cluster
- Using pip installed PySpark for non-Python Spark programs
*I've done some work to test release-build locally but as a non-committer I've just done local testing.
## How was this patch tested?
Automated testing with virtualenv, manual testing with conda, a system wide install, and YARN integration.
release-build changes tested locally as a non-committer (no testing of upload artifacts to Apache staging websites)
Author: Holden Karau <holden@us.ibm.com>
Author: Juliet Hougland <juliet@cloudera.com>
Author: Juliet Hougland <not@myemail.com>
Closes#15659 from holdenk/SPARK-1267-pip-install-pyspark.
## What changes were proposed in this pull request?
Small fix, fix the errors caused by lint check in Java
- Clear unused objects and `UnusedImports`.
- Add comments around the method `finalize` of `NioBufferedFileInputStream`to turn off checkstyle.
- Cut the line which is longer than 100 characters into two lines.
## How was this patch tested?
Travis CI.
```
$ build/mvn -T 4 -q -DskipTests -Pyarn -Phadoop-2.3 -Pkinesis-asl -Phive -Phive-thriftserver install
$ dev/lint-java
```
Before:
```
Checkstyle checks failed at following occurrences:
[ERROR] src/main/java/org/apache/spark/network/util/TransportConf.java:[21,8] (imports) UnusedImports: Unused import - org.apache.commons.crypto.cipher.CryptoCipherFactory.
[ERROR] src/test/java/org/apache/spark/network/sasl/SparkSaslSuite.java:[516,5] (modifier) RedundantModifier: Redundant 'public' modifier.
[ERROR] src/main/java/org/apache/spark/io/NioBufferedFileInputStream.java:[133] (coding) NoFinalizer: Avoid using finalizer method.
[ERROR] src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeMapData.java:[71] (sizes) LineLength: Line is longer than 100 characters (found 113).
[ERROR] src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeArrayData.java:[112] (sizes) LineLength: Line is longer than 100 characters (found 110).
[ERROR] src/test/java/org/apache/spark/sql/catalyst/expressions/HiveHasherSuite.java:[31,17] (modifier) ModifierOrder: 'static' modifier out of order with the JLS suggestions.
[ERROR]src/main/java/org/apache/spark/examples/ml/JavaLogisticRegressionWithElasticNetExample.java:[64] (sizes) LineLength: Line is longer than 100 characters (found 103).
[ERROR] src/main/java/org/apache/spark/examples/ml/JavaInteractionExample.java:[22,8] (imports) UnusedImports: Unused import - org.apache.spark.ml.linalg.Vectors.
[ERROR] src/main/java/org/apache/spark/examples/ml/JavaInteractionExample.java:[51] (regexp) RegexpSingleline: No trailing whitespace allowed.
```
After:
```
$ build/mvn -T 4 -q -DskipTests -Pyarn -Phadoop-2.3 -Pkinesis-asl -Phive -Phive-thriftserver install
$ dev/lint-java
Using `mvn` from path: /home/travis/build/ConeyLiu/spark/build/apache-maven-3.3.9/bin/mvn
Checkstyle checks passed.
```
Author: Xianyang Liu <xyliu0530@icloud.com>
Closes#15865 from ConeyLiu/master.
## What changes were proposed in this pull request?
Fix the flags used to specify the hadoop version
## How was this patch tested?
Manually tested as part of https://github.com/apache/spark/pull/15659 by having the build succeed.
cc joshrosen
Author: Holden Karau <holden@us.ibm.com>
Closes#15860 from holdenk/minor-fix-release-build-script.
## What changes were proposed in this pull request?
One of the important changes for 4.0.42.Final is "Support any FileRegion implementation when using epoll transport netty/netty#5825".
In 4.0.42.Final, `MessageWithHeader` can work properly when `spark.[shuffle|rpc].io.mode` is set to epoll
## How was this patch tested?
Existing tests
Author: Guoqiang Li <witgo@qq.com>
Closes#15830 from witgo/SPARK-18375_netty-4.0.42.
## What changes were proposed in this pull request?
Try excluding org.json:json from hive-exec dep as it's Cat X now. It may be the case that it's not used by the part of Hive Spark uses anyway.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#15798 from srowen/SPARK-18262.
## What changes were proposed in this pull request?
1) Upgrade the Py4J version on the Java side
2) Update the py4j src zip file we bundle with Spark
## How was this patch tested?
Existing doctests & unit tests pass
Author: Jagadeesan <as2@us.ibm.com>
Closes#15514 from jagadeesanas2/SPARK-17960.
## What changes were proposed in this pull request?
`SerializationUtils.clone()` of commons-lang3 (<3.5) has a bug that breaks thread safety, which gets stack sometimes caused by race condition of initializing hash map.
See https://issues.apache.org/jira/browse/LANG-1251.
## How was this patch tested?
Existing tests.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#15548 from ueshin/issues/SPARK-17985.
This reverts commit bfe7885aee.
The commit caused build failures on Hadoop 2.2 profile:
```
[error] /scratch/rxin/spark/core/src/main/scala/org/apache/spark/util/Utils.scala:1489: value read is not a member of object org.apache.commons.io.IOUtils
[error] var numBytes = IOUtils.read(gzInputStream, buf)
[error] ^
[error] /scratch/rxin/spark/core/src/main/scala/org/apache/spark/util/Utils.scala:1492: value read is not a member of object org.apache.commons.io.IOUtils
[error] numBytes = IOUtils.read(gzInputStream, buf)
[error] ^
```
## What changes were proposed in this pull request?
`SerializationUtils.clone()` of commons-lang3 (<3.5) has a bug that breaks thread safety, which gets stack sometimes caused by race condition of initializing hash map.
See https://issues.apache.org/jira/browse/LANG-1251.
## How was this patch tested?
Existing tests.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#15525 from ueshin/issues/SPARK-17985.
## What changes were proposed in this pull request?
Upgraded to a newer version of Pyrolite which supports serialization of a BinaryType StructField for PySpark.SQL
## How was this patch tested?
Added a unit test which fails with a raised ValueError when using the previous version of Pyrolite 4.9 and Python3
Author: Bryan Cutler <cutlerb@gmail.com>
Closes#15386 from BryanCutler/pyrolite-upgrade-SPARK-17808.
## What changes were proposed in this pull request?
This PR adds the Kafka 0.10 subproject to the build infrastructure. This makes sure Kafka 0.10 tests are only triggers when it or of its dependencies change.
Author: Herman van Hovell <hvanhovell@databricks.com>
Closes#15355 from hvanhovell/SPARK-17782.
## What changes were proposed in this pull request?
This PR adds a new project ` external/kafka-0-10-sql` for Structured Streaming Kafka source.
It's based on the design doc: https://docs.google.com/document/d/19t2rWe51x7tq2e5AOfrsM9qb8_m7BRuv9fel9i0PqR8/edit?usp=sharing
tdas did most of work and part of them was inspired by koeninger's work.
### Introduction
The Kafka source is a structured streaming data source to poll data from Kafka. The schema of reading data is as follows:
Column | Type
---- | ----
key | binary
value | binary
topic | string
partition | int
offset | long
timestamp | long
timestampType | int
The source can deal with deleting topics. However, the user should make sure there is no Spark job processing the data when deleting a topic.
### Configuration
The user can use `DataStreamReader.option` to set the following configurations.
Kafka Source's options | value | default | meaning
------ | ------- | ------ | -----
startingOffset | ["earliest", "latest"] | "latest" | The start point when a query is started, either "earliest" which is from the earliest offset, or "latest" which is just from the latest offset. Note: This only applies when a new Streaming query is started, and that resuming will always pick up from where the query left off.
failOnDataLost | [true, false] | true | Whether to fail the query when it's possible that data is lost (e.g., topics are deleted, or offsets are out of range). This may be a false alarm. You can disable it when it doesn't work as you expected.
subscribe | A comma-separated list of topics | (none) | The topic list to subscribe. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source.
subscribePattern | Java regex string | (none) | The pattern used to subscribe the topic. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source.
kafka.consumer.poll.timeoutMs | long | 512 | The timeout in milliseconds to poll data from Kafka in executors
fetchOffset.numRetries | int | 3 | Number of times to retry before giving up fatch Kafka latest offsets.
fetchOffset.retryIntervalMs | long | 10 | milliseconds to wait before retrying to fetch Kafka offsets
Kafka's own configurations can be set via `DataStreamReader.option` with `kafka.` prefix, e.g, `stream.option("kafka.bootstrap.servers", "host:port")`
### Usage
* Subscribe to 1 topic
```Scala
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "host:port")
.option("subscribe", "topic1")
.load()
```
* Subscribe to multiple topics
```Scala
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "host:port")
.option("subscribe", "topic1,topic2")
.load()
```
* Subscribe to a pattern
```Scala
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "host:port")
.option("subscribePattern", "topic.*")
.load()
```
## How was this patch tested?
The new unit tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Author: Tathagata Das <tathagata.das1565@gmail.com>
Author: Shixiong Zhu <zsxwing@gmail.com>
Author: cody koeninger <cody@koeninger.org>
Closes#15102 from zsxwing/kafka-source.
## What changes were proposed in this pull request?
This PR sets the R package version while tagging releases. Note that since R doesn't accept `-SNAPSHOT` in version number field, we remove that while setting the next version
## How was this patch tested?
Tested manually by running locally
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#15223 from shivaram/sparkr-version-change.
## What changes were proposed in this pull request?
This PR includes the changes below:
1. Upgrade Univocity library from 2.1.1 to 2.2.1
This includes some performance improvement and also enabling auto-extending buffer in `maxCharsPerColumn` option in CSV. Please refer the [release notes](https://github.com/uniVocity/univocity-parsers/releases).
2. Remove useless `rowSeparator` variable existing in `CSVOptions`
We have this unused variable in [CSVOptions.scala#L127](29952ed096/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVOptions.scala (L127)) but it seems possibly causing confusion that it actually does not care of `\r\n`. For example, we have an issue open about this, [SPARK-17227](https://issues.apache.org/jira/browse/SPARK-17227), describing this variable.
This variable is virtually not being used because we rely on `LineRecordReader` in Hadoop which deals with only both `\n` and `\r\n`.
3. Set the default value of `maxCharsPerColumn` to auto-expending.
We are setting 1000000 for the length of each column. It'd be more sensible we allow auto-expending rather than fixed length by default.
To make sure, using `-1` is being described in the release note, [2.2.0](https://github.com/uniVocity/univocity-parsers/releases/tag/v2.2.0).
## How was this patch tested?
N/A
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#15138 from HyukjinKwon/SPARK-17583.
## What changes were proposed in this pull request?
This patch bumps the Hadoop version in hadoop-2.7 profile from 2.7.2 to 2.7.3, which was recently released and contained a number of bug fixes.
## How was this patch tested?
The change should be covered by existing tests.
Author: Reynold Xin <rxin@databricks.com>
Closes#15115 from rxin/SPARK-17558.
## What changes were proposed in this pull request?
Upgrade netty-all to latest in the 4.0.x line which is 4.0.41, mentions several bug fixes and performance improvements we may find useful, see netty.io/news/2016/08/29/4-0-41-Final-4-1-5-Final.html. Initially tried to use 4.1.5 but noticed it's not backwards compatible.
## How was this patch tested?
Existing unit tests against branch-1.6 and branch-2.0 using IBM Java 8 on Intel, Power and Z architectures
Author: Adam Roberts <aroberts@uk.ibm.com>
Closes#14961 from a-roberts/netty.
## What changes were proposed in this pull request?
Upgrades the Snappy version to 1.1.2.6 from 1.1.2.4, release notes: https://github.com/xerial/snappy-java/blob/master/Milestone.md mention "Fix a bug in SnappyInputStream when reading compressed data that happened to have the same first byte with the stream magic header (#142)"
## How was this patch tested?
Existing unit tests using the latest IBM Java 8 on Intel, Power and Z architectures (little and big-endian)
Author: Adam Roberts <aroberts@uk.ibm.com>
Closes#14958 from a-roberts/master.
## What changes were proposed in this pull request?
Only build PRs with -Pyarn if YARN code was modified.
## How was this patch tested?
Jenkins tests (will look to verify whether -Pyarn was included in the PR builder for this one.)
Author: Sean Owen <sowen@cloudera.com>
Closes#14892 from srowen/SPARK-17329.
## What changes were proposed in this pull request?
add build_profile_flags entry to mesos build module
## How was this patch tested?
unit tests
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#14885 from mgummelt/mesos-profile.
This patch is using Apache Commons Crypto library to enable shuffle encryption support.
Author: Ferdinand Xu <cheng.a.xu@intel.com>
Author: kellyzly <kellyzly@126.com>
Closes#8880 from winningsix/SPARK-10771.
## What changes were proposed in this pull request?
Excludes the `spark-warehouse` directory from the Apache RAT checks that src/run-tests performs. `spark-warehouse` is created by some of the Spark SQL tests, as well as by `bin/spark-sql`.
## How was this patch tested?
Ran src/run-tests twice. The second time, the script failed because the first iteration
Made the change in this PR.
Ran src/run-tests a third time; RAT checks succeeded.
Author: frreiss <frreiss@us.ibm.com>
Closes#14870 from frreiss/fred-17303.
## What changes were proposed in this pull request?
Move Mesos code into a mvn module
## How was this patch tested?
unit tests
manually submitting a client mode and cluster mode job
spark/mesos integration test suite
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#14637 from mgummelt/mesos-module.
## What changes were proposed in this pull request?
Update to py4j 0.10.3 to enable JAVA_HOME support
## How was this patch tested?
Pyspark tests
Author: Sean Owen <sowen@cloudera.com>
Closes#14748 from srowen/SPARK-16781.
## What changes were proposed in this pull request?
Add a configurable token manager for Spark on running on yarn.
### Current Problems ###
1. Supported token provider is hard-coded, currently only hdfs, hbase and hive are supported and it is impossible for user to add new token provider without code changes.
2. Also this problem exits in timely token renewer and updater.
### Changes In This Proposal ###
In this proposal, to address the problems mentioned above and make the current code more cleaner and easier to understand, mainly has 3 changes:
1. Abstract a `ServiceTokenProvider` as well as `ServiceTokenRenewable` interface for token provider. Each service wants to communicate with Spark through token way needs to implement this interface.
2. Provide a `ConfigurableTokenManager` to manage all the register token providers, also token renewer and updater. Also this class offers the API for other modules to obtain tokens, get renewal interval and so on.
3. Implement 3 built-in token providers `HDFSTokenProvider`, `HiveTokenProvider` and `HBaseTokenProvider` to keep the same semantics as supported today. Whether to load in these built-in token providers is controlled by configuration "spark.yarn.security.tokens.${service}.enabled", by default for all the built-in token providers are loaded.
### Behavior Changes ###
For the end user there's no behavior change, we still use the same configuration `spark.yarn.security.tokens.${service}.enabled` to decide which token provider is enabled (hbase or hive).
For user implemented token provider (assume the name of token provider is "test") needs to add into this class should have two configurations:
1. `spark.yarn.security.tokens.test.enabled` to true
2. `spark.yarn.security.tokens.test.class` to the full qualified class name.
So we still keep the same semantics as current code while add one new configuration.
### Current Status ###
- [x] token provider interface and management framework.
- [x] implement built-in token providers (hdfs, hbase, hive).
- [x] Coverage of unit test.
- [x] Integrated test with security cluster.
## How was this patch tested?
Unit test and integrated test.
Please suggest and review, any comment is greatly appreciated.
Author: jerryshao <sshao@hortonworks.com>
Closes#14065 from jerryshao/SPARK-16342.
## What changes were proposed in this pull request?
As of Scala 2.11.x there is no longer a org.scala-lang:jline version aligned to the scala version itself. Scala console now uses the plain jline:jline module. Spark's dependency management did not reflect this change properly, causing Maven to pull in Jline via transitive dependency. Unfortunately Jline 2.12 contained a minor but very annoying bug rendering the shell almost useless for developers with german keyboard layout. This request contains the following chages:
- Exclude transitive dependency 'jline:jline' from hive-exec module
- Remove global properties 'jline.version' and 'jline.groupId'
- Add both properties and dependency to 'scala-2.11' profile
- Add explicit dependency on 'jline:jline' to module 'spark-repl'
## How was this patch tested?
- Running mvn dependency:tree and checking for correct Jline version 2.12.1
- Running full builds with assembly and checking for jline-2.12.1.jar in 'lib' folder of generated tarball
Author: Stefan Schulze <stefan.schulze@pentasys.de>
Closes#14429 from stsc-pentasys/SPARK-16770.
## What changes were proposed in this pull request?
New config var: spark.mesos.docker.containerizer={"mesos","docker" (default)}
This adds support for running docker containers via the Mesos unified containerizer: http://mesos.apache.org/documentation/latest/container-image/
The benefit is losing the dependency on `dockerd`, and all the costs which it incurs.
I've also updated the supported Mesos version to 0.28.2 for support of the required protobufs.
This is blocked on: https://github.com/apache/spark/pull/14167
## How was this patch tested?
- manually testing jobs submitted with both "mesos" and "docker" settings for the new config var.
- spark/mesos integration test suite
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#14275 from mgummelt/unified-containerizer.
## What changes were proposed in this pull request?
Version of derby upgraded based on important security info at VersionEye. Test scope added so we don't include it in our final package anyway. NB: I think this should be backported to all previous releases as it is a security problem https://www.versioneye.com/java/org.apache.derby:derby/10.11.1.1
The CVE number is 2015-1832. I also suggest we add a SECURITY tag for JIRAs
## How was this patch tested?
Existing tests with the change making sure that we see no new failures. I checked derby 10.12.x and not derby 10.11.x is downloaded to our ~/.m2 folder.
I then used dev/make-distribution.sh and checked the dist/jars folder for Spark 2.0: no derby jar is present.
I don't know if this would also remove it from the assembly jar in our 1.x branches.
Author: Adam Roberts <aroberts@uk.ibm.com>
Closes#14379 from a-roberts/patch-4.
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Mesos agents by default will not pull docker images which are cached
locally already. In order to run Spark executors from mutable tags like
`:latest` this commit introduces a Spark setting
(`spark.mesos.executor.docker.forcePullImage`). Setting this flag to
true will tell the Mesos agent to force pull the docker image (default is `false` which is consistent with the previous
implementation and Mesos' default
behaviour).
Author: Philipp Hoffmann <mail@philipphoffmann.de>
Closes#14348 from philipphoffmann/force-pull-image.
## What changes were proposed in this pull request?
Mesos agents by default will not pull docker images which are cached
locally already. In order to run Spark executors from mutable tags like
`:latest` this commit introduces a Spark setting
`spark.mesos.executor.docker.forcePullImage`. Setting this flag to
true will tell the Mesos agent to force pull the docker image (default is `false` which is consistent with the previous
implementation and Mesos' default
behaviour).
## How was this patch tested?
I ran a sample application including this change on a Mesos cluster and verified the correct behaviour for both, with and without, force pulling the executor image. As expected the image is being force pulled if the flag is set.
Author: Philipp Hoffmann <mail@philipphoffmann.de>
Closes#13051 from philipphoffmann/force-pull-image.
## What changes were proposed in this pull request?
This patch removes dev/audit-release. It was initially created to do basic release auditing. They have been unused by for the last one year+.
## How was this patch tested?
N/A
Author: Reynold Xin <rxin@databricks.com>
Closes#14342 from rxin/SPARK-16685.
## What changes were proposed in this pull request?
breeze 0.12 has been released for more than half a year, and it brings lots of new features, performance improvement and bug fixes.
One of the biggest features is ```LBFGS-B``` which is an implementation of ```LBFGS``` with box constraints and much faster for some special case.
We would like to implement Huber loss function for ```LinearRegression``` ([SPARK-3181](https://issues.apache.org/jira/browse/SPARK-3181)) and it requires ```LBFGS-B``` as the optimization solver. So we should bump up the dependent breeze version to 0.12.
For more features, improvements and bug fixes of breeze 0.12, you can refer the following link:
https://groups.google.com/forum/#!topic/scala-breeze/nEeRi_DcY5c
## How was this patch tested?
No new tests, should pass the existing ones.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#14150 from yanboliang/spark-16494.
## What changes were proposed in this pull request?
Add a check-cran.sh script that runs `R CMD check` as CRAN. Also fixes a number of issues pointed out by the check. These include
- Updating `DESCRIPTION` to be appropriate
- Adding a .Rbuildignore to ignore lintr, src-native, html that are non-standard files / dirs
- Adding aliases to all S4 methods in DataFrame, Column, GroupedData etc. This is required as stated in https://cran.r-project.org/doc/manuals/r-release/R-exts.html#Documenting-S4-classes-and-methods
- Other minor fixes
## How was this patch tested?
SparkR unit tests, running the above mentioned script
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#14173 from shivaram/sparkr-cran-changes.
## What changes were proposed in this pull request?
This PR adds hive-thriftserver profile to scala 2.10 build created by release-build.sh.
Author: Yin Huai <yhuai@databricks.com>
Closes#14108 from yhuai/SPARK-16453.
In the `dev/run-tests.py` script we check a `Popen.retcode` for success using `retcode > 0`, but this is subtlety wrong because Popen's return code will be negative if the child process was terminated by a signal: https://docs.python.org/2/library/subprocess.html#subprocess.Popen.returncode
In order to properly handle signals, we should change this to check `retcode != 0` instead.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#13692 from JoshRosen/dev-run-tests-return-code-handling.
