## What changes were proposed in this pull request?
We're using an old-ish jQuery, 1.12.4, and should probably update for Spark 3 to keep up in general, but also to keep up with CVEs. In fact, we know of at least one resolved in only 3.4.0+ (https://nvd.nist.gov/vuln/detail/CVE-2019-11358). They may not affect Spark, but, if the update isn't painful, maybe worthwhile in order to make future 3.x updates easier.
jQuery 1 -> 2 doesn't sound like a breaking change, as 2.0 is supposed to maintain compatibility with 1.9+ (https://blog.jquery.com/2013/04/18/jquery-2-0-released/)
2 -> 3 has breaking changes: https://jquery.com/upgrade-guide/3.0/. It's hard to evaluate each one, but the most likely area for problems is in ajax(). However, our usage of jQuery (and plugins) is pretty simple.
Update jquery to 3.4.1; update jquery blockUI and mustache to latest
## How was this patch tested?
Manual testing of docs build (except R docs), worker/master UI, spark application UI.
Note: this really doesn't guarantee it works, as our tests can't test javascript, and this is merely anecdotal testing, although I clicked about every link I could find. There's a risk this breaks a minor part of the UI; it does seem to work fine in the main.
Closes#24843 from srowen/SPARK-28004.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
For Apache Spark 3.0.0 release, this PR aims to update Kafka dependency to 2.2.1 to bring the following improvement and bug fixes like [KAFKA-8134](https://issues.apache.org/jira/browse/KAFKA-8134) (`'linger.ms' must be a long`).
https://issues.apache.org/jira/projects/KAFKA/versions/12345010
## How was this patch tested?
Pass the Jenkins.
Closes#24847 from dongjoon-hyun/SPARK-28013.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
This PR introduces the necessary Maven modules for the new [Spark Graph](https://issues.apache.org/jira/browse/SPARK-25994) feature for Spark 3.0.
* `spark-graph` is a parent module that users depend on to get all graph functionalities (Cypher and Graph Algorithms)
* `spark-graph-api` defines the [Property Graph API](https://docs.google.com/document/d/1Wxzghj0PvpOVu7XD1iA8uonRYhexwn18utdcTxtkxlI) that is being shared between Cypher and Algorithms
* `spark-cypher` contains a Cypher query engine implementation
Both, `spark-graph-api` and `spark-cypher` depend on Spark SQL.
Note, that the Maven module for Graph Algorithms is not part of this PR and will be introduced in https://issues.apache.org/jira/browse/SPARK-27302
A PoC for a running Cypher implementation can be found in this WIP PR https://github.com/apache/spark/pull/24297
## How was this patch tested?
Pass the Jenkins with all profiles and manually build and check the followings.
```
$ ls assembly/target/scala-2.12/jars/spark-cypher*
assembly/target/scala-2.12/jars/spark-cypher_2.12-3.0.0-SNAPSHOT.jar
$ ls assembly/target/scala-2.12/jars/spark-graph* | grep -v graphx
assembly/target/scala-2.12/jars/spark-graph-api_2.12-3.0.0-SNAPSHOT.jar
assembly/target/scala-2.12/jars/spark-graph_2.12-3.0.0-SNAPSHOT.jar
```
Closes#24490 from s1ck/SPARK-27300.
Lead-authored-by: Martin Junghanns <martin.junghanns@neotechnology.com>
Co-authored-by: Max Kießling <max@kopfueber.org>
Co-authored-by: Martin Junghanns <martin.junghanns@neo4j.com>
Co-authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
This pr moves Hive test jars(`hive-contrib-0.13.1.jar`, `hive-hcatalog-core-0.13.1.jar`, `hive-contrib-2.3.5.jar` and `hive-hcatalog-core-2.3.5.jar`) to maven dependency.
## How was this patch tested?
Existing test
Please note that this pr need test with `maven` and `sbt`.
Closes#24751 from wangyum/SPARK-27831.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Move to json4s version 3.6.6
Add scala-xml 1.2.0
## How was this patch tested?
Pass the Jenkins
Closes#24736 from igreenfield/master.
Authored-by: Izek Greenfield <igreenfield@axiomsl.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This fixes CVE-2019-12086 on Databind: https://github.com/FasterXML/jackson/wiki/Jackson-Release-2.9.9
## How was this patch tested?
Existing tests
Closes#24646 from Fokko/SPARK-27757.
Authored-by: Fokko Driesprong <fokko@apache.org>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This pr moves Hive test jars(`hive-contrib-0.13.1.jar`, `hive-hcatalog-core-0.13.1.jar`, `hive-contrib-2.3.5.jar` and `hive-hcatalog-core-2.3.5.jar`) to maven dependency.
## How was this patch tested?
Existing test
Closes#24695 from wangyum/SPARK-27831.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Leave avro, avro-ipc dependendencies as compile scope even for hadoop-provided usages, to ensure 1.8 is used. Hadoop 2.7 has Avro 1.7, and Spark won't generally work with that. Reports from the field are that this works, to include avro 1.8 with the Spark distro on Hadoop 2.7.
## How was this patch tested?
Existing tests
Closes#24680 from srowen/SPARK-26045.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
This PR aims to update `zstd-jni` library to `1.4.0-1` which improves the `level 1 compression speed` performance by 6% in most scenarios. The following is the full release note.
- https://github.com/facebook/zstd/releases/tag/v1.4.0
## How was this patch tested?
Pass the Jenkins.
Closes#24632 from dongjoon-hyun/SPARK-27755.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
This PR upgrades lz4-java from 1.5.1 to 1.6.0. Lz4-java is available at https://github.com/lz4/lz4-java.
Changes from 1.5.1:
- Upgraded LZ4 to 1.9.1. Updated the JNI bindings, except for the one for Linux/i386. Decompression speed is improved on amd64.
- Deprecated use of LZ4FastDecompressor of a native instance because the corresponding C API function is deprecated. See the release note of LZ4 1.9.0 for details. Updated javadoc accordingly.
- Changed the module name from org.lz4.lz4-java to org.lz4.java to avoid using - in the module name. (severn-everett, Oliver Eikemeier, Rei Odaira)
- Enabled build with Java 11. Note that the distribution is still built with Java 7. (Rei Odaira)
## How was this patch tested?
Existing tests.
Closes#24629 from kiszk/SPARK-27752.
Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Fixed the `spark-<version>-yarn-shuffle.jar` artifact packaging to shade the native netty libraries:
- shade the `META-INF/native/libnetty_*` native libraries when packagin
the yarn shuffle service jar. This is required as netty library loader
derives that based on shaded package name.
- updated the `org/spark_project` shade package prefix to `org/sparkproject`
(i.e. removed underscore) as the former breaks the netty native lib loading.
This was causing the yarn external shuffle service to fail
when spark.shuffle.io.mode=EPOLL
## How was this patch tested?
Manual tests
Closes#24502 from amuraru/SPARK-27610_master.
Authored-by: Adi Muraru <amuraru@adobe.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>
## What changes were proposed in this pull request?
This PR aims to upgrade Maven to 3.6.1 to bring JDK9+ related patches like [MNG-6506](https://issues.apache.org/jira/browse/MNG-6506). For the full release note, please see the following.
- https://maven.apache.org/docs/3.6.1/release-notes.html
This was committed and reverted due to AppVeyor failure. It turns out that the root cause is `PATH` issue. With the updated AppVeyor script, it passed.
https://ci.appveyor.com/project/ApacheSoftwareFoundation/spark/builds/24273412
## How was this patch tested?
Pass the Jenkins and AppVoyer
Closes#24481 from dongjoon-hyun/SPARK-R.
Lead-authored-by: Dongjoon Hyun <dhyun@apple.com>
Co-authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
PR #23890 introduced `org.glassfish.jaxb:jaxb-runtime:2.3.2` as a runtime dependency. As an unexpected side effect, `jakarta.activation:jakarta.activation-api:1.2.1` was also pulled in as a transitive dependency. As a result, for the Maven build, both of the following two jars can be found under `assembly/target/scala-2.12/jars/`:
```
activation-1.1.1.jar
jakarta.activation-api-1.2.1.jar
```
This PR exludes the Jakarta one.
Manually built Spark using Maven and checked files under `assembly/target/scala-2.12/jars/`. After this change, only `activation-1.1.1.jar` is there.
Closes#24507 from liancheng/spark-27611.
Authored-by: Cheng Lian <lian@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
One more place to update ASM 7.0 -> 7.1
## How was this patch tested?
Existing tests
Closes#24508 from srowen/SPARK-27493.3.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
This PR aims to upgrade Surefire plugin to 3.0.0-M3 to bring [SUREFIRE-1613](https://issues.apache.org/jira/browse/SUREFIRE-1613).
## How was this patch tested?
Pass the Jenkins with the existing tests.
Closes#24501 from dongjoon-hyun/SPARK-27608.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
hadoop-2.7 gets `commons-logging` version from `hive-metastore`:
```
[INFO] +- org.spark-project.hive:hive-metastore:jar:1.2.1.spark2:compile
[INFO] | +- com.jolbox:bonecp:jar:0.8.0.RELEASE:compile
[INFO] | +- commons-cli:commons-cli:jar:1.2:compile
[INFO] | +- commons-logging:commons-logging:jar:1.1.3:compile
```
But Hive removes `commons-logging` since [HIVE-12237(Hive 2.0.0)](https://issues.apache.org/jira/browse/HIVE-12237), so hadoop-3.2 gets `commons-logging` from `commons-httpclient`:
```
[INFO] +- commons-httpclient:commons-httpclient:jar:3.1:compile
[INFO] | \- commons-logging:commons-logging:jar:1.0.4:compile
```
Thus. we may hint `LogConfigurationException`:
```
bin/spark-sql --conf spark.sql.hive.metastore.version=1.2.2 --conf spark.sql.hive.metastore.jars=file:///apache/hive-1.2.2-bin/lib/*
...
Caused by: org.apache.commons.logging.LogConfigurationException: Invalid class loader hierarchy. You have more than one version of 'org.apache.commons.logging.Log' visible, which is not allowed.
at org.apache.commons.logging.impl.LogFactoryImpl.getLogConstructor(LogFactoryImpl.java:385)
... 43 more
```
This pr upgrade `commons-logging` to 1.1.3 for hadoop-3.2 to fix this issue.
## How was this patch tested?
manual tests
Closes#24388 from wangyum/SPARK-27481.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR aims to upgrade Maven to 3.6.1 to bring JDK9+ related patches like [MNG-6506](https://issues.apache.org/jira/browse/MNG-6506). For the full release note, please see the following.
- https://maven.apache.org/docs/3.6.1/release-notes.html
## How was this patch tested?
Pass the Jenkins with `[test-maven]` tag.
Closes#24377 from dongjoon-hyun/SPARK-27467.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Unify commons-beanutils deps to latest 1.9.3. This resolves the version inconsistency in Hadoop 2.7's build and also picks up security and bug fixes.
## How was this patch tested?
Existing tests.
Closes#24378 from srowen/SPARK-27469.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
This PR upgrades `lz4-java` to 1.5.1 in order to get a patch for avoiding racing with GC.
- https://github.com/lz4/lz4-java/blob/master/CHANGES.md#151
## How was this patch tested?
Pass the Jenkins with the existing tests.
Closes#24363 from dongjoon-hyun/SPARK-LZ4.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
This PR mainly contains:
1. Upgrade hadoop-3's built-in Hive maven dependencies to 2.3.4.
2. Resolve compatibility issues between Hive 1.2.1 and Hive 2.3.4 in the `sql/hive` module.
## How was this patch tested?
jenkins test hadoop-2.7
manual test hadoop-3:
```shell
build/sbt clean package -Phadoop-3.2 -Phive
export SPARK_PREPEND_CLASSES=true
# rm -rf metastore_db
cat <<EOF > test_hadoop3.scala
spark.range(10).write.saveAsTable("test_hadoop3")
spark.table("test_hadoop3").show
EOF
bin/spark-shell --conf spark.hadoop.hive.metastore.schema.verification=false --conf spark.hadoop.datanucleus.schema.autoCreateAll=true -i test_hadoop3.scala
```
Closes#23788 from wangyum/SPARK-23710-hadoop3.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
HighlyCompressedMapStatus uses RoaringBitmap to record the empty blocks. But RoaringBitmap couldn't be ser/deser with unsafe KryoSerializer.
It's a bug of RoaringBitmap-0.5.11 and fixed in latest version.
This is an update of #24157
## How was this patch tested?
Add a UT
Closes#24264 from LantaoJin/SPARK-27216.
Lead-authored-by: LantaoJin <jinlantao@gmail.com>
Co-authored-by: Lantao Jin <jinlantao@gmail.com>
Signed-off-by: Imran Rashid <irashid@cloudera.com>
## What changes were proposed in this pull request?
(See JIRA for problem statement)
Update snappy 1.1.7.1 -> 1.1.7.3 to pick up an empty-stream and Java 9 fix.
There appear to be no other changes of consequence:
https://github.com/xerial/snappy-java/blob/master/Milestone.md
## How was this patch tested?
Existing tests
Closes#24242 from srowen/SPARK-27267.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Remove Scala 2.11 support in build files and docs, and in various parts of code that accommodated 2.11. See some targeted comments below.
## How was this patch tested?
Existing tests.
Closes#23098 from srowen/SPARK-26132.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR aims to update Kafka dependency to 2.2.0 to bring the following improvement and bug fixes.
- https://issues.apache.org/jira/projects/KAFKA/versions/12344063
Due to [KAFKA-4453](https://issues.apache.org/jira/browse/KAFKA-4453), data plane API and controller plane API are separated. Apache Spark needs the following changes.
```scala
- servers.head.apis.metadataCache
+ servers.head.dataPlaneRequestProcessor.metadataCache
```
## How was this patch tested?
Pass the Jenkins with the existing tests.
Closes#24190 from dongjoon-hyun/SPARK-27260.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Fix Scala 2.11 maven build issue after merging SPARK-26946.
## How was this patch tested?
Maven Scala 2.11 and 2.12 builds with `-Phadoop-provided -Phadoop-2.7 -Pyarn -Phive -Phive-thriftserver`.
Closes#24184 from jzhuge/SPARK-26946-1.
Authored-by: John Zhuge <jzhuge@apache.org>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Since [YARN-7113](https://issues.apache.org/jira/browse/YARN-7113)(Hadoop-3.1.0), `hadoop-client` add `javax.ws.rs:jsr311-api` to its dependency. This conflict with [javax.ws.rs-api-2.0.1.jar](f26a1f3d37/dev/deps/spark-deps-hadoop-3.1 (L105)).
```shell
build/sbt "core/testOnly *.UISeleniumSuite *.HistoryServerSuite" -Phadoop-3.2
...
[info] <pre> Server Error</pre></p><h3>Caused by:</h3><pre>java.lang.NoSuchMethodError: javax.ws.rs.core.Application.getProperties()Ljava/util/Map;
...
```
This pr exclude `javax.ws.rs:jsr311-api` from hadoop-client.
## How was this patch tested?
manual tests:
```shell
build/sbt "core/testOnly *.UISeleniumSuite *.HistoryServerSuite" -Phadoop-3.2
```
Closes#24114 from wangyum/SPARK-27179.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR upgrade `hadoop-3` to `3.2.0` to workaround [HADOOP-16086](https://issues.apache.org/jira/browse/HADOOP-16086). Otherwise some test case will throw IllegalArgumentException:
```java
02:44:34.707 ERROR org.apache.hadoop.hive.ql.exec.Task: Job Submission failed with exception 'java.io.IOException(Cannot initialize Cluster. Please check your configuration for mapreduce.framework.name and the correspond server addresses.)'
java.io.IOException: Cannot initialize Cluster. Please check your configuration for mapreduce.framework.name and the correspond server addresses.
at org.apache.hadoop.mapreduce.Cluster.initialize(Cluster.java:116)
at org.apache.hadoop.mapreduce.Cluster.<init>(Cluster.java:109)
at org.apache.hadoop.mapreduce.Cluster.<init>(Cluster.java:102)
at org.apache.hadoop.mapred.JobClient.init(JobClient.java:475)
at org.apache.hadoop.mapred.JobClient.<init>(JobClient.java:454)
at org.apache.hadoop.hive.ql.exec.mr.ExecDriver.execute(ExecDriver.java:369)
at org.apache.hadoop.hive.ql.exec.mr.MapRedTask.execute(MapRedTask.java:151)
at org.apache.hadoop.hive.ql.exec.Task.executeTask(Task.java:199)
at org.apache.hadoop.hive.ql.exec.TaskRunner.runSequential(TaskRunner.java:100)
at org.apache.hadoop.hive.ql.Driver.launchTask(Driver.java:2183)
at org.apache.hadoop.hive.ql.Driver.execute(Driver.java:1839)
at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1526)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1237)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1227)
at org.apache.spark.sql.hive.client.HiveClientImpl.$anonfun$runHive$1(HiveClientImpl.scala:730)
at org.apache.spark.sql.hive.client.HiveClientImpl.$anonfun$withHiveState$1(HiveClientImpl.scala:283)
at org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:221)
at org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:220)
at org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:266)
at org.apache.spark.sql.hive.client.HiveClientImpl.runHive(HiveClientImpl.scala:719)
at org.apache.spark.sql.hive.client.HiveClientImpl.runSqlHive(HiveClientImpl.scala:709)
at org.apache.spark.sql.hive.StatisticsSuite.createNonPartitionedTable(StatisticsSuite.scala:719)
at org.apache.spark.sql.hive.StatisticsSuite.$anonfun$testAlterTableProperties$2(StatisticsSuite.scala:822)
```
## How was this patch tested?
manual tests
Closes#24106 from wangyum/SPARK-27175.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR aims to update Apache ORC dependency to fix [SPARK-27107](https://issues.apache.org/jira/browse/SPARK-27107) .
```
[ORC-452] Support converting MAP column from JSON to ORC Improvement
[ORC-447] Change the docker scripts to keep a persistent m2 cache
[ORC-463] Add `version` command
[ORC-475] ORC reader should lazily get filesystem
[ORC-476] Make SearchAgument kryo buffer size configurable
```
## How was this patch tested?
Pass the Jenkins with the existing tests.
Closes#24096 from dongjoon-hyun/SPARK-27165.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
**ScalaTest 3.0.5 Release Notes**
**Bug Fixes**
- Fixed the implicit view not available problem when used with compile macro.
- Fixed a stack depth problem in RefSpecLike and fixture.SpecLike under Scala 2.13.
- Changed Framework and ScalaTestFramework to set spanScaleFactor for Runner object instances for different Runners using different class loaders. This fixed a problem whereby an incorrect Runner.spanScaleFactor could be used when the tests for multiple sbt project's were run concurrently.
- Fixed a bug in endsWith regex matcher.
**Improvements**
- Removed duplicated parsing code for -C in ArgsParser.
- Improved performance in WebBrowser.
- Documentation typo rectification.
- Improve validity of Junit XML reports.
- Improved performance by replacing all .size == 0 and .length == 0 to .isEmpty.
**Enhancements**
- Added 'C' option to -P, which will tell -P to use cached thread pool.
- External Dependencies Update
- Bumped up scala-js version to 0.6.22.
- Changed to depend on mockito-core, not mockito-all.
- Bumped up jmock version to 2.8.3.
- Bumped up junit version to 4.12.
- Removed dependency to scala-parser-combinators.
More details:
http://www.scalatest.org/release_notes/3.0.5
## How was this patch tested?
manual tests on local machine:
```
nohup build/sbt clean -Djline.terminal=jline.UnsupportedTerminal -Phadoop-2.7 -Pkubernetes -Phive-thriftserver -Pyarn -Pspark-ganglia-lgpl -Phive -Pkinesis-asl -Pmesos test > run.scalatest.log &
```
Closes#24042 from wangyum/SPARK-27120.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
This pr adds 2 maven properties to help us upgrade the built-in Hive.
| Property Name | Default | In future |
| ------ | ------ | ------ |
| hive.classifier | (none) | core |
| hive.parquet.group | com.twitter | org.apache.parquet |
## How was this patch tested?
existing tests
Closes#23996 from wangyum/add_2_maven_properties.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Fasterxml Jackson version before 2.9.8 is affected by multiple [CVEs](https://github.com/FasterXML/jackson-databind/issues/2186), we need to fix bump the dependent Jackson to 2.9.8.
## How was this patch tested?
Existing tests and offline benchmark.
I have run ```SPARK_GENERATE_BENCHMARK_FILES=1 build/sbt "sql/test:runMain org.apache.spark.sql.execution.datasources.json.JSONBenchmark"``` to check there is no performance degradation for this upgrade.
Closes#23965 from yanboliang/SPARK-27051.
Authored-by: Yanbo Liang <ybliang8@gmail.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
Update Thrift to 0.12.0 to pick up bug and security fixes.
Changes: https://github.com/apache/thrift/blob/master/CHANGES.md
The important one is for https://issues.apache.org/jira/browse/THRIFT-4506
## How was this patch tested?
Existing tests. A quick local test suggests this works.
Closes#23935 from srowen/SPARK-27029.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Remove a few new JAXB dependencies that shouldn't be necessary now.
See https://github.com/apache/spark/pull/23890#issuecomment-468299922
## How was this patch tested?
Existing tests
Closes#23923 from srowen/SPARK-26986.2.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Add reference JAXB impl for Java 9+ from Glassfish. Right now it's only apparently necessary in MLlib but can be expanded later.
## How was this patch tested?
Existing tests particularly PMML-related ones, which use JAXB.
This works on Java 11.
Closes#23890 from srowen/SPARK-26986.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Since Spark 2.0, Akka is not used anymore and Akka related stuff were removed. However there are still some leftover. This PR aims to remove these leftover.
* `/pom.xml` has a comment about Akka, which is not needed anymore.
## How was this patch tested?
Existing tests.
Closes#23885 from seancxmao/remove-akka-leftover.
Authored-by: seancxmao <seancxmao@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
JPMML apparently only supports Java 9 in 1.4.2+. We are seeing text failures from JPMML relating to JAXB when running on Java 11. It's shaded and not a big change, so should be safe.
## How was this patch tested?
Existing tests.
Closes#23868 from srowen/SPARK-26966.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
As a part of preparing the official JDK 11 support ([SPARK-24417](https://issues.apache.org/jira/browse/SPARK-24417)), Spark 3.0.0 upgraded KAFKA version to 2.1.0. This PR updates Kafka dependency to 2.1.1 to bring the following 42 bug fixes.
- https://issues.apache.org/jira/projects/KAFKA/versions/12344250
## How was this patch tested?
Pass the Jenkins with the existing tests.
Closes#23831 from dongjoon-hyun/SPARK-26916.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
## What changes were proposed in this pull request?
Update to Parquet Java 1.10.1.
## How was this patch tested?
Added a test from HyukjinKwon that validates the notEq case from SPARK-26677.
Closes#23704 from rdblue/SPARK-26677-fix-noteq-parquet-bug.
Lead-authored-by: Ryan Blue <blue@apache.org>
Co-authored-by: Hyukjin Kwon <gurwls223@apache.org>
Co-authored-by: Ryan Blue <rdblue@users.noreply.github.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
Upgrade Apache Arrow to version 0.12.0. This includes the Java artifacts and fixes to enable usage with pyarrow 0.12.0
Version 0.12.0 includes the following selected fixes/improvements relevant to Spark users:
* Safe cast fails from numpy float64 array with nans to integer, ARROW-4258
* Java, Reduce heap usage for variable width vectors, ARROW-4147
* Binary identity cast not implemented, ARROW-4101
* pyarrow open_stream deprecated, use ipc.open_stream, ARROW-4098
* conversion to date object no longer needed, ARROW-3910
* Error reading IPC file with no record batches, ARROW-3894
* Signed to unsigned integer cast yields incorrect results when type sizes are the same, ARROW-3790
* from_pandas gives incorrect results when converting floating point to bool, ARROW-3428
* Import pyarrow fails if scikit-learn is installed from conda (boost-cpp / libboost issue), ARROW-3048
* Java update to official Flatbuffers version 1.9.0, ARROW-3175
complete list [here](https://issues.apache.org/jira/issues/?jql=project%20%3D%20ARROW%20AND%20status%20in%20(Resolved%2C%20Closed)%20AND%20fixVersion%20%3D%200.12.0)
PySpark requires the following fixes to work with PyArrow 0.12.0
* Encrypted pyspark worker fails due to ChunkedStream missing closed property
* pyarrow now converts dates as objects by default, which causes error because type is assumed datetime64
* ArrowTests fails due to difference in raised error message
* pyarrow.open_stream deprecated
* tests fail because groupby adds index column with duplicate name
## How was this patch tested?
Ran unit tests with pyarrow versions 0.8.0, 0.10.0, 0.11.1, 0.12.0
Closes#23657 from BryanCutler/arrow-upgrade-012.
Authored-by: Bryan Cutler <cutlerb@gmail.com>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
There are ugly provided dependencies inside core for the following:
* Hive
* Kafka
In this PR I've extracted them out. This PR contains the following:
* Token providers are now loaded with service loader
* Hive token provider moved to hive project
* Kafka token provider extracted into a new project
## How was this patch tested?
Existing + newly added unit tests.
Additionally tested on cluster.
Closes#23499 from gaborgsomogyi/SPARK-26254.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>
## What changes were proposed in this pull request?
With Scala-2.12 profile, Spark application fails while Spark is okay. For example, our documented `SimpleApp` Java example succeeds to compile but it fails at runtime because it doesn't use `paranamer 2.8` and hits [SPARK-22128](https://issues.apache.org/jira/browse/SPARK-22128). This PR aims to declare it explicitly for the Spark applications. Note that this doesn't introduce new dependency to Spark itself.
https://dist.apache.org/repos/dist/dev/spark/3.0.0-SNAPSHOT-2019_01_09_13_59-e853afb-docs/_site/quick-start.html
The following is the dependency tree from the Spark application.
**BEFORE**
```
$ mvn dependency:tree -Dincludes=com.thoughtworks.paranamer
[INFO] --- maven-dependency-plugin:2.8:tree (default-cli) simple ---
[INFO] my.test:simple:jar:1.0-SNAPSHOT
[INFO] \- org.apache.spark:spark-sql_2.12🫙3.0.0-SNAPSHOT:compile
[INFO] \- org.apache.spark:spark-core_2.12🫙3.0.0-SNAPSHOT:compile
[INFO] \- org.apache.avro:avro:jar:1.8.2:compile
[INFO] \- com.thoughtworks.paranamer:paranamer:jar:2.7:compile
```
**AFTER**
```
[INFO] --- maven-dependency-plugin:2.8:tree (default-cli) simple ---
[INFO] my.test:simple:jar:1.0-SNAPSHOT
[INFO] \- org.apache.spark:spark-sql_2.12🫙3.0.0-SNAPSHOT:compile
[INFO] \- org.apache.spark:spark-core_2.12🫙3.0.0-SNAPSHOT:compile
[INFO] \- com.thoughtworks.paranamer:paranamer:jar:2.8:compile
```
## How was this patch tested?
Pass the Jenkins. And manually test with the sample app is running.
Closes#23502 from dongjoon-hyun/SPARK-26583.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
This PR upgrades Mockito from 1.10.19 to 2.23.4. The following changes are required.
- Replace `org.mockito.Matchers` with `org.mockito.ArgumentMatchers`
- Replace `anyObject` with `any`
- Replace `getArgumentAt` with `getArgument` and add type annotation.
- Use `isNull` matcher in case of `null` is invoked.
```scala
saslHandler.channelInactive(null);
- verify(handler).channelInactive(any(TransportClient.class));
+ verify(handler).channelInactive(isNull());
```
- Make and use `doReturn` wrapper to avoid [SI-4775](https://issues.scala-lang.org/browse/SI-4775)
```scala
private def doReturn(value: Any) = org.mockito.Mockito.doReturn(value, Seq.empty: _*)
```
## How was this patch tested?
Pass the Jenkins with the existing tests.
Closes#23452 from dongjoon-hyun/SPARK-26536.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
due to apache recently moving from git-wip-us.apache.org to gitbox.apache.org, we need to update the packaging scripts to point to the new repo location.
this will also need to be backported to 2.4, 2.3, 2.1, 2.0 and 1.6.
## How was this patch tested?
the build system will test this.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Closes#23454 from shaneknapp/update-apache-repo.
Authored-by: shane knapp <incomplete@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
Increase test memory to avoid OOM in TimSort-related tests.
## How was this patch tested?
Existing tests.
Closes#23425 from srowen/SPARK-26306.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This should make tests in core modules pass for Java 11.
## How was this patch tested?
Existing tests, with modifications.
Closes#23419 from srowen/Java11.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR aims to upgrade Maven Surefile plugin for JDK11 support. 3.0.0-M2 is [released Dec. 9th.](https://issues.apache.org/jira/projects/SUREFIRE/versions/12344396)
```
[SUREFIRE-1568] Versions 2.21 and higher doesn't work with junit-platform for Java 9 module
[SUREFIRE-1605] NoClassDefFoundError (RunNotifier) with JDK 11
[SUREFIRE-1600] Surefire Project using surefire:2.12.4 is not fully able to work with JDK 10+ on internal build system. Therefore surefire-shadefire should go with Surefire:3.0.0-M2.
[SUREFIRE-1593] 3.0.0-M1 produces invalid code sources on Windows
[SUREFIRE-1602] Surefire fails loading class ForkedBooter when using a sub-directory pom file and a local maven repo
[SUREFIRE-1606] maven-shared-utils must not be on provider's classpath
[SUREFIRE-1531] Option to switch-off Java 9 modules
[SUREFIRE-1590] Deploy multiple versions of Report XSD
[SUREFIRE-1591] Java 1.7 feature Diamonds replaced Generics
[SUREFIRE-1594] Java 1.7 feature try-catch - multiple exceptions in one catch
[SUREFIRE-1595] Java 1.7 feature System.lineSeparator()
[SUREFIRE-1597] ModularClasspathForkConfiguration with debug logs (args file and its path on file system)
[SUREFIRE-1596] Unnecessary check JAVA_RECENT == JAVA_1_7 in unit tests
[SUREFIRE-1598] Fixed typo in assertion statement in integration test Surefire855AllowFailsafeUseArtifactFileIT
[SUREFIRE-1607] Roadmap on Project Site
```
## How was this patch tested?
Pass the Jenkins.
Closes#23370 from dongjoon-hyun/SPARK-26430.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
This PR aims to update Apache ORC dependency to the latest version 1.5.4 released at Dec. 20. ([Release Notes](https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12318320&version=12344187]))
```
[ORC-237] OrcFile.mergeFiles Specified block size is less than configured minimum value
[ORC-409] Changes for extending MemoryManagerImpl
[ORC-410] Fix a locale-dependent test in TestCsvReader
[ORC-416] Avoid opening data reader when there is no stripe
[ORC-417] Use dynamic Apache Maven mirror link
[ORC-419] Ensure to call `close` at RecordReaderImpl constructor exception
[ORC-432] openjdk 8 has a bug that prevents surefire from working
[ORC-435] Ability to read stripes that are greater than 2GB
[ORC-437] Make acid schema checks case insensitive
[ORC-411] Update build to work with Java 10.
[ORC-418] Fix broken docker build script
```
## How was this patch tested?
Build and pass Jenkins.
Closes#23364 from dongjoon-hyun/SPARK-26427.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
Update to Scala 2.12.8
## How was this patch tested?
Existing tests.
Closes#23218 from srowen/SPARK-26266.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR aims to upgrade Janino compiler to the latest version 3.0.11. The followings are the changes from the [release note](http://janino-compiler.github.io/janino/changelog.html).
- Script with many "helper" variables.
- Java 9+ compatibility
- Compilation Error Messages Generated by JDK.
- Added experimental support for the "StackMapFrame" attribute; not active yet.
- Make Unparser more flexible.
- Fixed NPEs in various "toString()" methods.
- Optimize static method invocation with rvalue target expression.
- Added all missing "ClassFile.getConstant*Info()" methods, removing the necessity for many type casts.
## How was this patch tested?
Pass the Jenkins with the existing tests.
Closes#23250 from dongjoon-hyun/SPARK-26298.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
This PR updates maven version from 3.5.4 to 3.6.0. The release note of the 3.6.0 is [here](https://maven.apache.org/docs/3.6.0/release-notes.html).
From [the release note of the 3.6.0](https://maven.apache.org/docs/3.6.0/release-notes.html), the followings are new features:
1. There had been issues related to the project discoverytime which has been increased in previous version which influenced some of our users.
1. The output in the reactor summary has been improved.
1. There was an issue related to the classpath ordering.
## How was this patch tested?
Existing tests
Closes#23177 from kiszk/SPARK-26212.
Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
It adds kafka delegation token support for structured streaming. Please see the relevant [SPIP](https://docs.google.com/document/d/1ouRayzaJf_N5VQtGhVq9FURXVmRpXzEEWYHob0ne3NY/edit?usp=sharing)
What this PR contains:
* Configuration parameters for the feature
* Delegation token fetching from broker
* Usage of token through dynamic JAAS configuration
* Minor refactoring in the existing code
What this PR doesn't contain:
* Documentation changes because design can change
## How was this patch tested?
Existing tests + added small amount of additional unit tests.
Because it's an external service integration mainly tested on cluster.
* 4 node cluster
* Kafka broker version 1.1.0
* Topic with 4 partitions
* security.protocol = SASL_SSL
* sasl.mechanism = SCRAM-SHA-256
An example of obtaining a token:
```
18/10/01 01:07:49 INFO kafka010.TokenUtil: TOKENID HMAC OWNER RENEWERS ISSUEDATE EXPIRYDATE MAXDATE
18/10/01 01:07:49 INFO kafka010.TokenUtil: D1-v__Q5T_uHx55rW16Jwg [hidden] User:user [] 2018-10-01T01:07 2018-10-02T01:07 2018-10-08T01:07
18/10/01 01:07:49 INFO security.KafkaDelegationTokenProvider: Get token from Kafka: Kind: KAFKA_DELEGATION_TOKEN, Service: kafka.server.delegation.token, Ident: 44 31 2d 76 5f 5f 51 35 54 5f 75 48 78 35 35 72 57 31 36 4a 77 67
```
An example token usage:
```
18/10/01 01:08:07 INFO kafka010.KafkaSecurityHelper: Scram JAAS params: org.apache.kafka.common.security.scram.ScramLoginModule required tokenauth=true serviceName="kafka" username="D1-v__Q5T_uHx55rW16Jwg" password="[hidden]";
18/10/01 01:08:07 INFO kafka010.KafkaSourceProvider: Delegation token detected, using it for login.
```
Closes#22598 from gaborgsomogyi/SPARK-25501.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@cloudera.com>
## What changes were proposed in this pull request?
Add a maven plugin and wrapper script to use scalafmt to format files that differ from git master.
Intention is for contributors to be able to use this to automate fixing code style, not to include it in build pipeline yet.
If this PR is accepted, I'd make a different PR to update the code style section of https://spark.apache.org/contributing.html to mention the script
## How was this patch tested?
Manually tested by modifying a few files and running ./dev/scalafmt then checking that ./dev/scalastyle still passed.
Closes#23148 from koeninger/scalafmt.
Authored-by: cody koeninger <cody@koeninger.org>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
When I ran spark-shell on JDK11+28(2018-09-25), It failed with the error below.
```
Exception in thread "main" java.lang.ExceptionInInitializerError
at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:80)
at org.apache.hadoop.security.SecurityUtil.getAuthenticationMethod(SecurityUtil.java:611)
at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:273)
at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:261)
at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:791)
at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:761)
at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:634)
at org.apache.spark.util.Utils$.$anonfun$getCurrentUserName$1(Utils.scala:2427)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2427)
at org.apache.spark.SecurityManager.<init>(SecurityManager.scala:79)
at org.apache.spark.deploy.SparkSubmit.secMgr$lzycompute$1(SparkSubmit.scala:359)
at org.apache.spark.deploy.SparkSubmit.secMgr$1(SparkSubmit.scala:359)
at org.apache.spark.deploy.SparkSubmit.$anonfun$prepareSubmitEnvironment$9(SparkSubmit.scala:367)
at scala.Option.map(Option.scala:146)
at org.apache.spark.deploy.SparkSubmit.prepareSubmitEnvironment(SparkSubmit.scala:367)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:143)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:927)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:936)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.StringIndexOutOfBoundsException: begin 0, end 3, length 2
at java.base/java.lang.String.checkBoundsBeginEnd(String.java:3319)
at java.base/java.lang.String.substring(String.java:1874)
at org.apache.hadoop.util.Shell.<clinit>(Shell.java:52)
```
This is a Hadoop issue that fails to parse some java.version. It has been fixed from Hadoop-2.7.4(see [HADOOP-14586](https://issues.apache.org/jira/browse/HADOOP-14586)).
Note, Hadoop-2.7.5 or upper have another problem with Spark ([SPARK-25330](https://issues.apache.org/jira/browse/SPARK-25330)). So upgrading to 2.7.4 would be fine for now.
## How was this patch tested?
Existing tests.
Closes#23101 from tasanuma/SPARK-26134.
Authored-by: Takanobu Asanuma <tasanuma@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
Update many plugins we use to the latest version, especially MiMa, which entails excluding some new errors on old changes.
## How was this patch tested?
N/A
Closes#23087 from srowen/Plugins.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
The build has a lot of deprecation warnings. Some are new in Scala 2.12 and Java 11. We've fixed some, but I wanted to take a pass at fixing lots of easy miscellaneous ones here.
They're too numerous and small to list here; see the pull request. Some highlights:
- `BeanInfo` is deprecated in 2.12, and BeanInfo classes are pretty ancient in Java. Instead, case classes can explicitly declare getters
- Eta expansion of zero-arg methods; foo() becomes () => foo() in many cases
- Floating-point Range is inexact and deprecated, like 0.0 to 100.0 by 1.0
- finalize() is finally deprecated (just needs to be suppressed)
- StageInfo.attempId was deprecated and easiest to remove here
I'm not now going to touch some chunks of deprecation warnings:
- Parquet deprecations
- Hive deprecations (particularly serde2 classes)
- Deprecations in generated code (mostly Thriftserver CLI)
- ProcessingTime deprecations (we may need to revive this class as internal)
- many MLlib deprecations because they concern methods that may be removed anyway
- a few Kinesis deprecations I couldn't figure out
- Mesos get/setRole, which I don't know well
- Kafka/ZK deprecations (e.g. poll())
- Kinesis
- a few other ones that will probably resolve by deleting a deprecated method
## How was this patch tested?
Existing tests, including manual testing with the 2.11 build and Java 11.
Closes#23065 from srowen/SPARK-26090.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This restores scaladoc artifact generation, which got dropped with the Scala 2.12 update. The change looks large, but is almost all due to needing to make the InterfaceStability annotations top-level classes (i.e. `InterfaceStability.Stable` -> `Stable`), unfortunately. A few inner class references had to be qualified too.
Lots of scaladoc warnings now reappear. We can choose to disable generation by default and enable for releases, later.
## How was this patch tested?
N/A; build runs scaladoc now.
Closes#23069 from srowen/SPARK-26026.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR makes Spark's default Scala version as 2.12, and Scala 2.11 will be the alternative version. This implies that Scala 2.12 will be used by our CI builds including pull request builds.
We'll update the Jenkins to include a new compile-only jobs for Scala 2.11 to ensure the code can be still compiled with Scala 2.11.
## How was this patch tested?
existing tests
Closes#22967 from dbtsai/scala2.12.
Authored-by: DB Tsai <d_tsai@apple.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
…. Other related changes to get JDK 11 working, to test
## What changes were proposed in this pull request?
- Access `sun.misc.Cleaner` (Java 8) and `jdk.internal.ref.Cleaner` (JDK 9+) by reflection (note: the latter only works if illegal reflective access is allowed)
- Access `sun.misc.Unsafe.invokeCleaner` in Java 9+ instead of `sun.misc.Cleaner` (Java 8)
In order to test anything on JDK 11, I also fixed a few small things, which I include here:
- Fix minor JDK 11 compile issues
- Update scala plugin, Jetty for JDK 11, to facilitate tests too
This doesn't mean JDK 11 tests all pass now, but lots do. Note also that the JDK 9+ solution for the Cleaner has a big caveat.
## How was this patch tested?
Existing tests. Manually tested JDK 11 build and tests, and tests covering this change appear to pass. All Java 8 tests should still pass, but this change alone does not achieve full JDK 11 compatibility.
Closes#22993 from srowen/SPARK-24421.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Based on the release description of ANTRL 4.7.1., https://github.com/antlr/antlr4/releases, let us upgrade our parser to 4.7.1.
## How was this patch tested?
N/A
Closes#23005 from gatorsmile/upgradeAntlr4.7.
Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
Upgrade ASM to 7.x to support JDK11
## How was this patch tested?
Existing tests.
Closes#22953 from dbtsai/asm7.
Authored-by: DB Tsai <d_tsai@apple.com>
Signed-off-by: DB Tsai <d_tsai@apple.com>
## What changes were proposed in this pull request?
- Fixes the scala version propagation issue.
- Disables the tests under the k8s profile, now we will run them manually. Adds a test specific profile otherwise tests will not run if we just remove the module from the kubernetes profile (quickest solution I can think of).
## How was this patch tested?
Manually by running the tests with different versions of scala.
Closes#22838 from skonto/propagate-scala2.12.
Authored-by: Stavros Kontopoulos <stavros.kontopoulos@lightbend.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
We find below warnings when build spark project:
```
[warn] * com.google.code.findbugs:jsr305:3.0.0 is selected over 1.3.9
[warn] +- org.apache.hadoop:hadoop-common:2.7.3 (depends on 3.0.0)
[warn] +- org.apache.spark:spark-core_2.11:3.0.0-SNAPSHOT (depends on 1.3.9)
[warn] +- org.apache.spark:spark-network-common_2.11:3.0.0-SNAPSHOT (depends on 1.3.9)
[warn] +- org.apache.spark:spark-unsafe_2.11:3.0.0-SNAPSHOT (depends on 1.3.9)
```
So ideally we need to upgrade jsr305 from 1.3.9 to 3.0.0 to fix this warning
Upgrade one of the dependencies jsr305 version from 1.3.9 to 3.0.0
## How was this patch tested?
sbt "core/testOnly"
sbt "sql/testOnly"
Closes#22803 from daviddingly/master.
Authored-by: xiaoding <xiaoding@ebay.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Upgrade netty dependency from 4.1.17 to 4.1.30.
Explanation:
Currently when sending a ChunkedByteBuffer with more than 16 chunks over the network will trigger a "merge" of all the blocks into one big transient array that is then sent over the network. This is problematic as the total memory for all chunks can be high (2GB) and this would then trigger an allocation of 2GB to merge everything, which will create OOM errors.
And we can avoid this issue by upgrade the netty. https://github.com/netty/netty/pull/8038
## How was this patch tested?
Manual tests in some spark jobs.
Closes#22765 from lipzhu/SPARK-25757.
Authored-by: Zhu, Lipeng <lipzhu@ebay.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
Remove Kafka 0.8 integration
## How was this patch tested?
Existing tests, build scripts
Closes#22703 from srowen/SPARK-25705.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Removes all vestiges of Flume in the build, for Spark 3.
I don't think this needs Jenkins config changes.
## How was this patch tested?
Existing tests.
Closes#22692 from srowen/SPARK-25598.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Remove Hadoop 2.6 references and make 2.7 the default.
Obviously, this is for master/3.0.0 only.
After this we can also get rid of the separate test jobs for Hadoop 2.6.
## How was this patch tested?
Existing tests
Closes#22615 from srowen/SPARK-25016.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR upgrade `lz4-java` to 1.5.0 get speed improvement.
**General speed improvements**
LZ4 decompression speed has always been a strong point. In v1.8.2, this gets even better, as it improves decompression speed by about 10%, thanks in a large part to suggestion from svpv .
For example, on a Mac OS-X laptop with an Intel Core i7-5557U CPU 3.10GHz,
running lz4 -bsilesia.tar compiled with default compiler llvm v9.1.0:
Version | v1.8.1 | v1.8.2 | Improvement
-- | -- | -- | --
Decompression speed | 2490 MB/s | 2770 MB/s | +11%
Compression speeds also receive a welcomed boost, though improvement is not evenly distributed, with higher levels benefiting quite a lot more.
Version | v1.8.1 | v1.8.2 | Improvement
-- | -- | -- | --
lz4 -1 | 504 MB/s | 516 MB/s | +2%
lz4 -9 | 23.2 MB/s | 25.6 MB/s | +10%
lz4 -12 | 3.5 Mb/s | 9.5 MB/s | +170%
More details:
https://github.com/lz4/lz4/releases/tag/v1.8.3
**Below is my benchmark result**
set `spark.sql.parquet.compression.codec` to `lz4` and disable orc benchmark, then run `FilterPushdownBenchmark`.
lz4-java 1.5.0:
```
[success] Total time: 5585 s, completed Sep 26, 2018 5:22:16 PM
```
lz4-java 1.4.0:
```
[success] Total time: 5591 s, completed Sep 26, 2018 5:22:24 PM
```
Some benchmark result:
```
lz4-java 1.5.0 Select 1 row with 500 filters: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
Parquet Vectorized 1953 / 1980 0.0 1952502908.0 1.0X
Parquet Vectorized (Pushdown) 2541 / 2585 0.0 2541019869.0 0.8X
lz4-java 1.4.0 Select 1 row with 500 filters: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------
Parquet Vectorized 1979 / 2103 0.0 1979328144.0 1.0X
Parquet Vectorized (Pushdown) 2596 / 2909 0.0 2596222118.0 0.8X
```
Complete benchmark result:
https://issues.apache.org/jira/secure/attachment/12941360/FilterPushdownBenchmark-lz4-java-140-results.txthttps://issues.apache.org/jira/secure/attachment/12941361/FilterPushdownBenchmark-lz4-java-150-results.txt
## How was this patch tested?
manual tests
Closes#22551 from wangyum/SPARK-25539.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Before ORC 1.5.3, `orc.dictionary.key.threshold` and `hive.exec.orc.dictionary.key.size.threshold` are applied for all columns. This has been a big huddle to enable dictionary encoding. From ORC 1.5.3, `orc.column.encoding.direct` is added to enforce direct encoding selectively in a column-wise manner. This PR aims to add that feature by upgrading ORC from 1.5.2 to 1.5.3.
The followings are the patches in ORC 1.5.3 and this feature is the only one related to Spark directly.
```
ORC-406: ORC: Char(n) and Varchar(n) writers truncate to n bytes & corrupts multi-byte data (gopalv)
ORC-403: [C++] Add checks to avoid invalid offsets in InputStream
ORC-405: Remove calcite as a dependency from the benchmarks.
ORC-375: Fix libhdfs on gcc7 by adding #include <functional> two places.
ORC-383: Parallel builds fails with ConcurrentModificationException
ORC-382: Apache rat exclusions + add rat check to travis
ORC-401: Fix incorrect quoting in specification.
ORC-385: Change RecordReader to extend Closeable.
ORC-384: [C++] fix memory leak when loading non-ORC files
ORC-391: [c++] parseType does not accept underscore in the field name
ORC-397: Allow selective disabling of dictionary encoding. Original patch was by Mithun Radhakrishnan.
ORC-389: Add ability to not decode Acid metadata columns
```
## How was this patch tested?
Pass the Jenkins with newly added test cases.
Closes#22622 from dongjoon-hyun/SPARK-25635.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
Hi all,
Jackson is incompatible with upstream versions, therefore bump the Jackson version to a more recent one. I bumped into some issues with Azure CosmosDB that is using a more recent version of Jackson. This can be fixed by adding exclusions and then it works without any issues. So no breaking changes in the API's.
I would also consider bumping the version of Jackson in Spark. I would suggest to keep up to date with the dependencies, since in the future this issue will pop up more frequently.
## What changes were proposed in this pull request?
Bump Jackson to 2.9.6
## How was this patch tested?
Compiled and tested it locally to see if anything broke.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Closes#21596 from Fokko/fd-bump-jackson.
Authored-by: Fokko Driesprong <fokkodriesprong@godatadriven.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
This patch is to bump the master branch version to 3.0.0-SNAPSHOT.
## How was this patch tested?
N/A
Closes#22606 from gatorsmile/bump3.0.
Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
Update to Scala 2.12.7. See https://issues.apache.org/jira/browse/SPARK-25578 for why.
## How was this patch tested?
Existing tests.
Closes#22600 from srowen/SPARK-25578.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
This PR upgrades Spark's use of Janino from 3.0.9 to 3.0.10.
Note that 3.0.10 is a out-of-band release specifically for fixing an integer overflow issue in Janino's `ClassFile` reader. It is otherwise exactly the same as 3.0.9, so it's a low risk and compatible upgrade.
The integer overflow issue affects Spark SQL's codegen stats collection: when a generated Class file is huge, especially when the constant pool size is above `Short.MAX_VALUE`, Janino's `ClassFile reader` will throw an exception when Spark wants to parse the generated Class file to collect stats. So we'll miss the stats of some huge Class files.
The related Janino issue is: https://github.com/janino-compiler/janino/issues/58
## How was this patch tested?
Existing codegen tests.
Closes#22506 from rednaxelafx/upgrade-janino.
Authored-by: Kris Mok <kris.mok@databricks.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
In the dev list, we can still discuss whether the next version is 2.5.0 or 3.0.0. Let us first bump the master branch version to `2.5.0-SNAPSHOT`.
## How was this patch tested?
N/A
Closes#22426 from gatorsmile/bumpVersionMaster.
Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
How to reproduce permission issue:
```sh
# build spark
./dev/make-distribution.sh --name SPARK-25330 --tgz -Phadoop-2.7 -Phive -Phive-thriftserver -Pyarn
tar -zxf spark-2.4.0-SNAPSHOT-bin-SPARK-25330.tar && cd spark-2.4.0-SNAPSHOT-bin-SPARK-25330
export HADOOP_PROXY_USER=user_a
bin/spark-sql
export HADOOP_PROXY_USER=user_b
bin/spark-sql
```
```java
Exception in thread "main" java.lang.RuntimeException: org.apache.hadoop.security.AccessControlException: Permission denied: user=user_b, access=EXECUTE, inode="/tmp/hive-$%7Buser.name%7D/user_b/668748f2-f6c5-4325-a797-fd0a7ee7f4d4":user_b:hadoop:drwx------
at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.check(FSPermissionChecker.java:319)
at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.checkTraverse(FSPermissionChecker.java:259)
at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.checkPermission(FSPermissionChecker.java:205)
at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.checkPermission(FSPermissionChecker.java:190)
```
The issue occurred in this commit: feb886f209. This pr revert Hadoop 2.7 to 2.7.3 to avoid this issue.
## How was this patch tested?
unit tests and manual tests.
Closes#22327 from wangyum/SPARK-25330.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Upgrade chill to 0.9.3, Kryo to 4.0.2, to get bug fixes and improvements.
The resolved tickets includes:
- SPARK-25258 Upgrade kryo package to version 4.0.2
- SPARK-23131 Kryo raises StackOverflow during serializing GLR model
- SPARK-25176 Kryo fails to serialize a parametrised type hierarchy
More details:
https://github.com/twitter/chill/releases/tag/v0.9.3cc3910d501
## How was this patch tested?
Existing tests.
Closes#22179 from wangyum/SPARK-23131.
Lead-authored-by: Yuming Wang <yumwang@ebay.com>
Co-authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Update to janino 3.0.9 to address Java 8 + Scala 2.12 incompatibility. The error manifests as test failures like this in `ExpressionEncoderSuite`:
```
- encode/decode for seq of string: List(abc, xyz) *** FAILED ***
java.lang.RuntimeException: Error while encoding: org.codehaus.janino.InternalCompilerException: failed to compile: org.codehaus.janino.InternalCompilerException: Compiling "GeneratedClass": Two non-abstract methods "public int scala.collection.TraversableOnce.size()" have the same parameter types, declaring type and return type
```
It comes up pretty immediately in any generated code that references Scala collections, and virtually always concerning the `size()` method.
## How was this patch tested?
Existing tests
Closes#22203 from srowen/SPARK-25029.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
When starting spark-shell from Mac terminal (MacOS High Sirra Version 10.13.6), Getting exception
[ERROR] Failed to construct terminal; falling back to unsupported
java.lang.NumberFormatException: For input string: "0x100"
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Integer.parseInt(Integer.java:580)
at java.lang.Integer.valueOf(Integer.java:766)
at jline.internal.InfoCmp.parseInfoCmp(InfoCmp.java:59)
at jline.UnixTerminal.parseInfoCmp(UnixTerminal.java:242)
at jline.UnixTerminal.<init>(UnixTerminal.java:65)
at jline.UnixTerminal.<init>(UnixTerminal.java:50)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at java.lang.Class.newInstance(Class.java:442)
at jline.TerminalFactory.getFlavor(TerminalFactory.java:211)
This issue is due a jline defect : https://github.com/jline/jline2/issues/281, which is fixed in Jline 2.14.4, bumping up JLine version in spark to version >= Jline 2.14.4 will fix the issue
## How was this patch tested?
No new UT/automation test added, after upgrade to latest Jline version 2.14.6, manually tested spark shell features
Closes#22130 from vinodkc/br_UpgradeJLineVersion.
Authored-by: Vinod KC <vinod.kc.in@gmail.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
Remove jets3t dependency, and bouncy castle which it brings in; update licenses and deps
Note this just takes over https://github.com/apache/spark/pull/21146
## How was this patch tested?
Existing tests.
Closes#22081 from srowen/SPARK-23654.
Authored-by: Sean Owen <srowen@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
This PR has been superceded by #22081
## What changes were proposed in this pull request?
Increment the kinesis client, producer and transient AWS SDK versions to a more recent release.
This is to help with the move off bouncy castle of #21146 and #22081; the goal is that moving up to the new SDK will allow a JVM with unlimited JCE but without bouncy castle to work with Kinesis endpoints.
Why this specific set of artifacts? it syncs up with the 1.11.271 AWS SDK used by hadoop 3.0.3, hadoop-3.1. and hadoop 3.1.1; that's been stable for the uses there (s3, STS, dynamo).
## How was this patch tested?
Running all the external/kinesis-asl tests via maven with java 8.121 & unlimited JCE, without bouncy castle (#21146); default endpoint of us-west.2. Without this SDK update I was getting http cert validation errors, with it they went away.
# This PR is not ready without
* Jenkins test runs to see what it is happy with
* more testing: repeated runs, another endpoint
* looking at the new deprecation warnings and selectively addressing them (the AWS SDKs are pretty aggressive about deprecation, but sometimes they increase the complexity of the client code or block some codepaths off completely)
Closes#22099 from steveloughran/cloud/SPARK-25111-kinesis.
Authored-by: Steve Loughran <stevel@hortonworks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Upgrade Apache Arrow to 0.10.0
Version 0.10.0 has a number of bug fixes and improvements with the following pertaining directly to usage in Spark:
* Allow for adding BinaryType support ARROW-2141
* Bug fix related to array serialization ARROW-1973
* Python2 str will be made into an Arrow string instead of bytes ARROW-2101
* Python bytearrays are supported in as input to pyarrow ARROW-2141
* Java has common interface for reset to cleanup complex vectors in Spark ArrowWriter ARROW-1962
* Cleanup pyarrow type equality checks ARROW-2423
* ArrowStreamWriter should not hold references to ArrowBlocks ARROW-2632, ARROW-2645
* Improved low level handling of messages for RecordBatch ARROW-2704
## How was this patch tested?
existing tests
Author: Bryan Cutler <cutlerb@gmail.com>
Closes#21939 from BryanCutler/arrow-upgrade-010.
## What changes were proposed in this pull request?
Update Jetty to 9.3.24.v20180605 to pick up security fix
## How was this patch tested?
Existing tests.
Closes#22055 from srowen/Jetty9324.
Authored-by: Sean Owen <srowen@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
## What changes were proposed in this pull request?
During upgrading Apache ORC to 1.5.2 ([SPARK-24576](https://issues.apache.org/jira/browse/SPARK-24576)), `sql/core` module overrides the exclusion rules of parent pom file and it causes published `spark-sql_2.1X` artifacts have incomplete exclusion rules ([SPARK-25019](https://issues.apache.org/jira/browse/SPARK-25019)). This PR fixes it by moving the newly added exclusion rule to the parent pom. This also fixes the sbt build hack introduced at that time.
## How was this patch tested?
Pass the existing dependency check and the tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#22003 from dongjoon-hyun/SPARK-25019.
## What changes were proposed in this pull request?
Update Hadoop 2.7 to 2.7.7 to pull in bug and security fixes.
## How was this patch tested?
Existing tests.
Author: Sean Owen <srowen@gmail.com>
Closes#21987 from srowen/SPARK-25015.
## What changes were proposed in this pull request?
Upgrade Apache Avro from 1.7.7 to 1.8.2. The major new features:
1. More logical types. From the spec of 1.8.2 https://avro.apache.org/docs/1.8.2/spec.html#Logical+Types we can see comparing to [1.7.7](https://avro.apache.org/docs/1.7.7/spec.html#Logical+Types), the new version support:
- Date
- Time (millisecond precision)
- Time (microsecond precision)
- Timestamp (millisecond precision)
- Timestamp (microsecond precision)
- Duration
2. Single-object encoding: https://avro.apache.org/docs/1.8.2/spec.html#single_object_encoding
This PR aims to update Apache Spark to support these new features.
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21761 from gengliangwang/upgrade_avro_1.8.
## What changes were proposed in this pull request?
This PR updates maven version from 3.3.9 to 3.5.4. The current build process uses mvn 3.3.9 that was release on 2015, which looks pretty old.
We met [an issue](https://issues.apache.org/jira/browse/SPARK-24895) to need the maven 3.5.2 or later.
The release note of the 3.5.4 is [here](https://maven.apache.org/docs/3.5.4/release-notes.html). Note version 3.4 was skipped.
From [the release note of the 3.5.0](https://maven.apache.org/docs/3.5.0/release-notes.html), the followings are new features:
1. ANSI color logging for improved output visibility
1. add support for module name != artifactId in every calculated URLs (project, SCM, site): special project.directory property
1. create a slf4j-simple provider extension that supports level color rendering
1. ModelResolver interface enhancement: addition of resolveModel(Dependency) supporting version ranges
## How was this patch tested?
Existing tests
Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Closes#21905 from kiszk/SPARK-24956.
## What changes were proposed in this pull request?
Please see [SPARK-24927][1] for more details.
[1]: https://issues.apache.org/jira/browse/SPARK-24927
## How was this patch tested?
Manually tested.
Author: Cheng Lian <lian.cs.zju@gmail.com>
Closes#21879 from liancheng/spark-24927.
(cherry picked from commit d5f340f277)
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
Spotbugs maven plugin was a recently added plugin before 2.4.0 snapshot artifacts were broken. To ensure it does not affect the maven deploy plugin, this change removes it.
## How was this patch tested?
Local build was ran, but this patch will be actually tested by monitoring the apache repo artifacts and making sure metadata is correctly uploaded after this job is ran: https://amplab.cs.berkeley.edu/jenkins/view/Spark%20Packaging/job/spark-master-maven-snapshots/
Author: Eric Chang <eric.chang@databricks.com>
Closes#21865 from ericfchang/SPARK-24895.
## What changes were proposed in this pull request?
Make the integration test script build all modules.
In order to not run all the non-Kubernetes integration tests in the build, support specifying tags and tag all integration tests specifically with "k8s". Supply the k8s tag in the dev/dev-run-integration-tests.sh script.
## How was this patch tested?
The build system will test this.
Author: mcheah <mcheah@palantir.com>
Closes#21800 from mccheah/k8s-integration-tests-maven-fix.
## What changes were proposed in this pull request?
This issue aims to upgrade Apache ORC library from 1.4.4 to 1.5.2 in order to bring the following benefits into Apache Spark.
- [ORC-91](https://issues.apache.org/jira/browse/ORC-91) Support for variable length blocks in HDFS (The current space wasted in ORC to padding is known to be 5%.)
- [ORC-344](https://issues.apache.org/jira/browse/ORC-344) Support for using Decimal64ColumnVector
In addition to that, Apache Hive 3.1 and 3.2 will use ORC 1.5.1 ([HIVE-19669](https://issues.apache.org/jira/browse/HIVE-19465)) and 1.5.2 ([HIVE-19792](https://issues.apache.org/jira/browse/HIVE-19792)) respectively. This will improve the compatibility between Apache Spark and Apache Hive by sharing the common library.
## How was this patch tested?
Pass the Jenkins with all existing tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#21582 from dongjoon-hyun/SPARK-24576.
## What changes were proposed in this pull request?
Apache Avro (https://avro.apache.org) is a popular data serialization format. It is widely used in the Spark and Hadoop ecosystem, especially for Kafka-based data pipelines. Using the external package https://github.com/databricks/spark-avro, Spark SQL can read and write the avro data. Making spark-Avro built-in can provide a better experience for first-time users of Spark SQL and structured streaming. We expect the built-in Avro data source can further improve the adoption of structured streaming.
The proposal is to inline code from spark-avro package (https://github.com/databricks/spark-avro). The target release is Spark 2.4.
[Built-in AVRO Data Source In Spark 2.4.pdf](https://github.com/apache/spark/files/2181511/Built-in.AVRO.Data.Source.In.Spark.2.4.pdf)
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21742 from gengliangwang/export_avro.
## What changes were proposed in this pull request?
This PR enables a Java bytecode check tool [spotbugs](https://spotbugs.github.io/) to avoid possible integer overflow at multiplication. When an violation is detected, the build process is stopped.
Due to the tool limitation, some other checks will be enabled. In this PR, [these patterns](http://spotbugs-in-kengo-toda.readthedocs.io/en/lqc-list-detectors/detectors.html#findpuzzlers) in `FindPuzzlers` can be detected.
This check is enabled at `compile` phase. Thus, `mvn compile` or `mvn package` launches this check.
## How was this patch tested?
Existing UTs
Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Closes#21542 from kiszk/SPARK-24529.
## What changes were proposed in this pull request?
- disables maven surfire plugin to allow tags function properly, doc here: http://www.scalatest.org/user_guide/using_the_scalatest_maven_plugin
## How was this patch tested?
Manually by adding tags.
Author: Stavros Kontopoulos <stavros.kontopoulos@lightbend.com>
Closes#21697 from skonto/fix-tags.
## What changes were proposed in this pull request?
Upgrade ASM to 6.1 to support JDK9+
## How was this patch tested?
Existing tests.
Author: DB Tsai <d_tsai@apple.com>
Closes#21459 from dbtsai/asm.
## What changes were proposed in this pull request?
Scala is upgraded to `2.11.12` and `2.12.6`.
We used `loadFIles()` in `ILoop` as a hook to initialize the Spark before REPL sees any files in Scala `2.11.8`. However, it was a hack, and it was not intended to be a public API, so it was removed in Scala `2.11.12`.
From the discussion in Scala community, https://github.com/scala/bug/issues/10913 , we can use `initializeSynchronous` to initialize Spark instead. This PR implements the Spark initialization there.
However, in Scala `2.11.12`'s `ILoop.scala`, in function `def startup()`, the first thing it calls is `printWelcome()`. As a result, Scala will call `printWelcome()` and `splash` before calling `initializeSynchronous`.
Thus, the Spark shell will allow users to type commends first, and then show the Spark UI URL. It's working, but it will change the Spark Shell interface as the following.
```scala
➜ apache-spark git:(scala-2.11.12) ✗ ./bin/spark-shell
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.4.0-SNAPSHOT
/_/
Using Scala version 2.11.12 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_161)
Type in expressions to have them evaluated.
Type :help for more information.
scala> Spark context Web UI available at http://192.168.1.169:4040
Spark context available as 'sc' (master = local[*], app id = local-1528180279528).
Spark session available as 'spark'.
scala>
```
It seems there is no easy way to inject the Spark initialization code in the proper place as Scala doesn't provide a hook. Maybe som-snytt can comment on this.
The following command is used to update the dep files.
```scala
./dev/test-dependencies.sh --replace-manifest
```
## How was this patch tested?
Existing tests
Author: DB Tsai <d_tsai@apple.com>
Closes#21495 from dbtsai/scala-2.11.12.
## What changes were proposed in this pull request?
Previously, the scheduler backend was maintaining state in many places, not only for reading state but also writing to it. For example, state had to be managed in both the watch and in the executor allocator runnable. Furthermore, one had to keep track of multiple hash tables.
We can do better here by:
1. Consolidating the places where we manage state. Here, we take inspiration from traditional Kubernetes controllers. These controllers tend to follow a level-triggered mechanism. This means that the controller will continuously monitor the API server via watches and polling, and on periodic passes, the controller will reconcile the current state of the cluster with the desired state. We implement this by introducing the concept of a pod snapshot, which is a given state of the executors in the Kubernetes cluster. We operate periodically on snapshots. To prevent overloading the API server with polling requests to get the state of the cluster (particularly for executor allocation where we want to be checking frequently to get executors to launch without unbearably bad latency), we use watches to populate snapshots by applying observed events to a previous snapshot to get a new snapshot. Whenever we do poll the cluster, the polled state replaces any existing snapshot - this ensures eventual consistency and mirroring of the cluster, as is desired in a level triggered architecture.
2. Storing less specialized in-memory state in general. Previously we were creating hash tables to represent the state of executors. Instead, it's easier to represent state solely by the snapshots.
## How was this patch tested?
Integration tests should test there's no regressions end to end. Unit tests to be updated, in particular focusing on different orderings of events, particularly accounting for when events come in unexpected ordering.
Author: mcheah <mcheah@palantir.com>
Closes#21366 from mccheah/event-queue-driven-scheduling.
These tests were developed in the https://github.com/apache-spark-on-k8s/spark-integration repo
by several contributors. This is a copy of the current state into the main apache spark repo.
The only changes from the current spark-integration repo state are:
* Move the files from the repo root into resource-managers/kubernetes/integration-tests
* Add a reference to these tests in the root README.md
* Fix a path reference in dev/dev-run-integration-tests.sh
* Add a TODO in include/util.sh
## What changes were proposed in this pull request?
Incorporation of Kubernetes integration tests.
## How was this patch tested?
This code has its own unit tests, but the main purpose is to provide the integration tests.
I tested this on my laptop by running dev/dev-run-integration-tests.sh --spark-tgz ~/spark-2.4.0-SNAPSHOT-bin--.tgz
The spark-integration tests have already been running for months in AMPLab, here is an example:
https://amplab.cs.berkeley.edu/jenkins/job/testing-k8s-scheduled-spark-integration-master/
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Sean Suchter <sean-github@suchter.com>
Author: Sean Suchter <ssuchter@pepperdata.com>
Closes#20697 from ssuchter/ssuchter-k8s-integration-tests.
## What changes were proposed in this pull request?
ORC 1.4.4 includes [nine fixes](https://issues.apache.org/jira/issues/?filter=12342568&jql=project%20%3D%20ORC%20AND%20resolution%20%3D%20Fixed%20AND%20fixVersion%20%3D%201.4.4). One of the issues is about `Timestamp` bug (ORC-306) which occurs when `native` ORC vectorized reader reads ORC column vector's sub-vector `times` and `nanos`. ORC-306 fixes this according to the [original definition](https://github.com/apache/hive/blob/master/storage-api/src/java/org/apache/hadoop/hive/ql/exec/vector/TimestampColumnVector.java#L45-L46) and this PR includes the updated interpretation on ORC column vectors. Note that `hive` ORC reader and ORC MR reader is not affected.
```scala
scala> spark.version
res0: String = 2.3.0
scala> spark.sql("set spark.sql.orc.impl=native")
scala> Seq(java.sql.Timestamp.valueOf("1900-05-05 12:34:56.000789")).toDF().write.orc("/tmp/orc")
scala> spark.read.orc("/tmp/orc").show(false)
+--------------------------+
|value |
+--------------------------+
|1900-05-05 12:34:55.000789|
+--------------------------+
```
This PR aims to update Apache Spark to use it.
**FULL LIST**
ID | TITLE
-- | --
ORC-281 | Fix compiler warnings from clang 5.0
ORC-301 | `extractFileTail` should open a file in `try` statement
ORC-304 | Fix TestRecordReaderImpl to not fail with new storage-api
ORC-306 | Fix incorrect workaround for bug in java.sql.Timestamp
ORC-324 | Add support for ARM and PPC arch
ORC-330 | Remove unnecessary Hive artifacts from root pom
ORC-332 | Add syntax version to orc_proto.proto
ORC-336 | Remove avro and parquet dependency management entries
ORC-360 | Implement error checking on subtype fields in Java
## How was this patch tested?
Pass the Jenkins.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#21372 from dongjoon-hyun/SPARK_ORC144.
## What changes were proposed in this pull request?
This updates Parquet to 1.10.0 and updates the vectorized path for buffer management changes. Parquet 1.10.0 uses ByteBufferInputStream instead of byte arrays in encoders. This allows Parquet to break allocations into smaller chunks that are better for garbage collection.
## How was this patch tested?
Existing Parquet tests. Running in production at Netflix for about 3 months.
Author: Ryan Blue <blue@apache.org>
Closes#21070 from rdblue/SPARK-23972-update-parquet-to-1.10.0.
## What changes were proposed in this pull request?
1. Adds a `hadoop-3.1` profile build depending on the hadoop-3.1 artifacts.
1. In the hadoop-cloud module, adds an explicit hadoop-3.1 profile which switches from explicitly pulling in cloud connectors (hadoop-openstack, hadoop-aws, hadoop-azure) to depending on the hadoop-cloudstorage POM artifact, which pulls these in, has pre-excluded things like hadoop-common, and stays up to date with new connectors (hadoop-azuredatalake, hadoop-allyun). Goal: it becomes the Hadoop projects homework of keeping this clean, and the spark project doesn't need to handle new hadoop releases adding more dependencies.
1. the hadoop-cloud/hadoop-3.1 profile also declares support for jetty-ajax and jetty-util to ensure that these jars get into the distribution jar directory when needed by unshaded libraries.
1. Increases the curator and zookeeper versions to match those in hadoop-3, fixing spark core to build in sbt with the hadoop-3 dependencies.
## How was this patch tested?
* Everything this has been built and tested against both ASF Hadoop branch-3.1 and hadoop trunk.
* spark-shell was used to create connectors to all the stores and verify that file IO could take place.
The spark hive-1.2.1 JAR has problems here, as it's version check logic fails for Hadoop versions > 2.
This can be avoided with either of
* The hadoop JARs built to declare their version as Hadoop 2.11 `mvn install -DskipTests -DskipShade -Ddeclared.hadoop.version=2.11` . This is safe for local test runs, not for deployment (HDFS is very strict about cross-version deployment).
* A modified version of spark hive whose version check switch statement is happy with hadoop 3.
I've done both, with maven and SBT.
Three issues surfaced
1. A spark-core test failure —fixed in SPARK-23787.
1. SBT only: Zookeeper not being found in spark-core. Somehow curator 2.12.0 triggers some slightly different dependency resolution logic from previous versions, and Ivy was missing zookeeper.jar entirely. This patch adds the explicit declaration for all spark profiles, setting the ZK version = 3.4.9 for hadoop-3.1
1. Marking jetty-utils as provided in spark was stopping hadoop-azure from being able to instantiate the azure wasb:// client; it was using jetty-util-ajax, which could then not find a class in jetty-util.
Author: Steve Loughran <stevel@hortonworks.com>
Closes#20923 from steveloughran/cloud/SPARK-23807-hadoop-31.
## What changes were proposed in this pull request?
This PR avoids version conflicts of `commons-net` by upgrading commons-net from 2.2 to 3.1. We are seeing the following message during the build using sbt.
```
[warn] Found version conflict(s) in library dependencies; some are suspected to be binary incompatible:
...
[warn] * commons-net:commons-net:3.1 is selected over 2.2
[warn] +- org.apache.hadoop:hadoop-common:2.6.5 (depends on 3.1)
[warn] +- org.apache.spark:spark-core_2.11:2.4.0-SNAPSHOT (depends on 2.2)
[warn]
```
[Here](https://commons.apache.org/proper/commons-net/changes-report.html) is a release history.
[Here](https://commons.apache.org/proper/commons-net/migration.html) is a migration guide from 2.x to 3.0.
## How was this patch tested?
Existing tests
Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Closes#20672 from kiszk/SPARK-23509.
## What changes were proposed in this pull request?
This PR updates Apache ORC dependencies to 1.4.3 released on February 9th. Apache ORC 1.4.2 release removes unnecessary dependencies and 1.4.3 has 5 more patches (https://s.apache.org/Fll8).
Especially, the following ORC-285 is fixed at 1.4.3.
```scala
scala> val df = Seq(Array.empty[Float]).toDF()
scala> df.write.format("orc").save("/tmp/floatarray")
scala> spark.read.orc("/tmp/floatarray")
res1: org.apache.spark.sql.DataFrame = [value: array<float>]
scala> spark.read.orc("/tmp/floatarray").show()
18/02/12 22:09:10 ERROR Executor: Exception in task 0.0 in stage 1.0 (TID 1)
java.io.IOException: Error reading file: file:/tmp/floatarray/part-00000-9c0b461b-4df1-4c23-aac1-3e4f349ac7d6-c000.snappy.orc
at org.apache.orc.impl.RecordReaderImpl.nextBatch(RecordReaderImpl.java:1191)
at org.apache.orc.mapreduce.OrcMapreduceRecordReader.ensureBatch(OrcMapreduceRecordReader.java:78)
...
Caused by: java.io.EOFException: Read past EOF for compressed stream Stream for column 2 kind DATA position: 0 length: 0 range: 0 offset: 0 limit: 0
```
## How was this patch tested?
Pass the Jenkins test.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#20511 from dongjoon-hyun/SPARK-23340.
## What changes were proposed in this pull request?
This PR upgrade snappy-java from 1.1.2.6 to 1.1.7.1.
1.1.7.1 release notes:
- Improved performance for big-endian architecture
- The other performance improvement in [snappy-1.1.5](https://github.com/google/snappy/releases/tag/1.1.5)
1.1.4 release notes:
- Fix a 1% performance regression when snappy is used in PIE executables.
- Improve compression performance by 5%.
- Improve decompression performance by 20%.
More details:
https://github.com/xerial/snappy-java/blob/master/Milestone.md
## How was this patch tested?
manual tests
Author: Yuming Wang <wgyumg@gmail.com>
Closes#20510 from wangyum/SPARK-23336.
## What changes were proposed in this pull request?
This PR proposes to explicitly specify Pandas and PyArrow versions in PySpark tests to skip or test.
We declared the extra dependencies:
b8bfce51ab/python/setup.py (L204)
In case of PyArrow:
Currently we only check if pyarrow is installed or not without checking the version. It already fails to run tests. For example, if PyArrow 0.7.0 is installed:
```
======================================================================
ERROR: test_vectorized_udf_wrong_return_type (pyspark.sql.tests.ScalarPandasUDF)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/.../spark/python/pyspark/sql/tests.py", line 4019, in test_vectorized_udf_wrong_return_type
f = pandas_udf(lambda x: x * 1.0, MapType(LongType(), LongType()))
File "/.../spark/python/pyspark/sql/functions.py", line 2309, in pandas_udf
return _create_udf(f=f, returnType=return_type, evalType=eval_type)
File "/.../spark/python/pyspark/sql/udf.py", line 47, in _create_udf
require_minimum_pyarrow_version()
File "/.../spark/python/pyspark/sql/utils.py", line 132, in require_minimum_pyarrow_version
"however, your version was %s." % pyarrow.__version__)
ImportError: pyarrow >= 0.8.0 must be installed on calling Python process; however, your version was 0.7.0.
----------------------------------------------------------------------
Ran 33 tests in 8.098s
FAILED (errors=33)
```
In case of Pandas:
There are few tests for old Pandas which were tested only when Pandas version was lower, and I rewrote them to be tested when both Pandas version is lower and missing.
## How was this patch tested?
Manually tested by modifying the condition:
```
test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 1.19.2 must be installed; however, your version was 0.19.2.'
test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 1.19.2 must be installed; however, your version was 0.19.2.'
test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 1.19.2 must be installed; however, your version was 0.19.2.'
```
```
test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
```
```
test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 1.8.0 must be installed; however, your version was 0.8.0.'
test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 1.8.0 must be installed; however, your version was 0.8.0.'
test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 1.8.0 must be installed; however, your version was 0.8.0.'
```
```
test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 0.8.0 must be installed; however, it was not found.'
test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 0.8.0 must be installed; however, it was not found.'
test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'PyArrow >= 0.8.0 must be installed; however, it was not found.'
```
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#20487 from HyukjinKwon/pyarrow-pandas-skip.
## What changes were proposed in this pull request?
Spark still use a few years old version 3.2.11. This change is to upgrade json4s to 3.5.3.
Note that this change does not include the Jackson update because the Jackson version referenced in json4s 3.5.3 is 2.8.4, which has a security vulnerability ([see](https://issues.apache.org/jira/browse/SPARK-20433)).
## How was this patch tested?
Existing unit tests and build.
Author: shimamoto <chibochibo@gmail.com>
Closes#20233 from shimamoto/upgrade-json4s.
## What changes were proposed in this pull request?
This patch bumps the master branch version to `2.4.0-SNAPSHOT`.
## How was this patch tested?
N/A
Author: gatorsmile <gatorsmile@gmail.com>
Closes#20222 from gatorsmile/bump24.
Hi all,
I would like to bump the PATCH versions of both the Apache httpclient Apache httpcore. I use the SparkTC Stocator library for connecting to an object store, and I would align the versions to reduce java version mismatches. Furthermore it is good to bump these versions since they fix stability and performance issues:
https://archive.apache.org/dist/httpcomponents/httpclient/RELEASE_NOTES-4.5.x.txthttps://www.apache.org/dist/httpcomponents/httpcore/RELEASE_NOTES-4.4.x.txt
Cheers, Fokko
## What changes were proposed in this pull request?
Update the versions of the httpclient and httpcore. Only update the PATCH versions, so no breaking changes.
## 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)
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Fokko Driesprong <fokkodriesprong@godatadriven.com>
Closes#20103 from Fokko/SPARK-22919-bump-httpclient-versions.
## What changes were proposed in this pull request?
Add tarLongFileMode=posix configuration for the assembly plugin
## How was this patch tested?
Reran build successfully
```
./build/mvn package -Pbigtop-dist -DskipTests -rf :spark-assembly_2.11
[INFO] Spark Project Assembly ............................. SUCCESS [ 23.082 s]
```
Author: Gera Shegalov <gshegalov@salesforce.com>
Closes#20055 from gerashegalov/gera/tarLongFileMode.
## What changes were proposed in this pull request?
Upgrade Spark to Arrow 0.8.0 for Java and Python. Also includes an upgrade of Netty to 4.1.17 to resolve dependency requirements.
The highlights that pertain to Spark for the update from Arrow versoin 0.4.1 to 0.8.0 include:
* Java refactoring for more simple API
* Java reduced heap usage and streamlined hot code paths
* Type support for DecimalType, ArrayType
* Improved type casting support in Python
* Simplified type checking in Python
## How was this patch tested?
Existing tests
Author: Bryan Cutler <cutlerb@gmail.com>
Author: Shixiong Zhu <zsxwing@gmail.com>
Closes#19884 from BryanCutler/arrow-upgrade-080-SPARK-22324.
## What changes were proposed in this pull request?
Update Bouncy Castle to 1.58, and jets3t to 0.9.4 to (sort of) match.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#19859 from srowen/SPARK-22634.
… with Janino when compiling generated code.
## What changes were proposed in this pull request?
Bump up Janino dependency version to fix thread safety issue during compiling generated code
## How was this patch tested?
Check https://issues.apache.org/jira/browse/SPARK-22373 for details.
Converted part of the code in CodeGenerator into a standalone application, so the issue can be consistently reproduced locally.
Verified that changing Janino dependency version resolved this issue.
Author: Min Shen <mshen@linkedin.com>
Closes#19839 from Victsm/SPARK-22373.
## What changes were proposed in this pull request?
This is a stripped down version of the `KubernetesClusterSchedulerBackend` for Spark with the following components:
- Static Allocation of Executors
- Executor Pod Factory
- Executor Recovery Semantics
It's step 1 from the step-wise plan documented [here](https://github.com/apache-spark-on-k8s/spark/issues/441#issuecomment-330802935).
This addition is covered by the [SPIP vote](http://apache-spark-developers-list.1001551.n3.nabble.com/SPIP-Spark-on-Kubernetes-td22147.html) which passed on Aug 31 .
## How was this patch tested?
- The patch contains unit tests which are passing.
- Manual testing: `./build/mvn -Pkubernetes clean package` succeeded.
- It is a **subset** of the entire changelist hosted in http://github.com/apache-spark-on-k8s/spark which is in active use in several organizations.
- There is integration testing enabled in the fork currently [hosted by PepperData](spark-k8s-jenkins.pepperdata.org:8080) which is being moved over to RiseLAB CI.
- Detailed documentation on trying out the patch in its entirety is in: https://apache-spark-on-k8s.github.io/userdocs/running-on-kubernetes.html
cc rxin felixcheung mateiz (shepherd)
k8s-big-data SIG members & contributors: mccheah ash211 ssuchter varunkatta kimoonkim erikerlandson liyinan926 tnachen ifilonenko
Author: Yinan Li <liyinan926@gmail.com>
Author: foxish <ramanathana@google.com>
Author: mcheah <mcheah@palantir.com>
Closes#19468 from foxish/spark-kubernetes-3.
## What changes were proposed in this pull request?
Set `-ea` and `-Xss4m` consistently for tests, to fix in particular:
```
OrderingSuite:
...
- GenerateOrdering with ShortType
*** RUN ABORTED ***
java.lang.StackOverflowError:
at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:370)
at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
at org.codehaus.janino.CodeContext.flowAnalysis(CodeContext.java:541)
...
```
## How was this patch tested?
Existing tests. Manually verified it resolves the StackOverflowError this intends to resolve.
Author: Sean Owen <sowen@cloudera.com>
Closes#19820 from srowen/SPARK-22607.
## What changes were proposed in this pull request?
Use repo.maven.apache.org repo address; use latest ASF parent POM version 18
## How was this patch tested?
Existing tests; no functional change
Author: Sean Owen <sowen@cloudera.com>
Closes#19742 from srowen/SPARK-22511.
## What changes were proposed in this pull request?
Spark REPL changes for Scala 2.12.4: use command(), not processLine() in ILoop; remove direct dependence on older jline. Not sure whether this became needed in 2.12.4 or just missed this before. This makes spark-shell work in 2.12.
## How was this patch tested?
Existing tests; manual run of spark-shell in 2.11, 2.12 builds
Author: Sean Owen <sowen@cloudera.com>
Closes#19612 from srowen/SPARK-14650.2.
## What changes were proposed in this pull request?
Using zstd compression for Spark jobs spilling 100s of TBs of data, we could reduce the amount of data written to disk by as much as 50%. This translates to significant latency gain because of reduced disk io operations. There is a degradation CPU time by 2 - 5% because of zstd compression overhead, but for jobs which are bottlenecked by disk IO, this hit can be taken.
## Benchmark
Please note that this benchmark is using real world compute heavy production workload spilling TBs of data to disk
| | zstd performance as compred to LZ4 |
| ------------- | -----:|
| spill/shuffle bytes | -48% |
| cpu time | + 3% |
| cpu reservation time | -40%|
| latency | -40% |
## How was this patch tested?
Tested by running few jobs spilling large amount of data on the cluster and amount of intermediate data written to disk reduced by as much as 50%.
Author: Sital Kedia <skedia@fb.com>
Closes#18805 from sitalkedia/skedia/upstream_zstd.
## What changes were proposed in this pull request?
Scala 2.12's `Future` defines two new methods to implement, `transform` and `transformWith`. These can be implemented naturally in Spark's `FutureAction` extension and subclasses, but, only in terms of the new methods that don't exist in Scala 2.11. To support both at the same time, reflection is used to implement these.
## How was this patch tested?
Existing tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#19561 from srowen/SPARK-22322.
## What changes were proposed in this pull request?
Apache ORC 1.4.1 is released yesterday.
- https://orc.apache.org/news/2017/10/16/ORC-1.4.1/
Like ORC-233 (Allow `orc.include.columns` to be empty), there are several important fixes.
This PR updates Apache ORC dependency to use the latest one, 1.4.1.
## How was this patch tested?
Pass the Jenkins.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#19521 from dongjoon-hyun/SPARK-22300.
## What changes were proposed in this pull request?
Move flume behind a profile, take 2. See https://github.com/apache/spark/pull/19365 for most of the back-story.
This change should fix the problem by removing the examples module dependency and moving Flume examples to the module itself. It also adds deprecation messages, per a discussion on dev about deprecating for 2.3.0.
## How was this patch tested?
Existing tests, which still enable flume integration.
Author: Sean Owen <sowen@cloudera.com>
Closes#19412 from srowen/SPARK-22142.2.
## What changes were proposed in this pull request?
Add 'flume' profile to enable Flume-related integration modules
## How was this patch tested?
Existing tests; no functional change
Author: Sean Owen <sowen@cloudera.com>
Closes#19365 from srowen/SPARK-22142.
## What changes were proposed in this pull request?
Un-manage jackson-module-paranamer version to let it use the version desired by jackson-module-scala; manage paranamer up from 2.8 for jackson-module-scala 2.7.9, to override avro 1.7.7's desired paranamer 2.3
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#19352 from srowen/SPARK-22128.
## What changes were proposed in this pull request?
Fix finalizer checkstyle violation by just turning it off; re-disable checkstyle as it won't be run by SBT PR builder. See https://github.com/apache/spark/pull/18887#issuecomment-332580700
## How was this patch tested?
`./dev/lint-java` runs successfully
Author: Sean Owen <sowen@cloudera.com>
Closes#19371 from srowen/HotfixFinalizerCheckstlye.
## What changes were proposed in this pull request?
See https://github.com/apache/spark/pull/19282
Revert scala-maven-plugin to 3.2.2 to work with Maven+zinc again
## How was this patch tested?
Reproduced locally with zinc, and confirmed this removes the problem.
Author: Sean Owen <sowen@cloudera.com>
Closes#19292 from srowen/SPARK-22066.2.
## What changes were proposed in this pull request?
Update plugins, including scala-maven-plugin, to latest versions. Update checkstyle to 8.2. Remove bogus checkstyle config and enable it. Fix existing and new Java checkstyle errors.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#19282 from srowen/SPARK-22066.
## What changes were proposed in this pull request?
Upgrade codahale metrics library so that Graphite constructor can re-resolve hosts behind a CNAME with re-tried DNS lookups. When Graphite is deployed behind an ELB, ELB may change IP addresses based on auto-scaling needs. Using current approach yields Graphite usage impossible, fixing for that use case
- Upgrade to codahale 3.1.5
- Use new Graphite(host, port) constructor instead of new Graphite(new InetSocketAddress(host, port)) constructor
## How was this patch tested?
The same logic is used for another project that is using the same configuration and code path, and graphite re-connect's behind ELB's are no longer an issue
This are proposed changes for codahale lib - https://github.com/dropwizard/metrics/compare/v3.1.2...v3.1.5#diff-6916c85d2dd08d89fe771c952e3b8512R120. Specifically, b4d246d34e/metrics-graphite/src/main/java/com/codahale/metrics/graphite/Graphite.java (L120)
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: alexmnyc <project@alexandermarkham.com>
Closes#19210 from alexmnyc/patch-1.
## What changes were proposed in this pull request?
Put Kafka 0.8 support behind a kafka-0-8 profile.
## How was this patch tested?
Existing tests, but, until PR builder and Jenkins configs are updated the effect here is to not build or test Kafka 0.8 support at all.
Author: Sean Owen <sowen@cloudera.com>
Closes#19134 from srowen/SPARK-21893.
## What changes were proposed in this pull request?
This PR proposes to match scalastyle version in POM and SparkBuild.scala
## How was this patch tested?
Manual builds.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#19146 from HyukjinKwon/SPARK-21903-follow-up.
## What changes were proposed in this pull request?
This PR exposes Netty memory usage for Spark's `TransportClientFactory` and `TransportServer`, including the details of each direct arena and heap arena metrics, as well as aggregated metrics. The purpose of adding the Netty metrics is to better know the memory usage of Netty in Spark shuffle, rpc and others network communications, and guide us to better configure the memory size of executors.
This PR doesn't expose these metrics to any sink, to leverage this feature, still requires to connect to either MetricsSystem or collect them back to Driver to display.
## How was this patch tested?
Add Unit test to verify it, also manually verified in real cluster.
Author: jerryshao <sshao@hortonworks.com>
Closes#18935 from jerryshao/SPARK-9104.
…build; fix some things that will be warnings or errors in 2.12; restore Scala 2.12 profile infrastructure
## What changes were proposed in this pull request?
This change adds back the infrastructure for a Scala 2.12 build, but does not enable it in the release or Python test scripts.
In order to make that meaningful, it also resolves compile errors that the code hits in 2.12 only, in a way that still works with 2.11.
It also updates dependencies to the earliest minor release of dependencies whose current version does not yet support Scala 2.12. This is in a sense covered by other JIRAs under the main umbrella, but implemented here. The versions below still work with 2.11, and are the _latest_ maintenance release in the _earliest_ viable minor release.
- Scalatest 2.x -> 3.0.3
- Chill 0.8.0 -> 0.8.4
- Clapper 1.0.x -> 1.1.2
- json4s 3.2.x -> 3.4.2
- Jackson 2.6.x -> 2.7.9 (required by json4s)
This change does _not_ fully enable a Scala 2.12 build:
- It will also require dropping support for Kafka before 0.10. Easy enough, just didn't do it yet here
- It will require recreating `SparkILoop` and `Main` for REPL 2.12, which is SPARK-14650. Possible to do here too.
What it does do is make changes that resolve much of the remaining gap without affecting the current 2.11 build.
## How was this patch tested?
Existing tests and build. Manually tested with `./dev/change-scala-version.sh 2.12` to verify it compiles, modulo the exceptions above.
Author: Sean Owen <sowen@cloudera.com>
Closes#18645 from srowen/SPARK-14280.
## What changes were proposed in this pull request?
Fix build warnings and Java lint errors. This just helps a bit in evaluating (new) warnings in another PR I have open.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#19051 from srowen/JavaWarnings.
## What changes were proposed in this pull request?
This PR bumps the ANTLR version to 4.7, and fixes a number of small parser related issues uncovered by the bump.
The main reason for upgrading is that in some cases the current version of ANTLR (4.5) can exhibit exponential slowdowns if it needs to parse boolean predicates. For example the following query will take forever to parse:
```sql
SELECT *
FROM RANGE(1000)
WHERE
TRUE
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
AND NOT upper(DESCRIPTION) LIKE '%FOO%'
```
This is caused by a know bug in ANTLR (https://github.com/antlr/antlr4/issues/994), which was fixed in version 4.6.
## How was this patch tested?
Existing tests.
Author: Herman van Hovell <hvanhovell@databricks.com>
Closes#19042 from hvanhovell/SPARK-21830.
## What changes were proposed in this pull request?
Like Parquet, this PR aims to depend on the latest Apache ORC 1.4 for Apache Spark 2.3. There are key benefits for Apache ORC 1.4.
- Stability: Apache ORC 1.4.0 has many fixes and we can depend on ORC community more.
- Maintainability: Reduce the Hive dependency and can remove old legacy code later.
Later, we can get the following two key benefits by adding new ORCFileFormat in SPARK-20728 (#17980), too.
- Usability: User can use ORC data sources without hive module, i.e, -Phive.
- Speed: Use both Spark ColumnarBatch and ORC RowBatch together. This will be faster than the current implementation in Spark.
## How was this patch tested?
Pass the jenkins.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#18640 from dongjoon-hyun/SPARK-21422.
This version fixes a few issues in the import order checker; it provides
better error messages, and detects more improper ordering (thus the need
to change a lot of files in this patch). The main fix is that it correctly
complains about the order of packages vs. classes.
As part of the above, I moved some "SparkSession" import in ML examples
inside the "$example on$" blocks; that didn't seem consistent across
different source files to start with, and avoids having to add more on/off blocks
around specific imports.
The new scalastyle also seems to have a better header detector, so a few
license headers had to be updated to match the expected indentation.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#18943 from vanzin/SPARK-21731.
## What changes were proposed in this pull request?
This pr updated `lz4-java` to the latest (v1.4.0) and removed custom `LZ4BlockInputStream`. We currently use custom `LZ4BlockInputStream` to read concatenated byte stream in shuffle. But, this functionality has been implemented in the latest lz4-java (https://github.com/lz4/lz4-java/pull/105). So, we might update the latest to remove the custom `LZ4BlockInputStream`.
Major diffs between the latest release and v1.3.0 in the master are as follows (62f7547abb...6d4693f562);
- fixed NPE in XXHashFactory similarly
- Don't place resources in default package to support shading
- Fixes ByteBuffer methods failing to apply arrayOffset() for array-backed
- Try to load lz4-java from java.library.path, then fallback to bundled
- Add ppc64le binary
- Add s390x JNI binding
- Add basic LZ4 Frame v1.5.0 support
- enable aarch64 support for lz4-java
- Allow unsafeInstance() for ppc64le archiecture
- Add unsafeInstance support for AArch64
- Support 64-bit JNI build on Solaris
- Avoid over-allocating a buffer
- Allow EndMark to be incompressible for LZ4FrameInputStream.
- Concat byte stream
## How was this patch tested?
Existing tests.
Author: Takeshi Yamamuro <yamamuro@apache.org>
Closes#18883 from maropu/SPARK-21276.
## What changes were proposed in this pull request?
Update breeze to 0.13.1 for an emergency bugfix in strong wolfe line search
https://github.com/scalanlp/breeze/pull/651
## How was this patch tested?
N/A
Author: WeichenXu <WeichenXu123@outlook.com>
Closes#18797 from WeichenXu123/update-breeze.
## What changes were proposed in this pull request?
Taking over https://github.com/apache/spark/pull/18789 ; Closes#18789
Update Jackson to 2.6.7 uniformly, and some components to 2.6.7.1, to get some fixes and prep for Scala 2.12
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#18881 from srowen/SPARK-20433.
