### What changes were proposed in this pull request?
This:
1. switches Spark to use shaded Hadoop clients, namely hadoop-client-api and hadoop-client-runtime, for Hadoop 3.x.
2. upgrade built-in version for Hadoop 3.x to Hadoop 3.2.2
Note that for Hadoop 2.7, we'll still use the same modules such as hadoop-client.
In order to still keep default Hadoop profile to be hadoop-3.2, this defines the following Maven properties:
```
hadoop-client-api.artifact
hadoop-client-runtime.artifact
hadoop-client-minicluster.artifact
```
which default to:
```
hadoop-client-api
hadoop-client-runtime
hadoop-client-minicluster
```
but all switch to `hadoop-client` when the Hadoop profile is hadoop-2.7. A side affect from this is we'll import the same dependency multiple times. For this I have to disable Maven enforcer `banDuplicatePomDependencyVersions`.
Besides above, there are the following changes:
- explicitly add a few dependencies which are imported via transitive dependencies from Hadoop jars, but are removed from the shaded client jars.
- removed the use of `ProxyUriUtils.getPath` from `ApplicationMaster` which is a server-side/private API.
- modified `IsolatedClientLoader` to exclude `hadoop-auth` jars when Hadoop version is 3.x. This change should only matter when we're not sharing Hadoop classes with Spark (which is _mostly_ used in tests).
### Why are the changes needed?
Hadoop 3.2.2 is released with new features and bug fixes, so it's good for the Spark community to adopt it. However, latest Hadoop versions starting from Hadoop 3.2.1 have upgraded to use Guava 27+. In order to resolve Guava conflicts, this takes the approach by switching to shaded client jars provided by Hadoop. This also has the benefits of avoid pulling other 3rd party dependencies from Hadoop side so as to avoid more potential future conflicts.
### Does this PR introduce _any_ user-facing change?
When people use Spark with `hadoop-provided` option, they should make sure class path contains `hadoop-client-api` and `hadoop-client-runtime` jars. In addition, they may need to make sure these jars appear before other Hadoop jars in the order. Otherwise, classes may be loaded from the other non-shaded Hadoop jars and cause potential conflicts.
### How was this patch tested?
Relying on existing tests.
Closes#30701 from sunchao/test-hadoop-3.2.2.
Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR upgrade Py4J from 0.10.9 to 0.10.9.1 that contains some bug fixes and improvements.
It contains one bug fix (4152353ac1).
### Why are the changes needed?
To leverage fixes from the upstream in Py4J.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Jenkins build and GitHub Actions will test it out.
Closes#31009 from HyukjinKwon/SPARK-33984.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to update commons-lang3 to 3.11 to support Java 16+ better.
### Why are the changes needed?
commons-lang3 has the following bug fixes and Java 16 support.
- https://commons.apache.org/proper/commons-lang/changes-report.html#a3.11
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
Pass the CIs.
Closes#30990 from williamhyun/Commons-lang3.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR proposes to fix the `Dockerfile` for Spark release.
- Port b135db3b1a to `Dockerfile`
- Upgrade Ubuntu 18.04 -> 20.04 (because of porting b135db3)
- Remove Python 2 (because of Ubuntu upgrade)
- Use built-in Python 3.8.5 (because of Ubuntu upgrade)
- Node.js 11 -> 12 (because of Ubuntu upgrade)
- Ruby 2.5 -> 2.7 (because of Ubuntu upgrade)
- Python dependencies and Jekyll + plugins upgrade to the latest as it's used in GitHub Actions build (unrelated to the issue itself)
### Why are the changes needed?
To make a Spark release :-).
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Manually tested via:
```bash
cd dev/create-release/spark-rm
docker build -t spark-rm --build-arg UID=$UID .
```
```
...
Successfully built 516d7943634f
Successfully tagged spark-rm:latest
```
Closes#30971 from HyukjinKwon/SPARK-33927.
Lead-authored-by: Hyukjin Kwon <gurwls223@apache.org>
Co-authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to upgrade Zstd library to 1.4.8.
### Why are the changes needed?
This will bring Zstd 1.4.7 and 1.4.8 improvement and bug fixes and the following from `zstd-jni`.
- https://github.com/facebook/zstd/releases/tag/v1.4.7
- https://github.com/facebook/zstd/releases/tag/v1.4.8
- https://github.com/luben/zstd-jni/issues/153 (Apple M1 architecture)
### Does this PR introduce _any_ user-facing change?
This will unblock Apple Silicon usage.
### How was this patch tested?
Pass the CIs.
Closes#30848 from dongjoon-hyun/SPARK-33843.
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 proposes to separate arguments properly for `-c` options. Otherwise, the space is considered as its part of argument:
```
Cloning into 'pyspark-coverage-site'...
unknown option: -c user.name='Apache Spark Test Account'
usage: git [--version] [--help] [-C <path>] [-c <name>=<value>]
[--exec-path[=<path>]] [--html-path] [--man-path] [--info-path]
[-p | --paginate | -P | --no-pager] [--no-replace-objects] [--bare]
[--git-dir=<path>] [--work-tree=<path>] [--namespace=<name>]
<command> [<args>]
[error] running git -c user.name='Apache Spark Test Account' -c user.email='sparktestaccgmail.com' commit -am Coverage report at latest commit in Apache Spark ; received return code 129
```
### Why are the changes needed?
To make the build pass (https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-sbt-hadoop-3.2/1728/console).
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
```python
>>> from sparktestsupport.shellutils import run_cmd
>>> run_cmd([
... "git",
... "-c",
... "user.name='Apache Spark Test Account'",
... "-c",
... "user.email='sparktestaccgmail.com'",
... "commit",
... "-am",
... "Coverage report at latest commit in Apache Spark"])
[SPARK-33802-followup 80d2565a511] Coverage report at latest commit in Apache Spark
1 file changed, 1 insertion(+), 1 deletion(-)
CompletedProcess(args=['git', '-c', "user.name='Apache Spark Test Account'", '-c', "user.email='sparktestaccgmail.com'", 'commit', '-am', 'Coverage report at latest commit in Apache Spark'], returncode=0)
```
I cannot run e2e test because it requires the env to have Jenkins secret.
Closes#30804 from HyukjinKwon/SPARK-33802-followup.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
The current Jenkins job fails as below (https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-sbt-hadoop-3.2/1726/console)
```
Generating HTML files for PySpark coverage under /home/jenkins/workspace/spark-master-test-sbt-hadoop-3.2/python/test_coverage/htmlcov
/home/jenkins/workspace/spark-master-test-sbt-hadoop-3.2
Cloning into 'pyspark-coverage-site'...
*** Please tell me who you are.
Run
git config --global user.email "youexample.com"
git config --global user.name "Your Name"
to set your account's default identity.
Omit --global to set the identity only in this repository.
```
This PR proposes to set both when committing to the coverage site.
### Why are the changes needed?
To make the coverage site keep working.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Manually tested in the console but it has to be merged to test in the Jenkins environment.
Closes#30796 from HyukjinKwon/SPARK-33802.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
TO FIX flaky tests:
https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/132345/testReport/
```
org.apache.spark.sql.hive.thriftserver.HiveThriftHttpServerSuite.JDBC query execution
org.apache.spark.sql.hive.thriftserver.HiveThriftHttpServerSuite.Checks Hive version
org.apache.spark.sql.hive.thriftserver.HiveThriftHttpServerSuite.SPARK-24829 Checks cast as float
```
The root cause here is a jar conflict issue.
`NewCookie.isHttpOnly` is not defined in the `jsr311-api.jar` which conflicts
The transitive artifact `jsr311-api.jar` of `hadoop-client` is excluded at the maven side. See https://issues.apache.org/jira/browse/SPARK-27179.
The Jenkins PR builder and Github Action use `SBT` as the compiler tool.
First, the exclusion rule from maven is not followed by sbt, so I was able to see `jsr311-api.jar` from maven cache to be added to the classpath directly. **This seems to be a bug of `sbt-pom-reader` plugin but I'm not that sure.**
Then I added an `ExcludeRule` for the `hive-thriftserver` module at the SBT side and did see the `jsr311-api.jar` gone, but the CI jobs still failed with the same error.
I added a trace log in ThriftHttpServlet
```s
ERROR ThriftHttpServlet: !!!!!!!!! Suspect???????? --->
file:/home/jenkins/workspace/SparkPullRequestBuilder/assembly/target/scala-2.12/jars/jsr311-api-1.1.1.jar
```
And the log pointed out that the assembly phase copied it to `assembly/target/scala-2.12/jars/` which will be added to the classpath too. With the help of SBT `dependencyTree` tool, I saw the `jsr311-api` again as a transitive of `jersery-core` from `yarn` module with a `test` scope. So **This seems to be another bug from the SBT side of the `sbt-assembly` plugin.** It copied a test scope transitive artifact to the assembly output.
In this PR, I defined some rules in SparkBuild.scala to bypass the potential bugs from the SBT side.
First, exclude the `jsr311` from all over the project and then add it back separately to the YARN module for SBT.
Additionally, the HiveThriftServerSuites was reflected for reducing flakiness too, but not related to the bugs I have found so far.
### Why are the changes needed?
fix test here
### Does this PR introduce _any_ user-facing change?
NO
### How was this patch tested?
passing jenkins and ga
Closes#30643 from yaooqinn/HiveThriftHttpServerSuite.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This pr upgrade Jackson to 2.11.4.
Jackson Release 2.11: https://github.com/FasterXML/jackson/wiki/Jackson-Release-2.11
### Why are the changes needed?
Make it easy to upgrade dependency because Jackson 2.10 is not compatible with 2.11:
```
com.fasterxml.jackson.databind.JsonMappingException: Scala module 2.10.5 requires Jackson Databind version >= 2.10.0 and < 2.11.0
```
[Avro](https://issues.apache.org/jira/browse/AVRO-2967) has upgraded Jackson to 2.11.3.
[Parquet](https://issues.apache.org/jira/browse/PARQUET-1895) has upgraded Jackson to 2.11.2.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing test.
Closes#30746 from wangyum/SPARK-33766.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
### Why are the changes needed?
Open Source scans are reporting a potential encoding/decoding issue related to versions of commons-codec prior to 1.13. Commit referenced: 48b615756d
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing tests.
Closes#30740 from n-marion/SPARK-33762_upgrade-commons-codec.
Authored-by: Nicholas Marion <nmarion@us.ibm.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Once you build and ran K8S tests, Python lint fails as below:
```bash
$ ./dev/lint-python
```
Before this PR:
```
starting python compilation test...
python compilation succeeded.
downloading pycodestyle from https://raw.githubusercontent.com/PyCQA/pycodestyle/2.6.0/pycodestyle.py...
starting pycodestyle test...
pycodestyle checks failed:
./resource-managers/kubernetes/integration-tests/target/spark-dist-unpacked/python/pyspark/cloudpickle/cloudpickle.py:15:101: E501 line too long (105 > 100 characters)
./resource-managers/kubernetes/integration-tests/target/spark-dist-unpacked/python/docs/source/conf.py:60:101: E501 line too long (124 > 100 characters)
...
```
After this PR:
```
starting python compilation test...
python compilation succeeded.
downloading pycodestyle from https://raw.githubusercontent.com/PyCQA/pycodestyle/2.6.0/pycodestyle.py...
starting pycodestyle test...
pycodestyle checks passed.
starting flake8 test...
flake8 checks passed.
starting mypy test...
mypy checks passed.
starting sphinx-build tests...
sphinx-build checks passed.
```
This PR excludes target directory to avoid such cases in the future.
### Why are the changes needed?
To make it easier to run linters
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Manually tested va running `./dev/lint-python`.
Closes#30718 from HyukjinKwon/SPARK-33749.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to upgrade Apache ORC to 1.6.6 for Apache Spark 3.2.0.
### Why are the changes needed?
This brings the latest bug fixes and features.
Apache Iceberg is already using Apache ORC 1.6.6.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CIs.
Closes#30715 from dongjoon-hyun/SPARK-33295.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This upgrades snappy-java to 1.1.8.2.
### Why are the changes needed?
Minor version upgrade that includes:
- [Fixed](https://github.com/xerial/snappy-java/pull/265) an initialization issue when using a recent Mac OS X version
- Support Apple Silicon (M1, Mac-aarch64)
- Fixed the pure-java Snappy fallback logic when no native library for your platform is found.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unit test.
Closes#30690 from viirya/upgrade-snappy.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Upgrade the jackson dependencies to 2.10.5 and jackson-databind to 2.10.5.1
### Why are the changes needed?
Jackson dependency has vulnerability CVE-2020-25649.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing unit tests.
Closes#30656 from n-marion/SPARK-33695_upgrade-jackson.
Authored-by: Nicholas Marion <nmarion@us.ibm.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR upgrades `commons.httpclient` from `4.5.6` to `4.5.13`.
4.5.6 is released over 2 years ago and now we can use more stable `4.5.13`.
https://archive.apache.org/dist/httpcomponents/httpclient/RELEASE_NOTES-4.5.x.txt
### Why are the changes needed?
To follow the more stable release.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Should be done by the existing tests.
Closes#30634 from sarutak/upgrade-httpclient.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This reverts commit SPARK-33212 (cb3fa6c936) mostly with three exceptions:
1. `SparkSubmitUtils` was updated recently by SPARK-33580
2. `resource-managers/yarn/pom.xml` was updated recently by SPARK-33104 to add `hadoop-yarn-server-resourcemanager` test dependency.
3. Adjust `com.fasterxml.jackson.module:jackson-module-jaxb-annotations` dependency in K8s module which is updated recently by SPARK-33471.
### Why are the changes needed?
According to [HADOOP-16080](https://issues.apache.org/jira/browse/HADOOP-16080) since Apache Hadoop 3.1.1, `hadoop-aws` doesn't work with `hadoop-client-api`. It fails at write operation like the following.
**1. Spark distribution with `-Phadoop-cloud`**
```scala
$ bin/spark-shell --conf spark.hadoop.fs.s3a.access.key=$AWS_ACCESS_KEY_ID --conf spark.hadoop.fs.s3a.secret.key=$AWS_SECRET_ACCESS_KEY
20/11/30 23:01:24 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context available as 'sc' (master = local[*], app id = local-1606806088715).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 3.1.0-SNAPSHOT
/_/
Using Scala version 2.12.10 (OpenJDK 64-Bit Server VM, Java 1.8.0_272)
Type in expressions to have them evaluated.
Type :help for more information.
scala> spark.read.parquet("s3a://dongjoon/users.parquet").show
20/11/30 23:01:34 WARN MetricsConfig: Cannot locate configuration: tried hadoop-metrics2-s3a-file-system.properties,hadoop-metrics2.properties
+------+--------------+----------------+
| name|favorite_color|favorite_numbers|
+------+--------------+----------------+
|Alyssa| null| [3, 9, 15, 20]|
| Ben| red| []|
+------+--------------+----------------+
scala> Seq(1).toDF.write.parquet("s3a://dongjoon/out.parquet")
20/11/30 23:02:14 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 2)/ 1]
java.lang.NoSuchMethodError: org.apache.hadoop.util.SemaphoredDelegatingExecutor.<init>(Lcom/google/common/util/concurrent/ListeningExecutorService;IZ)V
```
**2. Spark distribution without `-Phadoop-cloud`**
```scala
$ bin/spark-shell --conf spark.hadoop.fs.s3a.access.key=$AWS_ACCESS_KEY_ID --conf spark.hadoop.fs.s3a.secret.key=$AWS_SECRET_ACCESS_KEY -c spark.eventLog.enabled=true -c spark.eventLog.dir=s3a://dongjoon/spark-events/ --packages org.apache.hadoop:hadoop-aws:3.2.0,org.apache.hadoop:hadoop-common:3.2.0
...
java.lang.NoSuchMethodError: org.apache.hadoop.util.SemaphoredDelegatingExecutor.<init>(Lcom/google/common/util/concurrent/ListeningExecutorService;IZ)V
at org.apache.hadoop.fs.s3a.S3AFileSystem.create(S3AFileSystem.java:772)
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CI.
Closes#30508 from dongjoon-hyun/SPARK-33212-REVERT.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Fix: Pyspark ML Validator params in estimatorParamMaps may be lost after saving and reloading
When saving validator estimatorParamMaps, will check all nested stages in tuned estimator to get correct param parent.
Two typical cases to manually test:
~~~python
tokenizer = Tokenizer(inputCol="text", outputCol="words")
hashingTF = HashingTF(inputCol=tokenizer.getOutputCol(), outputCol="features")
lr = LogisticRegression()
pipeline = Pipeline(stages=[tokenizer, hashingTF, lr])
paramGrid = ParamGridBuilder() \
.addGrid(hashingTF.numFeatures, [10, 100]) \
.addGrid(lr.maxIter, [100, 200]) \
.build()
tvs = TrainValidationSplit(estimator=pipeline,
estimatorParamMaps=paramGrid,
evaluator=MulticlassClassificationEvaluator())
tvs.save(tvsPath)
loadedTvs = TrainValidationSplit.load(tvsPath)
# check `loadedTvs.getEstimatorParamMaps()` restored correctly.
~~~
~~~python
lr = LogisticRegression()
ova = OneVsRest(classifier=lr)
grid = ParamGridBuilder().addGrid(lr.maxIter, [100, 200]).build()
evaluator = MulticlassClassificationEvaluator()
tvs = TrainValidationSplit(estimator=ova, estimatorParamMaps=grid, evaluator=evaluator)
tvs.save(tvsPath)
loadedTvs = TrainValidationSplit.load(tvsPath)
# check `loadedTvs.getEstimatorParamMaps()` restored correctly.
~~~
### Why are the changes needed?
Bug fix.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unit test.
Closes#30539 from WeichenXu123/fix_tuning_param_maps_io.
Authored-by: Weichen Xu <weichen.xu@databricks.com>
Signed-off-by: Ruifeng Zheng <ruifengz@foxmail.com>
### What changes were proposed in this pull request?
This PR intends to fix typos in the sub-modules:
* `R`
* `common`
* `dev`
* `mlib`
* `external`
* `project`
* `streaming`
* `resource-managers`
* `python`
Split per srowen https://github.com/apache/spark/pull/30323#issuecomment-728981618
NOTE: The misspellings have been reported at 706a726f87 (commitcomment-44064356)
### Why are the changes needed?
Misspelled words make it harder to read / understand content.
### Does this PR introduce _any_ user-facing change?
There are various fixes to documentation, etc...
### How was this patch tested?
No testing was performed
Closes#30402 from jsoref/spelling-R_common_dev_mlib_external_project_streaming_resource-managers_python.
Authored-by: Josh Soref <jsoref@users.noreply.github.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR proposes to keep the test coverage with Python 3.8 in GitHub Actions. It is not tested for now in Jenkins due to an env issue.
**Before this change in GitHub Actions:**
```
========================================================================
Running PySpark tests
========================================================================
Running PySpark tests. Output is in /__w/spark/spark/python/unit-tests.log
Will test against the following Python executables: ['python3.6', 'pypy3']
...
```
**After this change in GitHub Actions:**
```
========================================================================
Running PySpark tests
========================================================================
Running PySpark tests. Output is in /__w/spark/spark/python/unit-tests.log
Will test against the following Python executables: ['python3.6', 'python3.8', 'pypy3']
```
### Why are the changes needed?
To keep the test coverage with Python 3.8 in GitHub Actions.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
GitHub Actions in this build will test.
Closes#30510 from HyukjinKwon/SPARK-33565.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
We supported Hive metastore are 0.12.0 through 3.1.2, but we supported hive-jdbc are 0.12.0 through 2.3.7. It will throw `TProtocolException` if we use hive-jdbc 3.x:
```
[rootspark-3267648 apache-hive-3.1.2-bin]# bin/beeline -u jdbc:hive2://localhost:10000/default
Connecting to jdbc:hive2://localhost:10000/default
Connected to: Spark SQL (version 3.1.0-SNAPSHOT)
Driver: Hive JDBC (version 3.1.2)
Transaction isolation: TRANSACTION_REPEATABLE_READ
Beeline version 3.1.2 by Apache Hive
0: jdbc:hive2://localhost:10000/default> create table t1(id int) using parquet;
Unexpected end of file when reading from HS2 server. The root cause might be too many concurrent connections. Please ask the administrator to check the number of active connections, and adjust hive.server2.thrift.max.worker.threads if applicable.
Error: org.apache.thrift.transport.TTransportException (state=08S01,code=0)
```
```
org.apache.thrift.protocol.TProtocolException: Missing version in readMessageBegin, old client?
at org.apache.thrift.protocol.TBinaryProtocol.readMessageBegin(TBinaryProtocol.java:234)
at org.apache.thrift.TBaseProcessor.process(TBaseProcessor.java:27)
at org.apache.hive.service.auth.TSetIpAddressProcessor.process(TSetIpAddressProcessor.java:53)
at org.apache.thrift.server.TThreadPoolServer$WorkerProcess.run(TThreadPoolServer.java:310)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1130)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:630)
at java.base/java.lang.Thread.run(Thread.java:832)
```
This pr upgrade hive-service-rpc to 3.1.2 to fix this issue.
### Why are the changes needed?
To support hive-jdbc 3.x.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manual test:
```
[rootspark-3267648 apache-hive-3.1.2-bin]# bin/beeline -u jdbc:hive2://localhost:10000/default
Connecting to jdbc:hive2://localhost:10000/default
Connected to: Spark SQL (version 3.1.0-SNAPSHOT)
Driver: Hive JDBC (version 3.1.2)
Transaction isolation: TRANSACTION_REPEATABLE_READ
Beeline version 3.1.2 by Apache Hive
0: jdbc:hive2://localhost:10000/default> create table t1(id int) using parquet;
+---------+
| Result |
+---------+
+---------+
No rows selected (1.051 seconds)
0: jdbc:hive2://localhost:10000/default> insert into t1 values(1);
+---------+
| Result |
+---------+
+---------+
No rows selected (2.08 seconds)
0: jdbc:hive2://localhost:10000/default> select * from t1;
+-----+
| id |
+-----+
| 1 |
+-----+
1 row selected (0.605 seconds)
```
Closes#30478 from wangyum/SPARK-33525.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
It seems that Jenkins tests tasks in many pr have test failed. The failed cases include:
- `org.apache.spark.sql.hive.thriftserver.SparkThriftServerProtocolVersionsSuite.HIVE_CLI_SERVICE_PROTOCOL_V1 get binary type`
- `org.apache.spark.sql.hive.thriftserver.SparkThriftServerProtocolVersionsSuite.HIVE_CLI_SERVICE_PROTOCOL_V2 get binary type`
- `org.apache.spark.sql.hive.thriftserver.SparkThriftServerProtocolVersionsSuite.HIVE_CLI_SERVICE_PROTOCOL_V3 get binary type`
- `org.apache.spark.sql.hive.thriftserver.SparkThriftServerProtocolVersionsSuite.HIVE_CLI_SERVICE_PROTOCOL_V4 get binary type`
- `org.apache.spark.sql.hive.thriftserver.SparkThriftServerProtocolVersionsSuite.HIVE_CLI_SERVICE_PROTOCOL_V5 get binary type`
The error message as follows:
```
Error Messageorg.scalatest.exceptions.TestFailedException: "[?](" did not equal "[�]("Stacktracesbt.ForkMain$ForkError: org.scalatest.exceptions.TestFailedException: "[?](" did not equal "[�]("
at org.scalatest.Assertions.newAssertionFailedException(Assertions.scala:472)
at org.scalatest.Assertions.newAssertionFailedException$(Assertions.scala:471)
at org.scalatest.Assertions$.newAssertionFailedException(Assertions.scala:1231)
at org.scalatest.Assertions$AssertionsHelper.macroAssert(Assertions.scala:1295)
at org.apache.spark.sql.hive.thriftserver.SparkThriftServerProtocolVersionsSuite.$anonfun$new$26(SparkThriftServerProtocolVersionsSuite.scala:302)
```
But they can pass the GitHub Action, maybe it's related to the `LANG` of the Jenkins build machine, this pr add `export LANG="en_US.UTF-8"` in `run-test-jenkins` script.
### Why are the changes needed?
Ensure LANG in Jenkins test process is `en_US.UTF-8` to pass `HIVE_CLI_SERVICE_PROTOCOL_VX` related tests
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Jenkins tests pass
Closes#30487 from LuciferYang/SPARK-33535.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to update SBT from 1.4.2 to 1.4.4.
### Why are the changes needed?
This will bring the latest bug fixes.
- https://github.com/sbt/sbt/releases/tag/v1.4.3
- https://github.com/sbt/sbt/releases/tag/v1.4.4
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CIs.
Closes#30453 from williamhyun/sbt143.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to suppress the warning `File exists` in check-license
### Why are the changes needed?
**BEFORE**
```
% dev/check-license
Attempting to fetch rat
RAT checks passed.
% dev/check-license
mkdir: target: File exists
RAT checks passed.
```
**AFTER**
```
% dev/check-license
Attempting to fetch rat
RAT checks passed.
% dev/check-license
RAT checks passed.
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manually do dev/check-license twice.
Closes#30460 from williamhyun/checklicense.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR fixes the RAT exclusion rule which was originated from SPARK-1144 (Apache Spark 1.0)
### Why are the changes needed?
This prevents the situation like https://github.com/apache/spark/pull/30415.
Currently, it missed `catalog` directory due to `.log` rule.
```
$ dev/check-license
Could not find Apache license headers in the following files:
!????? /Users/dongjoon/APACHE/spark-merge/sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/MetadataColumn.java
!????? /Users/dongjoon/APACHE/spark-merge/sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/SupportsMetadataColumns.java
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CI with the new rule.
Closes#30418 from dongjoon-hyun/SPARK-RAT.
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 intends to upgrade ANTLR runtime from 4.7.1 to 4.8-1.
### Why are the changes needed?
Release note of v4.8 and v4.7.2 (the v4.7.2 release has a few minor bug fixes for java targets):
- v4.8: https://github.com/antlr/antlr4/releases/tag/4.8
- v4.7.2: https://github.com/antlr/antlr4/releases/tag/4.7.2
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
GA tests.
Closes#30404 from maropu/UpgradeAntlr.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to upgrade Kubernetes-client from 4.11.1 to 4.12.0
### Why are the changes needed?
This upgrades the dependency for Apache Spark 3.1.0.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Pass the CIs.
Closes#30401 from ramesh-muthusamy/SPARK-33471-k8s-clientupgrade.
Authored-by: Rameshkrishnan Muthusamy <rameshkrishnan_muthusamy@apple.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This upgrade Apache Arrow version from 1.0.1 to 2.0.0
### Why are the changes needed?
Apache Arrow 2.0.0 was released with some improvements from Java side, so it's better to upgrade Spark to the new version.
Note that the format version in Arrow 2.0.0 is still 1.0.0 so API should still be compatible between 1.0.1 and 2.0.0.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing UTs.
Closes#30306 from sunchao/SPARK-33213.
Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to upgrade `commons-compress` from 1.8 to 1.20.
### Why are the changes needed?
- https://commons.apache.org/proper/commons-compress/security-reports.html
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CIs.
Closes#30304 from dongjoon-hyun/SPARK-33405.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Update the package commons-crypto to v1.1.0 to support aarch64 platform
- https://issues.apache.org/jira/browse/CRYPTO-139
### Why are the changes needed?
The package commons-crypto-1.0.0 available in the Maven repository
doesn't support aarch64 platform. It costs long time in
CryptoRandomFactory.getCryptoRandom(properties).nextBytes(iv) when NettyBlockRpcSever
receive block data from client, if the time more than the default value 120s, IOException raised and client
will retry replicate the block data to other executors. But in fact the replication is complete,
it makes the replication number incorrect.
This makes DistributedSuite tests pass.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Pass the CIs.
Closes#30275 from huangtianhua/SPARK-32691.
Authored-by: huangtianhua <huangtianhua223@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to upgrade `Kubernetes-client` from 4.10.3 to 4.11.1.
### Why are the changes needed?
This upgrades the dependency for Apache Spark 3.1.0.
Since 4.12.0 is still new and has a breaking API changes, this PR chooses the latest compatible one.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the all CIs including K8s IT.
Closes#30233 from dongjoon-hyun/SPARK-33324.
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 proposes to initiate the migration to NumPy documentation style (from reST style) in PySpark docstrings.
This PR also adds one migration example of `SparkContext`.
- **Before:**
...
...
...
- **After:**
...
...
See also https://numpydoc.readthedocs.io/en/latest/format.html
### Why are the changes needed?
There are many reasons for switching to NumPy documentation style.
1. Arguably reST style doesn't fit well when the docstring grows large because it provides (arguably) less structures and syntax.
2. NumPy documentation style provides a better human readable docstring format. For example, notebook users often just do `help(...)` by `pydoc`.
3. NumPy documentation style is pretty commonly used in data science libraries, for example, pandas, numpy, Dask, Koalas,
matplotlib, ... Using NumPy documentation style can give users a consistent documentation style.
### Does this PR introduce _any_ user-facing change?
The dependency itself doesn't change anything user-facing.
The documentation change in `SparkContext` does, as shown above.
### How was this patch tested?
Manually tested via running `cd python` and `make clean html`.
Closes#30149 from HyukjinKwon/SPARK-33243.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
I am generating the SHA-512 using the standard shasum which also has a better output compared to GPG.
### Why are the changes needed?
Which makes the hash much easier to verify for users that don't have GPG.
Because an user having GPG can check the keys but an user without GPG will have a hard time validating the SHA-512 based on the 'pretty printed' format.
Apache Spark is the only project where I've seen this format. Most other Apache projects have a one-line hash file.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
This patch assumes the build system has shasum (it should, but I can't test this).
Closes#30123 from emilianbold/master.
Authored-by: Emi <emilian.bold@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This switches Spark to use shaded Hadoop clients, namely hadoop-client-api and hadoop-client-runtime, for Hadoop 3.x. For Hadoop 2.7, we'll still use the same modules such as hadoop-client.
In order to still keep default Hadoop profile to be hadoop-3.2, this defines the following Maven properties:
```
hadoop-client-api.artifact
hadoop-client-runtime.artifact
hadoop-client-minicluster.artifact
```
which default to:
```
hadoop-client-api
hadoop-client-runtime
hadoop-client-minicluster
```
but all switch to `hadoop-client` when the Hadoop profile is hadoop-2.7. A side affect from this is we'll import the same dependency multiple times. For this I have to disable Maven enforcer `banDuplicatePomDependencyVersions`.
Besides above, there are the following changes:
- explicitly add a few dependencies which are imported via transitive dependencies from Hadoop jars, but are removed from the shaded client jars.
- removed the use of `ProxyUriUtils.getPath` from `ApplicationMaster` which is a server-side/private API.
- modified `IsolatedClientLoader` to exclude `hadoop-auth` jars when Hadoop version is 3.x. This change should only matter when we're not sharing Hadoop classes with Spark (which is _mostly_ used in tests).
### Why are the changes needed?
This serves two purposes:
- to unblock Spark from upgrading to Hadoop 3.2.2/3.3.0+. Latest Hadoop versions have upgraded to use Guava 27+ and in order to adopt the latest Hadoop versions in Spark, we'll need to resolve the Guava conflicts. This takes the approach by switching to shaded client jars provided by Hadoop.
- avoid pulling 3rd party dependencies from Hadoop and avoid potential future conflicts.
### Does this PR introduce _any_ user-facing change?
When people use Spark with `hadoop-provided` option, they should make sure class path contains `hadoop-client-api` and `hadoop-client-runtime` jars. In addition, they may need to make sure these jars appear before other Hadoop jars in the order. Otherwise, classes may be loaded from the other non-shaded Hadoop jars and cause potential conflicts.
### How was this patch tested?
Relying on existing tests.
Closes#29843 from sunchao/SPARK-29250.
Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: DB Tsai <d_tsai@apple.com>
### What changes were proposed in this pull request?
This PR intends to upgrade snappy-java from 1.1.7.5 to 1.1.8.
### Why are the changes needed?
For performance improvements; the released `snappy-java` bundles the latest `Snappy` v1.1.8 binaries with small performance improvements.
- snappy-java release note: https://github.com/xerial/snappy-java/releases/tag/1.1.8
- snappy release note: https://github.com/google/snappy/releases/tag/1.1.8
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
GA tests.
Closes#30120 from maropu/Snappy1.1.8.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>
### What changes were proposed in this pull request?
Add MyPy to the CI. Once this is installed on the CI: https://issues.apache.org/jira/browse/SPARK-32797?jql=project%20%3D%20SPARK%20AND%20text%20~%20mypy this wil automatically check the types.
### Why are the changes needed?
We should check if the types are still correct on the CI.
```
MacBook-Pro-van-Fokko:spark fokkodriesprong$ ./dev/lint-python
starting python compilation test...
python compilation succeeded.
starting pycodestyle test...
pycodestyle checks passed.
starting flake8 test...
flake8 checks passed.
starting mypy test...
mypy checks passed.
The sphinx-build command was not found. Skipping Sphinx build for now.
all lint-python tests passed!
```
### Does this PR introduce _any_ user-facing change?
No :)
### How was this patch tested?
By running `./dev/lint-python` locally.
Closes#30088 from Fokko/SPARK-17333.
Authored-by: Fokko Driesprong <fokko@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to switch the default Hadoop profile from `hadoop2.7` to `hadoop3.2` in `dev/run-tests.py` when it's running in local or GitHub Action environments.
### Why are the changes needed?
The default Hadoop version is 3.2. We had better be consistent.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manually.
**BEFORE**
```
% dev/run-tests.py
Cannot install SparkR as R was not found in PATH
[info] Using build tool sbt with Hadoop profile hadoop2.7 and Hive profile hive2.3 under environment local
```
**AFTER**
```
% dev/run-tests.py
Cannot install SparkR as R was not found in PATH
[info] Using build tool sbt with Hadoop profile hadoop3.2 and Hive profile hive2.3 under environment local
```
Closes#30090 from williamhyun/SPARK-33179.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to ignore GitHub only changes in Amplab Jenkins build.
### Why are the changes needed?
This will save server resources.
### Does this PR introduce _any_ user-facing change?
No, this is a dev-only change.
### How was this patch tested?
Manually. I used the following doctest during testing and removed it at the clean-up.
E2E tests:
```
cd dev
cat test.py
```
```python
import importlib
runtests = importlib.import_module("run-tests")
print([x.name for x in runtests.determine_modules_for_files([".github/workflows/build_and_test.yml"])])
```
```python
$ GITHUB_ACTIONS=1 python test.py
['root']
$ python test.py
[]
```
Unittests:
```bash
$ GITHUN_ACTIONS=1 python3 -m doctest dev/run-tests.py
$ python3 -m doctest dev/run-tests.py
```
Closes#30020 from williamhyun/SPARK-33123.
Lead-authored-by: William Hyun <williamhyun3@gmail.com>
Co-authored-by: Hyukjin Kwon <gurwls223@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Hive's `hive-service-rpc` module started since hive-2.1.0 and it contains only the thrift IDL file and the code generated by it.
Removing the inlined code will help maintain and upgrade builtin hive versions
### Why are the changes needed?
to simply the code.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
passing CI
Closes#30055 from yaooqinn/SPARK-33159.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to upgrade ZStandard library for Apache Spark 3.1.0.
### Why are the changes needed?
This will bring the latest bug fixes.
- 2662fbdc32
- bbe140b758
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CI.
Closes#30010 from dongjoon-hyun/SPARK-33117.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
- Change default R `arch` from `i386` to `x64`, to match Rtools version.
- Parameterize `BINPREF` with `WIN` (https://stackoverflow.com/a/44035904)
Reported on dev:
http://apache-spark-developers-list.1001551.n3.nabble.com/Broken-rlang-installation-on-AppVeyor-td30294.html
### Why are the changes needed?
It seems like update from rlang 0.4.7 to 0.4.8 exposed an issue, where build fails because of incompatible ddl
```
c:/Rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe:
skipping incompatible C:/R/bin/i386/R.dll when searching for -lR
[00:01:52]
c:/Rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe:
skipping incompatible C:/R/bin/i386/R.dll when searching for -lR
[00:01:52]
c:/Rtools40/mingw64/bin/../lib/gcc/x86_64-w64-mingw32/8.3.0/../../../../x86_64-w64-mingw32/bin/ld.exe:
cannot find -lR
[00:01:52] collect2.exe: error: ld returned 1 exit status
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing tests.
Closes#29991 from zero323/APPVEYOR-DEAFAULT-ARCH.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR removes the leftover of Hive 1.2 workarounds and Hive 1.2 profile in Jenkins script.
- `test-hive1.2` title is not used anymore in Jenkins
- Remove some comments related to Hive 1.2
- Remove unused codes in `OrcFilters.scala` Hive
- Test `spark.sql.hive.convertMetastoreOrc` disabled case for the tests added at SPARK-19809 and SPARK-22267
### Why are the changes needed?
To remove unused codes & improve test coverage
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Manually ran the unit tests. Also It will be tested in CI in this PR.
Closes#29973 from HyukjinKwon/SPARK-33082-SPARK-20202.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
As of today,
- SPARK-30034 Apache Spark 3.0.0 switched its default Hive execution engine from Hive 1.2 to Hive 2.3. This removes the direct dependency to the forked Hive 1.2.1 in maven repository.
- SPARK-32981 Apache Spark 3.1.0(`master` branch) removed Hive 1.2 related artifacts from Apache Spark binary distributions.
This PR(SPARK-20202) aims to remove the following usage of unofficial Apache Hive fork completely from Apache Spark master for Apache Spark 3.1.0.
```
<hive.group>org.spark-project.hive</hive.group>
<hive.version>1.2.1.spark2</hive.version>
```
For the forked Hive 1.2.1.spark2 users, Apache Spark 2.4(LTS) and 3.0 (~ 2021.12) will provide it.
### Why are the changes needed?
- First, Apache Spark community should not use the unofficial forked release of another Apache project.
- Second, Apache Hive 1.2.1 was released at 2015-06-26 and the forked Hive `1.2.1.spark2` exposed many unfixable bugs in Apache because the forked `1.2.1.spark2` is not maintained at all. Apache Hive 2.3.0 was released at 2017-07-19 and it has been used with less number of bugs compared with `1.2.1.spark2`. Many bugs still exist in `hive-1.2` profile and new Apache Spark unit tests are added with `HiveUtils.isHive23` condition so far.
### Does this PR introduce _any_ user-facing change?
No. This is a dev-only change. PRBuilder will not accept `[test-hive1.2]` on master and `branch-3.1`.
### How was this patch tested?
1. SBT/Hadoop 3.2/Hive 2.3 (https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/129366)
2. SBT/Hadoop 2.7/Hive 2.3 (https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/129382)
3. SBT/Hadoop 3.2/Hive 1.2 (This has not been supported already due to Hive 1.2 doesn't work with Hadoop 3.2.)
4. SBT/Hadoop 2.7/Hive 1.2 (https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/129383, This is rejected)
Closes#29936 from dongjoon-hyun/SPARK-REMOVE-HIVE1.
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 aims to upgrade Apache ORC to 1.5.12.
### Why are the changes needed?
This brings us the latest bug patches like the followings.
- ORC-644 nested struct evolution does not respect to orc.force.positional.evolution
- ORC-667 Positional mapping for nested struct types should not applied by default
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CI.
Closes#29930 from dongjoon-hyun/SPARK-ORC-1.5.12.
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 aims to upgrade Apache Hive `hive-storage-api` library from 2.7.1 to 2.7.2.
### Why are the changes needed?
[storage-api 2.7.2](https://github.com/apache/hive/commits/rel/storage-release-2.7.2/storage-api) has the following extension and can be used when users uses a provided orc dependency.
[HIVE-22959](dade9919d9 (diff-ccfc9dd7584117f531322cda3a29f3c3)) : Extend storage-api to expose FilterContext
[HIVE-23215](361925d2f3 (diff-ccfc9dd7584117f531322cda3a29f3c3)) : Make FilterContext and MutableFilterContext interfaces
### Does this PR introduce _any_ user-facing change?
Yes. This is a dependency change.
### How was this patch tested?
Pass the existing tests.
Closes#29923 from dongjoon-hyun/SPARK-33047.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Upgrade to the latest available version of jQuery (3.5.1).
### Why are the changes needed?
There are some CVE-s reported (CVE-2020-11022, CVE-2020-11023) affecting older versions of jQuery. Although Spark UI is read-only and those CVEs doesn't seem to affect Spark, using the latest version of this library can help to handle vulnerability reports of security scans.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manual tests and checked the jQuery 3.5 upgrade guide.
Closes#29902 from peter-toth/SPARK-32723-upgrade-to-jquery-3.5.1.
Authored-by: Peter Toth <peter.toth@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to upgrade `kubernetes-client` library to track fabric8's declared compatibility for k8s 1.18.0:
https://github.com/fabric8io/kubernetes-client#compatibility-matrix
### Why are the changes needed?
According to fabric8, 4.9.2 is incompatible with k8s 1.18.0.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Not tested yet.
Closes#29888 from laflechejonathan/jlf/fabric8Ugprade.
Authored-by: jlafleche <jlafleche@palantir.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR removes Hive 1.2 option (and therefore `HIVE_VERSION` environment variable as well).
### Why are the changes needed?
Hive 1.2 is a fork version. We shouldn't promote users to use.
### Does this PR introduce _any_ user-facing change?
Nope, `HIVE_VERSION` and Hive 1.2 are removed but this is new experimental feature in master only.
### How was this patch tested?
Manually tested:
```bash
SPARK_VERSION=3.0.1 HADOOP_VERSION=3.2 pip install pyspark-3.1.0.dev0.tar.gz -v
SPARK_VERSION=3.0.1 HADOOP_VERSION=2.7 pip install pyspark-3.1.0.dev0.tar.gz -v
SPARK_VERSION=3.0.1 HADOOP_VERSION=invalid pip install pyspark-3.1.0.dev0.tar.gz -v
```
Closes#29858 from HyukjinKwon/SPARK-32981.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes migration of [`pyspark-stubs`](https://github.com/zero323/pyspark-stubs) into Spark codebase.
### Why are the changes needed?
### Does this PR introduce _any_ user-facing change?
Yes. This PR adds type annotations directly to Spark source.
This can impact interaction with development tools for users, which haven't used `pyspark-stubs`.
### How was this patch tested?
- [x] MyPy tests of the PySpark source
```
mypy --no-incremental --config python/mypy.ini python/pyspark
```
- [x] MyPy tests of Spark examples
```
MYPYPATH=python/ mypy --no-incremental --config python/mypy.ini examples/src/main/python/ml examples/src/main/python/sql examples/src/main/python/sql/streaming
```
- [x] Existing Flake8 linter
- [x] Existing unit tests
Tested against:
- `mypy==0.790+dev.e959952d9001e9713d329a2f9b196705b028f894`
- `mypy==0.782`
Closes#29591 from zero323/SPARK-32681.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Apache Spark 3.0 switches its Hive execution version from 1.2 to 2.3, but it still provides the unofficial forked Hive 1.2 version from our distribution like the following. This PR aims to remove it from Apache Spark 3.1.0 officially while keeping `hive-1.2` profile.
```
spark-3.0.1-bin-hadoop2.7-hive1.2.tgz
spark-3.0.1-bin-hadoop2.7-hive1.2.tgz.asc
spark-3.0.1-bin-hadoop2.7-hive1.2.tgz.sha512
```
### Why are the changes needed?
The unofficial Hive 1.2.1 fork has many bugs and is not maintained for a long time. We had better not recommend this in the official Apache Spark distribution.
### Does this PR introduce _any_ user-facing change?
There is no user-facing change in the default distribution (Hadoop 3.2/Hive 2.3).
### How was this patch tested?
Manually because this is a change in release script .
Closes#29856 from dongjoon-hyun/SPARK-32981.
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 proposes to add a way to select Hadoop and Hive versions in pip installation.
Users can select Hive or Hadoop versions as below:
```bash
HADOOP_VERSION=3.2 pip install pyspark
HIVE_VERSION=1.2 pip install pyspark
HIVE_VERSION=1.2 HADOOP_VERSION=2.7 pip install pyspark
```
When the environment variables are set, internally it downloads the corresponding Spark version and then sets the Spark home to it. Also this PR exposes a mirror to set as an environment variable, `PYSPARK_RELEASE_MIRROR`.
**Please NOTE that:**
- We cannot currently leverage pip's native installation option, for example:
```bash
pip install pyspark --install-option="hadoop3.2"
```
This is because of a limitation and bug in pip itself. Once they fix this issue, we can switch from the environment variables to the proper installation options, see SPARK-32837.
It IS possible to workaround but very ugly or hacky with a big change. See [this PR](https://github.com/microsoft/nni/pull/139/files) as an example.
- In pip installation, we pack the relevant jars together. This PR _does not touch existing packaging way_ in order to prevent any behaviour changes.
Once this experimental way is proven to be safe, we can avoid packing the relevant jars together (and keep only the relevant Python scripts). And downloads the Spark distribution as this PR proposes.
- This way is sort of consistent with SparkR:
SparkR provides a method `SparkR::install.spark` to support CRAN installation. This is fine because SparkR is provided purely as a R library. For example, `sparkr` script is not packed together.
PySpark cannot take this approach because PySpark packaging ships relevant executable script together, e.g.) `pyspark` shell.
If PySpark has a method such as `pyspark.install_spark`, users cannot call it in `pyspark` because `pyspark` already assumes relevant Spark is installed, JVM is launched, etc.
- There looks no way to release that contains different Hadoop or Hive to PyPI due to [the version semantics](https://www.python.org/dev/peps/pep-0440/). This is not an option.
The usual way looks either `--install-option` above with hacks or environment variables given my investigation.
### Why are the changes needed?
To provide users the options to select Hadoop and Hive versions.
### Does this PR introduce _any_ user-facing change?
Yes, users will be able to select Hive and Hadoop version as below when they install it from `pip`;
```bash
HADOOP_VERSION=3.2 pip install pyspark
HIVE_VERSION=1.2 pip install pyspark
HIVE_VERSION=1.2 HADOOP_VERSION=2.7 pip install pyspark
```
### How was this patch tested?
Unit tests were added. I also manually tested in Mac and Windows (after building Spark with `python/dist/pyspark-3.1.0.dev0.tar.gz`):
```bash
./build/mvn -DskipTests -Phive-thriftserver clean package
```
Mac:
```bash
SPARK_VERSION=3.0.1 HADOOP_VERSION=3.2 pip install pyspark-3.1.0.dev0.tar.gz
```
Windows:
```bash
set HADOOP_VERSION=3.2
set SPARK_VERSION=3.0.1
pip install pyspark-3.1.0.dev0.tar.gz
```
Closes#29703 from HyukjinKwon/SPARK-32017.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
PyPI and CRAN did not change because of the concern about selecting Hadoop and Hive versions.
For PyPI, now there is a PR open at https://github.com/apache/spark/pull/29703
For CRAN, we can already select Hadoop and Hive versions via `SparkR::install.spark`.
### Why are the changes needed?
To keep the default profiles consistent in distributions
### Does this PR introduce _any_ user-facing change?
Yes, the default distributions will use Hadoop 3.2.
### How was this patch tested?
Jenkins tests.
Closes#29704 from HyukjinKwon/SPARK-32058.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Upgrade Apache Arrow to version 1.0.1 for the Java dependency and increase minimum version of PyArrow to 1.0.0.
This release marks a transition to binary stability of the columnar format (which was already informally backward-compatible going back to December 2017) and a transition to Semantic Versioning for the Arrow software libraries. Also note that the Java arrow-memory artifact has been split to separate dependence on netty-buffer and allow users to select an allocator. Spark will continue to use `arrow-memory-netty` to maintain performance benefits.
Version 1.0.0 - 1.0.0 include the following selected fixes/improvements relevant to Spark users:
ARROW-9300 - [Java] Separate Netty Memory to its own module
ARROW-9272 - [C++][Python] Reduce complexity in python to arrow conversion
ARROW-9016 - [Java] Remove direct references to Netty/Unsafe Allocators
ARROW-8664 - [Java] Add skip null check to all Vector types
ARROW-8485 - [Integration][Java] Implement extension types integration
ARROW-8434 - [C++] Ipc RecordBatchFileReader deserializes the Schema multiple times
ARROW-8314 - [Python] Provide a method to select a subset of columns of a Table
ARROW-8230 - [Java] Move Netty memory manager into a separate module
ARROW-8229 - [Java] Move ArrowBuf into the Arrow package
ARROW-7955 - [Java] Support large buffer for file/stream IPC
ARROW-7831 - [Java] unnecessary buffer allocation when calling splitAndTransferTo on variable width vectors
ARROW-6111 - [Java] Support LargeVarChar and LargeBinary types and add integration test with C++
ARROW-6110 - [Java] Support LargeList Type and add integration test with C++
ARROW-5760 - [C++] Optimize Take implementation
ARROW-300 - [Format] Add body buffer compression option to IPC message protocol using LZ4 or ZSTD
ARROW-9098 - RecordBatch::ToStructArray cannot handle record batches with 0 column
ARROW-9066 - [Python] Raise correct error in isnull()
ARROW-9223 - [Python] Fix to_pandas() export for timestamps within structs
ARROW-9195 - [Java] Wrong usage of Unsafe.get from bytearray in ByteFunctionsHelper class
ARROW-7610 - [Java] Finish support for 64 bit int allocations
ARROW-8115 - [Python] Conversion when mixing NaT and datetime objects not working
ARROW-8392 - [Java] Fix overflow related corner cases for vector value comparison
ARROW-8537 - [C++] Performance regression from ARROW-8523
ARROW-8803 - [Java] Row count should be set before loading buffers in VectorLoader
ARROW-8911 - [C++] Slicing a ChunkedArray with zero chunks segfaults
View release notes here:
https://arrow.apache.org/release/1.0.1.htmlhttps://arrow.apache.org/release/1.0.0.html
### Why are the changes needed?
Upgrade brings fixes, improvements and stability guarantees.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing tests with pyarrow 1.0.0 and 1.0.1
Closes#29686 from BryanCutler/arrow-upgrade-100-SPARK-32312.
Authored-by: Bryan Cutler <cutlerb@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
It should check `IPython` as it's imported as a package. Currently, Sphinx build is being skipped in GitHub Actions as below:
https://github.com/apache/spark/runs/1084164546
```
starting python compilation test...
python compilation succeeded.
starting pycodestyle test...
pycodestyle checks passed.
starting flake8 test...
flake8 checks passed.
python3 does not have ipython installed. Skipping Sphinx build for now.
all lint-python tests passed!
```
### Why are the changes needed?
To run the documentation builds in Github Actions.
### Does this PR introduce _any_ user-facing change?
No, dev-only
### How was this patch tested?
Manually tested as `dev/lint-python`.
Closes#29679 from HyukjinKwon/follow-ipython.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
https://issues.apache.org/jira/browse/SPARK-32719
### What changes were proposed in this pull request?
Add a check to detect missing imports. This makes sure that if we use a specific class, it should be explicitly imported (not using a wildcard).
### Why are the changes needed?
To make sure that the quality of the Python code is up to standard.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing unit-tests and Flake8 static analysis
Closes#29563 from Fokko/fd-add-check-missing-imports.
Authored-by: Fokko Driesprong <fokko@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Spark's CSV source can optionally ignore lines starting with a comment char. Some code paths check to see if it's set before applying comment logic (i.e. not set to default of `\0`), but many do not, including the one that passes the option to Univocity. This means that rows beginning with a null char were being treated as comments even when 'disabled'.
### Why are the changes needed?
To avoid dropping rows that start with a null char when this is not requested or intended. See JIRA for an example.
### Does this PR introduce _any_ user-facing change?
Nothing beyond the effect of the bug fix.
### How was this patch tested?
Existing tests plus new test case.
Closes#29516 from srowen/SPARK-32614.
Authored-by: Sean Owen <srowen@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes to add a `workflow_dispatch` entry in the GitHub Action script (`build_and_test.yml`). This update can enable developers to run the Spark tests for a specific branch on their own local repository, so I think it might help to check if al the tests can pass before opening a new PR.
<img width="944" alt="Screen Shot 2020-08-21 at 16 28 41" src="https://user-images.githubusercontent.com/692303/90866249-96250c80-e3ce-11ea-8496-3dd6683e92ea.png">
### Why are the changes needed?
To reduce the pressure of GitHub Actions on the Spark repository.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manually checked.
Closes#29504 from maropu/DispatchTest.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
### What changes were proposed in this pull request?
This PR reverts https://github.com/apache/spark/pull/27860 to downgrade Janino, as the new version has a bug.
### Why are the changes needed?
The symptom is about NaN comparison. For code below
```
if (double_value <= 0.0) {
...
} else {
...
}
```
If `double_value` is NaN, `NaN <= 0.0` is false and we should go to the else branch. However, current Spark goes to the if branch and causes correctness issues like SPARK-32640.
One way to fix it is:
```
boolean cond = double_value <= 0.0;
if (cond) {
...
} else {
...
}
```
I'm not familiar with Janino so I don't know what's going on there.
### Does this PR introduce _any_ user-facing change?
Yes, fix correctness bugs.
### How was this patch tested?
a new test
Closes#29495 from cloud-fan/revert.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
Disallow the use of unused imports:
- Unnecessary increases the memory footprint of the application
- Removes the imports that are required for the examples in the docstring from the file-scope to the example itself. This keeps the files itself clean, and gives a more complete example as it also includes the imports :)
```
fokkodriesprongFan spark % flake8 python | grep -i "imported but unused"
python/pyspark/cloudpickle.py:46:1: F401 'functools.partial' imported but unused
python/pyspark/cloudpickle.py:55:1: F401 'traceback' imported but unused
python/pyspark/heapq3.py:868:5: F401 '_heapq.*' imported but unused
python/pyspark/__init__.py:61:1: F401 'pyspark.version.__version__' imported but unused
python/pyspark/__init__.py:62:1: F401 'pyspark._globals._NoValue' imported but unused
python/pyspark/__init__.py:115:1: F401 'pyspark.sql.SQLContext' imported but unused
python/pyspark/__init__.py:115:1: F401 'pyspark.sql.HiveContext' imported but unused
python/pyspark/__init__.py:115:1: F401 'pyspark.sql.Row' imported but unused
python/pyspark/rdd.py:21:1: F401 're' imported but unused
python/pyspark/rdd.py:29:1: F401 'tempfile.NamedTemporaryFile' imported but unused
python/pyspark/mllib/regression.py:26:1: F401 'pyspark.mllib.linalg.SparseVector' imported but unused
python/pyspark/mllib/clustering.py:28:1: F401 'pyspark.mllib.linalg.SparseVector' imported but unused
python/pyspark/mllib/clustering.py:28:1: F401 'pyspark.mllib.linalg.DenseVector' imported but unused
python/pyspark/mllib/classification.py:26:1: F401 'pyspark.mllib.linalg.SparseVector' imported but unused
python/pyspark/mllib/feature.py:28:1: F401 'pyspark.mllib.linalg.DenseVector' imported but unused
python/pyspark/mllib/feature.py:28:1: F401 'pyspark.mllib.linalg.SparseVector' imported but unused
python/pyspark/mllib/feature.py:30:1: F401 'pyspark.mllib.regression.LabeledPoint' imported but unused
python/pyspark/mllib/tests/test_linalg.py:18:1: F401 'sys' imported but unused
python/pyspark/mllib/tests/test_linalg.py:642:5: F401 'pyspark.mllib.tests.test_linalg.*' imported but unused
python/pyspark/mllib/tests/test_feature.py:21:1: F401 'numpy.random' imported but unused
python/pyspark/mllib/tests/test_feature.py:21:1: F401 'numpy.exp' imported but unused
python/pyspark/mllib/tests/test_feature.py:23:1: F401 'pyspark.mllib.linalg.Vector' imported but unused
python/pyspark/mllib/tests/test_feature.py:23:1: F401 'pyspark.mllib.linalg.VectorUDT' imported but unused
python/pyspark/mllib/tests/test_feature.py:185:5: F401 'pyspark.mllib.tests.test_feature.*' imported but unused
python/pyspark/mllib/tests/test_util.py:97:5: F401 'pyspark.mllib.tests.test_util.*' imported but unused
python/pyspark/mllib/tests/test_stat.py:23:1: F401 'pyspark.mllib.linalg.Vector' imported but unused
python/pyspark/mllib/tests/test_stat.py:23:1: F401 'pyspark.mllib.linalg.SparseVector' imported but unused
python/pyspark/mllib/tests/test_stat.py:23:1: F401 'pyspark.mllib.linalg.DenseVector' imported but unused
python/pyspark/mllib/tests/test_stat.py:23:1: F401 'pyspark.mllib.linalg.VectorUDT' imported but unused
python/pyspark/mllib/tests/test_stat.py:23:1: F401 'pyspark.mllib.linalg._convert_to_vector' imported but unused
python/pyspark/mllib/tests/test_stat.py:23:1: F401 'pyspark.mllib.linalg.DenseMatrix' imported but unused
python/pyspark/mllib/tests/test_stat.py:23:1: F401 'pyspark.mllib.linalg.SparseMatrix' imported but unused
python/pyspark/mllib/tests/test_stat.py:23:1: F401 'pyspark.mllib.linalg.MatrixUDT' imported but unused
python/pyspark/mllib/tests/test_stat.py:181:5: F401 'pyspark.mllib.tests.test_stat.*' imported but unused
python/pyspark/mllib/tests/test_streaming_algorithms.py:18:1: F401 'time.time' imported but unused
python/pyspark/mllib/tests/test_streaming_algorithms.py:18:1: F401 'time.sleep' imported but unused
python/pyspark/mllib/tests/test_streaming_algorithms.py:470:5: F401 'pyspark.mllib.tests.test_streaming_algorithms.*' imported but unused
python/pyspark/mllib/tests/test_algorithms.py:295:5: F401 'pyspark.mllib.tests.test_algorithms.*' imported but unused
python/pyspark/tests/test_serializers.py:90:13: F401 'xmlrunner' imported but unused
python/pyspark/tests/test_rdd.py:21:1: F401 'sys' imported but unused
python/pyspark/tests/test_rdd.py:29:1: F401 'pyspark.resource.ResourceProfile' imported but unused
python/pyspark/tests/test_rdd.py:885:5: F401 'pyspark.tests.test_rdd.*' imported but unused
python/pyspark/tests/test_readwrite.py:19:1: F401 'sys' imported but unused
python/pyspark/tests/test_readwrite.py:22:1: F401 'array.array' imported but unused
python/pyspark/tests/test_readwrite.py:309:5: F401 'pyspark.tests.test_readwrite.*' imported but unused
python/pyspark/tests/test_join.py:62:5: F401 'pyspark.tests.test_join.*' imported but unused
python/pyspark/tests/test_taskcontext.py:19:1: F401 'shutil' imported but unused
python/pyspark/tests/test_taskcontext.py:325:5: F401 'pyspark.tests.test_taskcontext.*' imported but unused
python/pyspark/tests/test_conf.py:36:5: F401 'pyspark.tests.test_conf.*' imported but unused
python/pyspark/tests/test_broadcast.py:148:5: F401 'pyspark.tests.test_broadcast.*' imported but unused
python/pyspark/tests/test_daemon.py:76:5: F401 'pyspark.tests.test_daemon.*' imported but unused
python/pyspark/tests/test_util.py:77:5: F401 'pyspark.tests.test_util.*' imported but unused
python/pyspark/tests/test_pin_thread.py:19:1: F401 'random' imported but unused
python/pyspark/tests/test_pin_thread.py:149:5: F401 'pyspark.tests.test_pin_thread.*' imported but unused
python/pyspark/tests/test_worker.py:19:1: F401 'sys' imported but unused
python/pyspark/tests/test_worker.py:26:5: F401 'resource' imported but unused
python/pyspark/tests/test_worker.py:203:5: F401 'pyspark.tests.test_worker.*' imported but unused
python/pyspark/tests/test_profiler.py:101:5: F401 'pyspark.tests.test_profiler.*' imported but unused
python/pyspark/tests/test_shuffle.py:18:1: F401 'sys' imported but unused
python/pyspark/tests/test_shuffle.py:171:5: F401 'pyspark.tests.test_shuffle.*' imported but unused
python/pyspark/tests/test_rddbarrier.py:43:5: F401 'pyspark.tests.test_rddbarrier.*' imported but unused
python/pyspark/tests/test_context.py:129:13: F401 'userlibrary.UserClass' imported but unused
python/pyspark/tests/test_context.py:140:13: F401 'userlib.UserClass' imported but unused
python/pyspark/tests/test_context.py:310:5: F401 'pyspark.tests.test_context.*' imported but unused
python/pyspark/tests/test_appsubmit.py:241:5: F401 'pyspark.tests.test_appsubmit.*' imported but unused
python/pyspark/streaming/dstream.py:18:1: F401 'sys' imported but unused
python/pyspark/streaming/tests/test_dstream.py:27:1: F401 'pyspark.RDD' imported but unused
python/pyspark/streaming/tests/test_dstream.py:647:5: F401 'pyspark.streaming.tests.test_dstream.*' imported but unused
python/pyspark/streaming/tests/test_kinesis.py:83:5: F401 'pyspark.streaming.tests.test_kinesis.*' imported but unused
python/pyspark/streaming/tests/test_listener.py:152:5: F401 'pyspark.streaming.tests.test_listener.*' imported but unused
python/pyspark/streaming/tests/test_context.py:178:5: F401 'pyspark.streaming.tests.test_context.*' imported but unused
python/pyspark/testing/utils.py:30:5: F401 'scipy.sparse' imported but unused
python/pyspark/testing/utils.py:36:5: F401 'numpy as np' imported but unused
python/pyspark/ml/regression.py:25:1: F401 'pyspark.ml.tree._TreeEnsembleParams' imported but unused
python/pyspark/ml/regression.py:25:1: F401 'pyspark.ml.tree._HasVarianceImpurity' imported but unused
python/pyspark/ml/regression.py:29:1: F401 'pyspark.ml.wrapper.JavaParams' imported but unused
python/pyspark/ml/util.py:19:1: F401 'sys' imported but unused
python/pyspark/ml/__init__.py:25:1: F401 'pyspark.ml.pipeline' imported but unused
python/pyspark/ml/pipeline.py:18:1: F401 'sys' imported but unused
python/pyspark/ml/stat.py:22:1: F401 'pyspark.ml.linalg.DenseMatrix' imported but unused
python/pyspark/ml/stat.py:22:1: F401 'pyspark.ml.linalg.Vectors' imported but unused
python/pyspark/ml/tests/test_training_summary.py:18:1: F401 'sys' imported but unused
python/pyspark/ml/tests/test_training_summary.py:364:5: F401 'pyspark.ml.tests.test_training_summary.*' imported but unused
python/pyspark/ml/tests/test_linalg.py:381:5: F401 'pyspark.ml.tests.test_linalg.*' imported but unused
python/pyspark/ml/tests/test_tuning.py:427:9: F401 'pyspark.sql.functions as F' imported but unused
python/pyspark/ml/tests/test_tuning.py:757:5: F401 'pyspark.ml.tests.test_tuning.*' imported but unused
python/pyspark/ml/tests/test_wrapper.py:120:5: F401 'pyspark.ml.tests.test_wrapper.*' imported but unused
python/pyspark/ml/tests/test_feature.py:19:1: F401 'sys' imported but unused
python/pyspark/ml/tests/test_feature.py:304:5: F401 'pyspark.ml.tests.test_feature.*' imported but unused
python/pyspark/ml/tests/test_image.py:19:1: F401 'py4j' imported but unused
python/pyspark/ml/tests/test_image.py:22:1: F401 'pyspark.testing.mlutils.PySparkTestCase' imported but unused
python/pyspark/ml/tests/test_image.py:71:5: F401 'pyspark.ml.tests.test_image.*' imported but unused
python/pyspark/ml/tests/test_persistence.py:456:5: F401 'pyspark.ml.tests.test_persistence.*' imported but unused
python/pyspark/ml/tests/test_evaluation.py:56:5: F401 'pyspark.ml.tests.test_evaluation.*' imported but unused
python/pyspark/ml/tests/test_stat.py:43:5: F401 'pyspark.ml.tests.test_stat.*' imported but unused
python/pyspark/ml/tests/test_base.py:70:5: F401 'pyspark.ml.tests.test_base.*' imported but unused
python/pyspark/ml/tests/test_param.py:20:1: F401 'sys' imported but unused
python/pyspark/ml/tests/test_param.py:375:5: F401 'pyspark.ml.tests.test_param.*' imported but unused
python/pyspark/ml/tests/test_pipeline.py:62:5: F401 'pyspark.ml.tests.test_pipeline.*' imported but unused
python/pyspark/ml/tests/test_algorithms.py:333:5: F401 'pyspark.ml.tests.test_algorithms.*' imported but unused
python/pyspark/ml/param/__init__.py:18:1: F401 'sys' imported but unused
python/pyspark/resource/tests/test_resources.py:17:1: F401 'random' imported but unused
python/pyspark/resource/tests/test_resources.py:20:1: F401 'pyspark.resource.ResourceProfile' imported but unused
python/pyspark/resource/tests/test_resources.py:75:5: F401 'pyspark.resource.tests.test_resources.*' imported but unused
python/pyspark/sql/functions.py:32:1: F401 'pyspark.sql.udf.UserDefinedFunction' imported but unused
python/pyspark/sql/functions.py:34:1: F401 'pyspark.sql.pandas.functions.pandas_udf' imported but unused
python/pyspark/sql/session.py:30:1: F401 'pyspark.sql.types.Row' imported but unused
python/pyspark/sql/session.py:30:1: F401 'pyspark.sql.types.StringType' imported but unused
python/pyspark/sql/readwriter.py:1084:5: F401 'pyspark.sql.Row' imported but unused
python/pyspark/sql/context.py:26:1: F401 'pyspark.sql.types.IntegerType' imported but unused
python/pyspark/sql/context.py:26:1: F401 'pyspark.sql.types.Row' imported but unused
python/pyspark/sql/context.py:26:1: F401 'pyspark.sql.types.StringType' imported but unused
python/pyspark/sql/context.py:27:1: F401 'pyspark.sql.udf.UDFRegistration' imported but unused
python/pyspark/sql/streaming.py:1212:5: F401 'pyspark.sql.Row' imported but unused
python/pyspark/sql/tests/test_utils.py:55:5: F401 'pyspark.sql.tests.test_utils.*' imported but unused
python/pyspark/sql/tests/test_pandas_map.py:18:1: F401 'sys' imported but unused
python/pyspark/sql/tests/test_pandas_map.py:22:1: F401 'pyspark.sql.functions.pandas_udf' imported but unused
python/pyspark/sql/tests/test_pandas_map.py:22:1: F401 'pyspark.sql.functions.PandasUDFType' imported but unused
python/pyspark/sql/tests/test_pandas_map.py:119:5: F401 'pyspark.sql.tests.test_pandas_map.*' imported but unused
python/pyspark/sql/tests/test_catalog.py:193:5: F401 'pyspark.sql.tests.test_catalog.*' imported but unused
python/pyspark/sql/tests/test_group.py:39:5: F401 'pyspark.sql.tests.test_group.*' imported but unused
python/pyspark/sql/tests/test_session.py:361:5: F401 'pyspark.sql.tests.test_session.*' imported but unused
python/pyspark/sql/tests/test_conf.py:49:5: F401 'pyspark.sql.tests.test_conf.*' imported but unused
python/pyspark/sql/tests/test_pandas_cogrouped_map.py:19:1: F401 'sys' imported but unused
python/pyspark/sql/tests/test_pandas_cogrouped_map.py:21:1: F401 'pyspark.sql.functions.sum' imported but unused
python/pyspark/sql/tests/test_pandas_cogrouped_map.py:21:1: F401 'pyspark.sql.functions.PandasUDFType' imported but unused
python/pyspark/sql/tests/test_pandas_cogrouped_map.py:29:5: F401 'pandas.util.testing.assert_series_equal' imported but unused
python/pyspark/sql/tests/test_pandas_cogrouped_map.py:32:5: F401 'pyarrow as pa' imported but unused
python/pyspark/sql/tests/test_pandas_cogrouped_map.py:248:5: F401 'pyspark.sql.tests.test_pandas_cogrouped_map.*' imported but unused
python/pyspark/sql/tests/test_udf.py:24:1: F401 'py4j' imported but unused
python/pyspark/sql/tests/test_pandas_udf_typehints.py:246:5: F401 'pyspark.sql.tests.test_pandas_udf_typehints.*' imported but unused
python/pyspark/sql/tests/test_functions.py:19:1: F401 'sys' imported but unused
python/pyspark/sql/tests/test_functions.py:362:9: F401 'pyspark.sql.functions.exists' imported but unused
python/pyspark/sql/tests/test_functions.py:387:5: F401 'pyspark.sql.tests.test_functions.*' imported but unused
python/pyspark/sql/tests/test_pandas_udf_scalar.py:21:1: F401 'sys' imported but unused
python/pyspark/sql/tests/test_pandas_udf_scalar.py:45:5: F401 'pyarrow as pa' imported but unused
python/pyspark/sql/tests/test_pandas_udf_window.py:355:5: F401 'pyspark.sql.tests.test_pandas_udf_window.*' imported but unused
python/pyspark/sql/tests/test_arrow.py:38:5: F401 'pyarrow as pa' imported but unused
python/pyspark/sql/tests/test_pandas_grouped_map.py:20:1: F401 'sys' imported but unused
python/pyspark/sql/tests/test_pandas_grouped_map.py:38:5: F401 'pyarrow as pa' imported but unused
python/pyspark/sql/tests/test_dataframe.py:382:9: F401 'pyspark.sql.DataFrame' imported but unused
python/pyspark/sql/avro/functions.py:125:5: F401 'pyspark.sql.Row' imported but unused
python/pyspark/sql/pandas/functions.py:19:1: F401 'sys' imported but unused
```
After:
```
fokkodriesprongFan spark % flake8 python | grep -i "imported but unused"
fokkodriesprongFan spark %
```
### What changes were proposed in this pull request?
Removing unused imports from the Python files to keep everything nice and tidy.
### Why are the changes needed?
Cleaning up of the imports that aren't used, and suppressing the imports that are used as references to other modules, preserving backward compatibility.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Adding the rule to the existing Flake8 checks.
Closes#29121 from Fokko/SPARK-32319.
Authored-by: Fokko Driesprong <fokko@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
1. URL encode the `ASF_PASSWORD` of the release manager.
2. Update the image to install `qpdf` and `jq` dep
3. Increase the JVM HEAM memory for maven build.
### Why are the changes needed?
Release script takes hours to run, and if a single failure happens about somewhere midway, then either one has to get down to manually doing stuff or re run the entire script. (This is my understanding) So, I have made the fixes of a few failures, discovered so far.
1. If the release manager password contains a char, that is not allowed in URL, then it fails the build at the clone spark step.
`git clone "https://$ASF_USERNAME:$ASF_PASSWORD$ASF_SPARK_REPO" -b $GIT_BRANCH`
^^^ Fails with bad URL
`ASF_USERNAME` may not be URL encoded, but we need to encode `ASF_PASSWORD`.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running the release for branch-2.4, using both type of passwords, i.e. passwords with special chars and without it.
Closes#29373 from ScrapCodes/release-script-fix2.
Lead-authored-by: Prashant Sharma <prashant@apache.org>
Co-authored-by: Prashant Sharma <prashsh1@in.ibm.com>
Signed-off-by: Prashant Sharma <prashant@apache.org>
### What changes were proposed in this pull request?
CRAN check fails due to the size of the generated PDF docs as below:
```
...
WARNING
‘qpdf’ is needed for checks on size reduction of PDFs
...
Status: 1 WARNING, 1 NOTE
See
‘/home/runner/work/spark/spark/R/SparkR.Rcheck/00check.log’
for details.
```
This PR proposes to install `qpdf` in GitHub Actions.
Note that I cannot reproduce in my local with the same R version so I am not documenting it for now.
Also, while I am here, I piggyback to install SparkR when the module includes `sparkr`. it is rather a followup of SPARK-32491.
### Why are the changes needed?
To fix SparkR CRAN check failure.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
GitHub Actions will test it out.
Closes#29306 from HyukjinKwon/SPARK-32497.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
https://github.com/apache/spark/pull/26556 excluded `.github/workflows/master.yml`. So tests are skipped if the GitHub Actions configuration file is changed.
As of SPARK-32245, we now run the regular tests via the testing script. We should include it to test to make sure GitHub Actions build does not break due to some changes such as Python versions.
### Why are the changes needed?
For better test coverage in GitHub Actions build.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
GitHub Actions in this PR will test.
Closes#29305 from HyukjinKwon/SPARK-32496.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes to skip SparkR installation that is to run R linters (see SPARK-8505) in the test-only mode at `dev/run-tests.py` script.
As of SPARK-32292, the test-only mode in `dev/run-tests.py` was introduced, for example:
```
dev/run-tests.py --modules sql,core
```
which only runs the relevant tests and does not run other tests such as linters. Therefore, we don't need to install SparkR when `--modules` are specified.
### Why are the changes needed?
GitHub Actions build is currently failed as below:
```
ERROR: this R is version 3.4.4, package 'SparkR' requires R >= 3.5
[error] running /home/runner/work/spark/spark/R/install-dev.sh ; received return code 1
##[error]Process completed with exit code 10.
```
For some reasons, looks GitHub Actions started to have R 3.4.4 installed by default; however, R 3.4 was dropped as of SPARK-32073. When SparkR tests are not needed, GitHub Actions still builds SparkR with a low R version and it causes the test failure.
This PR partially fixes it by avoid the installation of SparkR.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
GitHub Actions tests should run to confirm this fix is correct.
Closes#29300 from HyukjinKwon/install-r.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR removes the manual port of `heapq3.py` introduced from SPARK-3073. The main reason of this was to support Python 2.6 and 2.7 because Python 2's `heapq.merge()` doesn't not support `key` and `reverse`.
See
- https://docs.python.org/2/library/heapq.html#heapq.merge in Python 2
- https://docs.python.org/3.8/library/heapq.html#heapq.merge in Python 3
Since we dropped the Python 2 at SPARK-32138, we can remove this away.
### Why are the changes needed?
To remove unnecessary codes. Also, we can leverage bug fixes made in Python 3.x at `heapq`.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Existing tests should cover. I locally ran and verified:
```bash
./python/run-tests --python-executable=python3 --testname="pyspark.tests.test_shuffle"
./python/run-tests --python-executable=python3 --testname="pyspark.shuffle ExternalSorter"
./python/run-tests --python-executable=python3 --testname="pyspark.tests.test_rdd RDDTests.test_external_group_by_key"
```
Closes#29229 from HyukjinKwon/SPARK-32435.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes to redesign the PySpark documentation.
I made a demo site to make it easier to review: https://hyukjin-spark.readthedocs.io/en/stable/reference/index.html.
Here is the initial draft for the final PySpark docs shape: https://hyukjin-spark.readthedocs.io/en/latest/index.html.
In more details, this PR proposes:
1. Use [pydata_sphinx_theme](https://github.com/pandas-dev/pydata-sphinx-theme) theme - [pandas](https://pandas.pydata.org/docs/) and [Koalas](https://koalas.readthedocs.io/en/latest/) use this theme. The CSS overwrite is ported from Koalas. The colours in the CSS were actually chosen by designers to use in Spark.
2. Use the Sphinx option to separate `source` and `build` directories as the documentation pages will likely grow.
3. Port current API documentation into the new style. It mimics Koalas and pandas to use the theme most effectively.
One disadvantage of this approach is that you should list up APIs or classes; however, I think this isn't a big issue in PySpark since we're being conservative on adding APIs. I also intentionally listed classes only instead of functions in ML and MLlib to make it relatively easier to manage.
### Why are the changes needed?
Often I hear the complaints, from the users, that current PySpark documentation is pretty messy to read - https://spark.apache.org/docs/latest/api/python/index.html compared other projects such as [pandas](https://pandas.pydata.org/docs/) and [Koalas](https://koalas.readthedocs.io/en/latest/).
It would be nicer if we can make it more organised instead of just listing all classes, methods and attributes to make it easier to navigate.
Also, the documentation has been there from almost the very first version of PySpark. Maybe it's time to update it.
### Does this PR introduce _any_ user-facing change?
Yes, PySpark API documentation will be redesigned.
### How was this patch tested?
Manually tested, and the demo site was made to show.
Closes#29188 from HyukjinKwon/SPARK-32179.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This patch upgrades pycodestyle from v2.4.0 to v2.6.0. The changes at each release:
2.5.0: https://pycodestyle.pycqa.org/en/latest/developer.html#id3
2.6.0a1: https://pycodestyle.pycqa.org/en/latest/developer.html#a1-2020-04-23
2.6.0: https://pycodestyle.pycqa.org/en/latest/developer.html#id2
Changes: Dropped Python 2.6 and 3.3 support, added Python 3.7 and 3.8 support...
### Why are the changes needed?
Including bug fixes and newer Python version support.
### Does this PR introduce _any_ user-facing change?
No, dev only.
### How was this patch tested?
Ran `dev/lint-python` locally.
Closes#29249 from viirya/upgrade-pycodestyle.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to upgrade `json4s` to from 3.6.6 to 3.7.0-M5 for Scala 2.13 support at Apache Spark 3.1.0 on December. We will upgrade to the latest `json4s` around November.
### Why are the changes needed?
`json4s` starts to support Scala 2.13 since v3.7.0-M4.
- https://github.com/json4s/json4s/issues/660
- b013af8e75
Old `json4s` causes many UT failures with `NoSuchMethodException`.
```scala
Cause: java.lang.NoSuchMethodException: scala.collection.immutable.Seq$.apply(scala.collection.Seq)
at java.lang.Class.getMethod(Class.java:1786)
```
The following is one example.
```scala
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.executor.CoarseGrainedExecutorBackendSuite
...
Tests: succeeded 4, failed 9, canceled 0, ignored 0, pending 0
*** 9 TESTS FAILED ***
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
1. **Scala 2.12**: Pass the Jenkins or GitHub Action with the existing tests.
2. **Scala 2.13**: Do the following manually at least.
```scala
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.executor.CoarseGrainedExecutorBackendSuite
...
Tests: succeeded 13, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#29239 from dongjoon-hyun/SPARK-32441.
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 proposes to avoid using subshell when it activates Conda environment. Looks like it ends up with activating the env within the subshell even if you use `conda` command.
### Why are the changes needed?
If you take a close look for GitHub Actions log:
```
Installing dist into virtual env
Processing ./python/dist/pyspark-3.1.0.dev0.tar.gz
Collecting py4j==0.10.9
Downloading py4j-0.10.9-py2.py3-none-any.whl (198 kB)
Using legacy setup.py install for pyspark, since package 'wheel' is not installed.
Installing collected packages: py4j, pyspark
Running setup.py install for pyspark: started
Running setup.py install for pyspark: finished with status 'done'
Successfully installed py4j-0.10.9 pyspark-3.1.0.dev0
...
Installing dist into virtual env
Obtaining file:///home/runner/work/spark/spark/python
Collecting py4j==0.10.9
Downloading py4j-0.10.9-py2.py3-none-any.whl (198 kB)
Installing collected packages: py4j, pyspark
Attempting uninstall: py4j
Found existing installation: py4j 0.10.9
Uninstalling py4j-0.10.9:
Successfully uninstalled py4j-0.10.9
Attempting uninstall: pyspark
Found existing installation: pyspark 3.1.0.dev0
Uninstalling pyspark-3.1.0.dev0:
Successfully uninstalled pyspark-3.1.0.dev0
Running setup.py develop for pyspark
Successfully installed py4j-0.10.9 pyspark
```
It looks not properly using Conda as it removes the previously installed one when it reinstalls again.
We should ideally test it with Conda environment as it's intended.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
GitHub Actions will test. I also manually tested in my local.
Closes#29212 from HyukjinKwon/SPARK-32419.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This reverts commit 026b0b926d.
### Why are the changes needed?
As HyukjinKwon pointed out in https://github.com/apache/spark/pull/29133#issuecomment-663339240, there is no JUnit test report after https://github.com/apache/spark/pull/29133. Let's revert https://github.com/apache/spark/pull/29133 for now and find a better solution to improve the log output later.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
GitHub Actions build
Closes#29219 from gengliangwang/revertErrorOnly.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
Updates to scalatest 3.2.0. Though it looks large, it is 99% changes to the new location of scalatest classes.
### Why are the changes needed?
3.2.0+ has a fix that is required for Scala 2.13.3+ compatibility.
### Does this PR introduce _any_ user-facing change?
No, only affects tests.
### How was this patch tested?
Existing tests.
Closes#29196 from srowen/SPARK-32398.
Authored-by: Sean Owen <srowen@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR proposes:
- Don't use `--user` in pip packaging test
- Pull `source` out of the subshell, and place it first.
- Exclude user sitepackages in Python path during pip installation test
to address the flakiness of the pip packaging test in Jenkins.
(I think) #29116 caused this flakiness given my observation in the Jenkins log. I had to work around by specifying `--user` but it turned out that it does not properly work in old Conda on Jenkins for some reasons. Therefore, reverting this change back.
(I think) the installation at user site-packages affects other environments created by Conda in the old Conda version that Jenkins has. Seems it fails to isolate the environments for some reasons. So, it excludes user sitepackages in the Python path during the test.
In addition, #29116 also added some fallback logics of `conda (de)activate` and `source (de)activate` because Conda prefers to use `conda (de)activate` now per the official documentation and `source (de)activate` doesn't work for some reasons in certain environments (see also https://github.com/conda/conda/issues/7980). The problem was that `source` loads things to the current shell so does not affect the current shell. Therefore, this PR pulls `source` out of the subshell.
Disclaimer: I made the analysis purely based on Jenkins machine's log in this PR. It may have a different reason I missed during my observation.
### Why are the changes needed?
To make the build and tests pass in Jenkins.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Jenkins tests should test it out.
Closes#29117 from HyukjinKwon/debug-conda.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Use `/usr/bin/env python3` consistently instead of `/usr/bin/env python` in build scripts, to reliably select Python 3.
### Why are the changes needed?
Scripts no longer work with Python 2.
### Does this PR introduce _any_ user-facing change?
No, should be all build system changes.
### How was this patch tested?
Existing tests / NA
Closes#29151 from srowen/SPARK-29909.2.
Authored-by: Sean Owen <srowen@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to rename `HADOOP2_MODULE_PROFILES` to `HADOOP_MODULE_PROFILES` because Hadoop 3 is now the default.
### Why are the changes needed?
Hadoop 3 is now the default.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass GitHub Action dependency test.
Closes#29128 from williamhyun/williamhyun-patch-3.
Authored-by: williamhyun <62487364+williamhyun@users.noreply.github.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR aims to upgrade PySpark's embedded cloudpickle to the latest cloudpickle v1.5.0 (See https://github.com/cloudpipe/cloudpickle/blob/v1.5.0/cloudpickle/cloudpickle.py)
### Why are the changes needed?
There are many bug fixes. For example, the bug described in the JIRA:
dill unpickling fails because they define `types.ClassType`, which is undefined in dill. This results in the following error:
```
Traceback (most recent call last):
File "/usr/local/lib/python3.6/site-packages/apache_beam/internal/pickler.py", line 279, in loads
return dill.loads(s)
File "/usr/local/lib/python3.6/site-packages/dill/_dill.py", line 317, in loads
return load(file, ignore)
File "/usr/local/lib/python3.6/site-packages/dill/_dill.py", line 305, in load
obj = pik.load()
File "/usr/local/lib/python3.6/site-packages/dill/_dill.py", line 577, in _load_type
return _reverse_typemap[name]
KeyError: 'ClassType'
```
See also https://github.com/cloudpipe/cloudpickle/issues/82. This was fixed for cloudpickle 1.3.0+ (https://github.com/cloudpipe/cloudpickle/pull/337), but PySpark's cloudpickle.py doesn't have this change yet.
More notably, now it supports C pickle implementation with Python 3.8 which hugely improve performance. This is already adopted in another project such as Ray.
### Does this PR introduce _any_ user-facing change?
Yes, as described above, the bug fixes. Internally, users also could leverage the fast cloudpickle backed by C pickle.
### How was this patch tested?
Jenkins will test it out.
Closes#29114 from HyukjinKwon/SPARK-32094.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR will remove references to these "blacklist" and "whitelist" terms besides the blacklisting feature as a whole, which can be handled in a separate JIRA/PR.
This touches quite a few files, but the changes are straightforward (variable/method/etc. name changes) and most quite self-contained.
### Why are the changes needed?
As per discussion on the Spark dev list, it will be beneficial to remove references to problematic language that can alienate potential community members. One such reference is "blacklist" and "whitelist". While it seems to me that there is some valid debate as to whether these terms have racist origins, the cultural connotations are inescapable in today's world.
### Does this PR introduce _any_ user-facing change?
In the test file `HiveQueryFileTest`, a developer has the ability to specify the system property `spark.hive.whitelist` to specify a list of Hive query files that should be tested. This system property has been renamed to `spark.hive.includelist`. The old property has been kept for compatibility, but will log a warning if used. I am open to feedback from others on whether keeping a deprecated property here is unnecessary given that this is just for developers running tests.
### How was this patch tested?
Existing tests should be suitable since no behavior changes are expected as a result of this PR.
Closes#28874 from xkrogen/xkrogen-SPARK-32036-rename-blacklists.
Authored-by: Erik Krogen <ekrogen@linkedin.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
Currently the Jenkins PIP packaging test fails as below intermediately:
```
Installing dist into virtual env
Processing ./python/dist/pyspark-3.1.0.dev0.tar.gz
Collecting py4j==0.10.9 (from pyspark==3.1.0.dev0)
Downloading 6a4fb90cd2/py4j-0.10.9-py2.py3-none-any.whl (198kB)
Installing collected packages: py4j, pyspark
Found existing installation: py4j 0.10.9
Uninstalling py4j-0.10.9:
Successfully uninstalled py4j-0.10.9
Found existing installation: pyspark 3.1.0.dev0
Exception:
Traceback (most recent call last):
File "/home/anaconda/envs/py36/lib/python3.6/site-packages/pip/_internal/cli/base_command.py", line 179, in main
status = self.run(options, args)
File "/home/anaconda/envs/py36/lib/python3.6/site-packages/pip/_internal/commands/install.py", line 393, in run
use_user_site=options.use_user_site,
File "/home/anaconda/envs/py36/lib/python3.6/site-packages/pip/_internal/req/__init__.py", line 50, in install_given_reqs
auto_confirm=True
File "/home/anaconda/envs/py36/lib/python3.6/site-packages/pip/_internal/req/req_install.py", line 816, in uninstall
uninstalled_pathset = UninstallPathSet.from_dist(dist)
File "/home/anaconda/envs/py36/lib/python3.6/site-packages/pip/_internal/req/req_uninstall.py", line 505, in from_dist
'(at %s)' % (link_pointer, dist.project_name, dist.location)
AssertionError: Egg-link /home/jenkins/workspace/SparkPullRequestBuilder3/python does not match installed
```
- https://github.com/apache/spark/pull/29099#issuecomment-658073453 (amp-jenkins-worker-04)
- https://github.com/apache/spark/pull/29090#issuecomment-657819973 (amp-jenkins-worker-03)
Seems like the previous installation of editable mode affects other PRs.
This PR simply works around by removing the symbolic link from the previous editable installation. This is a common workaround up to my knowledge.
### Why are the changes needed?
To recover the Jenkins build.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Jenkins build will test it out.
Closes#29102 from HyukjinKwon/SPARK-32303.
Lead-authored-by: HyukjinKwon <gurwls223@apache.org>
Co-authored-by: Hyukjin Kwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to drop Python 2.7, 3.4 and 3.5.
Roughly speaking, it removes all the widely known Python 2 compatibility workarounds such as `sys.version` comparison, `__future__`. Also, it removes the Python 2 dedicated codes such as `ArrayConstructor` in Spark.
### Why are the changes needed?
1. Unsupport EOL Python versions
2. Reduce maintenance overhead and remove a bit of legacy codes and hacks for Python 2.
3. PyPy2 has a critical bug that causes a flaky test, SPARK-28358 given my testing and investigation.
4. Users can use Python type hints with Pandas UDFs without thinking about Python version
5. Users can leverage one latest cloudpickle, https://github.com/apache/spark/pull/28950. With Python 3.8+ it can also leverage C pickle.
### Does this PR introduce _any_ user-facing change?
Yes, users cannot use Python 2.7, 3.4 and 3.5 in the upcoming Spark version.
### How was this patch tested?
Manually tested and also tested in Jenkins.
Closes#28957 from HyukjinKwon/SPARK-32138.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR mainly proposes to run only relevant tests just like Jenkins PR builder does. Currently, GitHub Actions always run full tests which wastes the resources.
In addition, this PR also fixes 3 more issues very closely related together while I am here.
1. The main idea here is: It reuses the existing logic embedded in `dev/run-tests.py` which Jenkins PR builder use in order to run only the related test cases.
2. While I am here, I fixed SPARK-32292 too to run the doc tests. It was because other references were not available when it is cloned via `checkoutv2`. With `fetch-depth: 0`, the history is available.
3. In addition, it fixes the `dev/run-tests.py` to match with `python/run-tests.py` in terms of its options. Environment variables such as `TEST_ONLY_XXX` were moved as proper options. For example,
```bash
dev/run-tests.py --modules sql,core
```
which is consistent with `python/run-tests.py`, for example,
```bash
python/run-tests.py --modules pyspark-core,pyspark-ml
```
4. Lastly, also fixed the formatting issue in module specification in the matrix:
```diff
- network_common, network_shuffle, repl, launcher
+ network-common, network-shuffle, repl, launcher,
```
which incorrectly runs build/test the modules.
### Why are the changes needed?
By running only related tests, we can hugely save the resources and avoid unrelated flaky tests, etc.
Also, now it runs the doctest of `dev/run-tests.py` properly, the usages are similar between `dev/run-tests.py` and `python/run-tests.py`, and run `network-common`, `network-shuffle`, `launcher` and `examples` modules too.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Manually tested in my own forked Spark:
https://github.com/HyukjinKwon/spark/pull/7https://github.com/HyukjinKwon/spark/pull/8https://github.com/HyukjinKwon/spark/pull/9https://github.com/HyukjinKwon/spark/pull/10https://github.com/HyukjinKwon/spark/pull/11https://github.com/HyukjinKwon/spark/pull/12Closes#29086 from HyukjinKwon/SPARK-32292.
Authored-by: Hyukjin Kwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to run the Spark tests in Github Actions.
To briefly explain the main idea:
- Reuse `dev/run-tests.py` with SBT build
- Reuse the modules in `dev/sparktestsupport/modules.py` to test each module
- Pass the modules to test into `dev/run-tests.py` directly via `TEST_ONLY_MODULES` environment variable. For example, `pyspark-sql,core,sql,hive`.
- `dev/run-tests.py` _does not_ take the dependent modules into account but solely the specified modules to test.
Another thing to note might be `SlowHiveTest` annotation. Running the tests in Hive modules takes too much so the slow tests are extracted and it runs as a separate job. It was extracted from the actual elapsed time in Jenkins:
So, Hive tests are separated into to jobs. One is slow test cases, and the other one is the other test cases.
_Note that_ the current GitHub Actions build virtually copies what the default PR builder on Jenkins does (without other profiles such as JDK 11, Hadoop 2, etc.). The only exception is Kinesis https://github.com/apache/spark/pull/29057/files#diff-04eb107ee163a50b61281ca08f4e4c7bR23
### Why are the changes needed?
Last week and onwards, the Jenkins machines became very unstable for many reasons:
- Apparently, the machines became extremely slow. Almost all tests can't pass.
- One machine (worker 4) started to have the corrupt `.m2` which fails the build.
- Documentation build fails time to time for an unknown reason in Jenkins machine specifically. This is disabled for now at https://github.com/apache/spark/pull/29017.
- Almost all PRs are basically blocked by this instability currently.
The advantages of using Github Actions:
- To avoid depending on few persons who can access to the cluster.
- To reduce the elapsed time in the build - we could split the tests (e.g., SQL, ML, CORE), and run them in parallel so the total build time will significantly reduce.
- To control the environment more flexibly.
- Other contributors can test and propose to fix Github Actions configurations so we can distribute this build management cost.
Note that:
- The current build in Jenkins takes _more than 7 hours_. With Github actions it takes _less than 2 hours_
- We can now control the environments especially for Python easily.
- The test and build look more stable than the Jenkins'.
### Does this PR introduce _any_ user-facing change?
No, dev-only change.
### How was this patch tested?
Tested at https://github.com/HyukjinKwon/spark/pull/4Closes#29057 from HyukjinKwon/migrate-to-github-actions.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to upgrade to ZStd 1.4.5-4.
### Why are the changes needed?
ZStd 1.4.5-4 fixes the following.
- 3d16e51525
- 3d51bdcb82
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the Jenkins.
Closes#28969 from williamhyun/zstd2.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes to use Hadoop 3 winutils to make AppVeyor builds pass. Currently it's being failed as below
https://ci.appveyor.com/project/ApacheSoftwareFoundation/spark/builds/33976604
### Why are the changes needed?
To recover the build in AppVeyor.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
AppVeyor build will test it out.
Closes#29042 from HyukjinKwon/SPARK-32231.
Lead-authored-by: Dongjoon Hyun <dongjoon@apache.org>
Co-authored-by: Hyukjin Kwon <gurwls223@apache.org>
Co-authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to disable dependency tests(test-dependencies.sh) from Jenkins.
### Why are the changes needed?
- First of all, GitHub Action provides the same test capability already and stabler.
- Second, currently, `test-dependencies.sh` fails very frequently in AmpLab Jenkins environment. For example, in the following irrelevant PR, it fails 5 times during 6 hours.
- https://github.com/apache/spark/pull/29001
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the Jenkins without `test-dependencies.sh` invocation.
Closes#29004 from dongjoon-hyun/SPARK-32178.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
According to the dev mailing list discussion, this PR aims to switch the default Apache Hadoop dependency from 2.7.4 to 3.2.0 for Apache Spark 3.1.0 on December 2020.
| Item | Default Hadoop Dependency |
|------|-----------------------------|
| Apache Spark Website | 3.2.0 |
| Apache Download Site | 3.2.0 |
| Apache Snapshot | 3.2.0 |
| Maven Central | 3.2.0 |
| PyPI | 2.7.4 (We will switch later) |
| CRAN | 2.7.4 (We will switch later) |
| Homebrew | 3.2.0 (already) |
In Apache Spark 3.0.0 release, we focused on the other features. This PR targets for [Apache Spark 3.1.0 scheduled on December 2020](https://spark.apache.org/versioning-policy.html).
### Why are the changes needed?
Apache Hadoop 3.2 has many fixes and new cloud-friendly features.
**Reference**
- 2017-08-04: https://hadoop.apache.org/release/2.7.4.html
- 2019-01-16: https://hadoop.apache.org/release/3.2.0.html
### Does this PR introduce _any_ user-facing change?
Since the default Hadoop dependency changes, the users will get a better support in a cloud environment.
### How was this patch tested?
Pass the Jenkins.
Closes#28897 from dongjoon-hyun/SPARK-32058.
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 proposes to upgrade R version to 4.0.2 in the release docker image. As of SPARK-31918, we should make a release with R 4.0.0+ which works with R 3.5+ too.
### Why are the changes needed?
To unblock releases on CRAN.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Manually tested via scripts under `dev/create-release`, manually attaching to the container and checking the R version.
Closes#28922 from HyukjinKwon/SPARK-32089.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
R version 4.0.2 was released, see https://cran.r-project.org/doc/manuals/r-release/NEWS.html. This PR targets to upgrade R version in AppVeyor CI environment.
### Why are the changes needed?
To test the latest R versions before the release, and see if there are any regressions.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
AppVeyor will test.
Closes#28909 from HyukjinKwon/SPARK-32074.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to upgrade to Apache Commons Lang 3.10.
### Why are the changes needed?
This will bring the latest bug fixes like [LANG-1453](https://issues.apache.org/jira/browse/LANG-1453).
https://commons.apache.org/proper/commons-lang/release-notes/RELEASE-NOTES-3.10.txt
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the Jenkins.
Closes#28889 from williamhyun/commons-lang-3.10.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
This is auto-updated by running script `translate-contributors.py`
Closes#28861 from cloud-fan/update.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
If a Spark distribution has built-in hadoop runtime, Spark will not populate the hadoop classpath from `yarn.application.classpath` and `mapreduce.application.classpath` when a job is submitted to Yarn. Users can override this behavior by setting `spark.yarn.populateHadoopClasspath` to `true`.
### Why are the changes needed?
Without this, Spark will populate the hadoop classpath from `yarn.application.classpath` and `mapreduce.application.classpath` even Spark distribution has built-in hadoop. This results jar conflict and many unexpected behaviors in runtime.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manually test with two builds, with-hadoop and no-hadoop builds.
Closes#28788 from dbtsai/yarn-classpath.
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?
After #28192, the job list page becomes very slow.
For example, after the following operation, the UI loading can take >40 sec.
```
(1 to 1000).foreach(_ => sc.parallelize(1 to 10).collect)
```
This is caused by a [performance issue of `vis-timeline`](https://github.com/visjs/vis-timeline/issues/379). The serious issue affects both branch-3.0 and branch-2.4
I tried a different version 4.21.0 from https://cdnjs.com/libraries/vis
The infinite drawing issue seems also fixed if the zoom is disabled as default.
### Why are the changes needed?
Fix the serious perf issue in web UI by falling back vis-timeline-graph2d to an ealier version.
### Does this PR introduce _any_ user-facing change?
Yes, fix the UI perf regression
### How was this patch tested?
Manual test
Closes#28806 from gengliangwang/downgradeVis.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
When removing non-existing files in the release script, do not fail.
### Why are the changes needed?
This is to make the release script more robust, as we don't care if the files exist before we remove them.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
tested when cutting 3.0.0 RC
Closes#28815 from cloud-fan/release.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
