### What changes were proposed in this pull request?
Disallow `FileSystem.get(Configuration conf)` in Scala style check by default and suggest developers use `FileSystem.get(URI uri, Configuration conf)` or `Path.getFileSystem()` instead.
### Why are the changes needed?
The method `FileSystem.get(Configuration conf)` will return a default FileSystem instance if the conf `fs.file.impl` is not set. This can cause file not found exception on reading a target path of non-default file system, e.g. S3. It is hard to discover such a mistake via unit tests.
If we disallow it in Scala style check by default and suggest developers use `FileSystem.get(URI uri, Configuration conf)` or `Path.getFileSystem(Configuration conf)`, we can reduce potential regression and PR review effort.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manually run scala style check and test.
Closes#29357 from gengliangwang/newStyleRule.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
1. Make `CoarseGrainedSchedulerBackend.maxNumConcurrentTasks()` considers all kinds of resources when calculating the max concurrent tasks
2. Refactor `calculateAvailableSlots()` to make it be able to be used for both `CoarseGrainedSchedulerBackend` and `TaskSchedulerImpl`
### Why are the changes needed?
Currently, `CoarseGrainedSchedulerBackend.maxNumConcurrentTasks()` only considers the CPU for the max concurrent tasks. This can cause the application to hang when a barrier stage requires extra custom resources but the cluster doesn't have enough corresponding resources. Because, without the checking for other custom resources in `maxNumConcurrentTasks`, the barrier stage can be submitted to the `TaskSchedulerImpl`. But the `TaskSchedulerImpl` won't launch tasks for the barrier stage due to the insufficient task slots calculated by `TaskSchedulerImpl.calculateAvailableSlots` (which does check all kinds of resources).
The application hang issue can be reproduced by the added unit test.
### Does this PR introduce _any_ user-facing change?
Yes. In case of a barrier stage requires more custom resources than the cluster has, the application can get hang before this PR but can fail due to insufficient resources at the end after this PR.
### How was this patch tested?
Added a unit test.
Closes#29332 from Ngone51/fix-slots.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Exit the executor when it has been asked to decommission and there is nothing left for it to do.
This is a rebase of https://github.com/apache/spark/pull/28817
### Why are the changes needed?
If we want to use decommissioning in Spark's own scale down we should terminate the executor once finished.
Furthermore, in graceful shutdown it makes sense to release resources we no longer need if we've been asked to shutdown by the cluster manager instead of always holding the resources as long as possible.
### Does this PR introduce _any_ user-facing change?
The decommissioned executors will exit and the end of decommissioning. This is sort of a user facing change, however decommissioning hasn't been in any releases yet.
### How was this patch tested?
I changed the unit test to not send the executor exit message and still wait on the executor exited message.
Closes#29211 from holdenk/SPARK-31197-exit-execs-redone.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
# What changes were proposed in this pull request?
This PR adds a `FileNotFoundException` try catch block while adding a new entry to history server application listing to skip the non-existing path.
### Why are the changes needed?
If there are a large number (>100k) of applications log dir, listing the log dir will take a few seconds. After getting the path list some applications might have finished already, and the filename will change from `foo.inprogress` to `foo`.
It leads to a problem when adding an entry to the listing, querying file status like `fileSizeForLastIndex` will throw out a `FileNotFoundException` exception if the application was finished. And the exception will abort current loop, in a busy cluster, it will make history server couldn't list and load any application log.
```
20/08/03 15:17:23 ERROR FsHistoryProvider: Exception in checking for event log updates
java.io.FileNotFoundException: File does not exist: hdfs://xx/logs/spark/application_11111111111111.lz4.inprogress
at org.apache.hadoop.hdfs.DistributedFileSystem$29.doCall(DistributedFileSystem.java:1527)
at org.apache.hadoop.hdfs.DistributedFileSystem$29.doCall(DistributedFileSystem.java:1520)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1520)
at org.apache.spark.deploy.history.SingleFileEventLogFileReader.status$lzycompute(EventLogFileReaders.scala:170)
```
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
1. setup another script keeps changing the filename of applications under history log dir
2. launch the history server
3. check whether the `File does not exist` error log was gone.
Closes#29350 from yanxiaole/SPARK-32529.
Authored-by: Yan Xiaole <xiaole.yan@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This is a follow-up of #29278.
This PR changes the config name to switch allow/disallow `SparkContext` in executors as per the comment https://github.com/apache/spark/pull/29278#pullrequestreview-460256338.
### Why are the changes needed?
The config name `spark.executor.allowSparkContext` is more reasonable.
### Does this PR introduce _any_ user-facing change?
Yes, the config name is changed.
### How was this patch tested?
Updated tests.
Closes#29340 from ueshin/issues/SPARK-32160/change_config_name.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR modified the parser code to handle invalid usages of a SET/RESET command.
For example;
```
SET spark.sql.ansi.enabled true
```
The above SQL command does not change the configuration value and it just tries to display the value of the configuration
`spark.sql.ansi.enabled true`. This PR disallows using special characters including spaces in the configuration name and reports a user-friendly error instead. In the error message, it tells users a workaround to use quotes or a string literal if they still needs to specify a configuration with them.
Before this PR:
```
scala> sql("SET spark.sql.ansi.enabled true").show(1, -1)
+---------------------------+-----------+
|key |value |
+---------------------------+-----------+
|spark.sql.ansi.enabled true|<undefined>|
+---------------------------+-----------+
```
After this PR:
```
scala> sql("SET spark.sql.ansi.enabled true")
org.apache.spark.sql.catalyst.parser.ParseException:
Expected format is 'SET', 'SET key', or 'SET key=value'. If you want to include special characters in key, please use quotes, e.g., SET `ke y`=value.(line 1, pos 0)
== SQL ==
SET spark.sql.ansi.enabled true
^^^
```
### Why are the changes needed?
For better user-friendly errors.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Added tests in `SparkSqlParserSuite`.
Closes#29146 from maropu/SPARK-32257.
Lead-authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Co-authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
When https is enabled for Spark UI, an HTTP request will be redirected as an encoded HTTPS URL: https://github.com/apache/spark/pull/10238/files#diff-f79a5ead735b3d0b34b6b94486918e1cR312
When we create the redirect url, we will call getRequestURI and getQueryString. Both two methods may return an encoded string. However, we pass them directly to the following URI constructor
```
URI(String scheme, String authority, String path, String query, String fragment)
```
As this URI constructor assumes both path and query parameters are decoded strings, it will encode them again. This makes the redirect URL encoded twice.
This problem is on stage page with HTTPS enabled. The URL of "/taskTable" contains query parameter `order%5B0%5D%5Bcolumn%5D`. After encoded it becomes `order%255B0%255D%255Bcolumn%255D` and it will be decoded as `order%5B0%5D%5Bcolumn%5D` instead of `order[0][dir]`. When the parameter `order[0][dir]` is missing, there will be an excetpion from:
https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/status/api/v1/StagesResource.scala#L176
and the stage page fail to load.
To fix the problem, we can try decoding the query parameters before encoding it. This is to make sure we encode the URL
### Why are the changes needed?
Fix a UI issue when HTTPS is enabled
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
A new Unit test + manually test on a cluster
Closes#29271 from gengliangwang/urlEncode.
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?
Just few log lines fixes which are logging the object name instead of the stage IDs
### Why are the changes needed?
This would make it easier later for debugging.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Just log messages. Existing tests should be enough
Closes#29279 from venkata91/SPARK-31418-follow-up.
Authored-by: Venkata krishnan Sowrirajan <vsowrirajan@linkedin.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This is a follow-up of #28986.
This PR adds a config to switch allow/disallow to create `SparkContext` in executors.
- `spark.driver.allowSparkContextInExecutors`
### Why are the changes needed?
Some users or libraries actually create `SparkContext` in executors.
We shouldn't break their workloads.
### Does this PR introduce _any_ user-facing change?
Yes, users will be able to create `SparkContext` in executors with the config enabled.
### How was this patch tested?
More tests are added.
Closes#29278 from ueshin/issues/SPARK-32160/add_configs.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR removes a test added in SPARK-32175(#29002).
### Why are the changes needed?
That test is flaky. It can be mitigated by increasing the timeout but it would rather be simpler to remove the test.
See also the [discussion](https://github.com/apache/spark/pull/29002#issuecomment-666746857).
### Does this PR introduce _any_ user-facing change?
No.
Closes#29314 from sarutak/remove-flaky-test.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
This test tries to fix the flakyness of BlockManagerDecommissionIntegrationSuite.
### Description of the problem
Make the block manager decommissioning test be less flaky
An interesting failure happens when migrateDuring = true (and persist or shuffle is true):
- We schedule the job with tasks on executors 0, 1, 2.
- We wait 300 ms and decommission executor 0.
- If the task is not yet done on executor 0, it will now fail because
the block manager won't be able to save the block. This condition is
easy to trigger on a loaded machine where the github checks run.
- The task with retry on a different executor (1 or 2) and its shuffle
blocks will land there.
- No actual block migration happens here because the decommissioned
executor technically failed before it could even produce a block.
To remove the above race, this change replaces the fixed wait for 300 ms to wait for an actual task to succeed. When a task has succeeded, we know its blocks would have been written for sure and thus its executor would certainly be forced to migrate those blocks when it is decommissioned.
The change always decommissions an executor on which a real task finished successfully instead of picking the first executor. Because the system may choose to schedule nothing on the first executor and instead run the two tasks on one executor.
### Why are the changes needed?
I have had bad luck with BlockManagerDecommissionIntegrationSuite and it has failed several times on my PRs. So fixing it.
### Does this PR introduce _any_ user-facing change?
No, unit test only change.
### How was this patch tested?
Github checks. Ran this test 100 times, 10 at a time in parallel in a script.
Closes#29226 from agrawaldevesh/block-manager-decom-flaky.
Authored-by: Devesh Agrawal <devesh.agrawal@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR reduces the prospect of a job loss during decommissioning. It
fixes two holes in the current decommissioning framework:
- (a) Loss of decommissioned executors is not treated as a job failure:
We know that the decommissioned executor would be dying soon, so its death is
clearly not caused by the application.
- (b) Shuffle files on the decommissioned host are cleared when the
first fetch failure is detected from a decommissioned host: This is a
bit tricky in terms of when to clear the shuffle state ? Ideally you
want to clear it the millisecond before the shuffle service on the node
dies (or the executor dies when there is no external shuffle service) --
too soon and it could lead to some wastage and too late would lead to
fetch failures.
The approach here is to do this clearing when the very first fetch
failure is observed on the decommissioned block manager, without waiting for
other blocks to also signal a failure.
### Why are the changes needed?
Without them decommissioning a lot of executors at a time leads to job failures.
### Code overview
The task scheduler tracks the executors that were decommissioned along with their
`ExecutorDecommissionInfo`. This information is used by: (a) For handling a `ExecutorProcessLost` error, or (b) by the `DAGScheduler` when handling a fetch failure.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added a new unit test `DecommissionWorkerSuite` to test the new behavior by exercising the Master-Worker decommissioning. I chose to add a new test since the setup logic was quite different from the existing `WorkerDecommissionSuite`. I am open to changing the name of the newly added test suite :-)
### Questions for reviewers
- Should I add a feature flag to guard these two behaviors ? They seem safe to me that they should only get triggered by decommissioning, but you never know :-).
Closes#29014 from agrawaldevesh/decom_harden.
Authored-by: Devesh Agrawal <devesh.agrawal@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
So far, we fixed many stuffs in `core` module. This PR fixes the remaining UT failures in Scala 2.13.
- `OneApplicationResource.environmentInfo` will return a deterministic result for `sparkProperties`, `hadoopProperties`, `systemProperties`, and `classpathEntries`.
- `SubmitRestProtocolSuite` has Scala 2.13 answer in addition to the existing Scala 2.12 answer, and uses the expected answer based on the Scala runtime version.
### Why are the changes needed?
To support Scala 2.13.
### Does this PR introduce _any_ user-facing change?
Yes, `environmentInfo` is changed, but this fixes the indeterministic behavior.
### How was this patch tested?
- Scala 2.12: Pass the Jenkins or GitHub Action
- Scala 2.13: Do the following.
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13
```
**BEFORE**
```
Tests: succeeded 2612, failed 3, canceled 1, ignored 8, pending 0
*** 3 TESTS FAILED ***
```
**AFTER**
```
Tests: succeeded 2615, failed 0, canceled 1, ignored 8, pending 0
All tests passed.
```
Closes#29298 from dongjoon-hyun/SPARK-32489.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to remove `java.ws.rs.NotFoundException` from two problematic `import` statements. All the other use cases are correct.
### Why are the changes needed?
In `StagesResource` and `OneApplicationResource`, there exist two `NotFoundException`s.
- javax.ws.rs.NotFoundException
- org.apache.spark.status.api.v1.NotFoundException
To use `org.apache.spark.status.api.v1.NotFoundException` correctly, we should not import `java.ws.rs.NotFoundException`. This causes UT failures in Scala 2.13 environment.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
- Scala 2.12: Pass the GitHub Action or Jenkins.
- Scala 2.13: Do the following manually.
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.deploy.history.HistoryServerSuite
```
**BEFORE**
```
*** 4 TESTS FAILED ***
```
**AFTER**
```
*** 1 TEST FAILED ***
```
Closes#29293 from dongjoon-hyun/SPARK-32487.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to make `ResourceAllocator.availableAddrs` deterministic.
### Why are the changes needed?
Currently, this function returns indeterministically due to the underlying `HashMap`. So, the test case itself is creating a list `[0, 1, 2]` initially, but ends up with comparing `[2, 1, 0]`.
Not only this happens in the 3.0.0, but also this causes UT failures on Scala 2.13 environment.
### Does this PR introduce _any_ user-facing change?
Yes, but this fixes the in-deterministic behavior.
### How was this patch tested?
- Scala 2.12: This should pass the UT with the modified test case.
- Scala 2.13: This can be tested like the following (at least `JsonProtocolSuite`)
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.deploy.JsonProtocolSuite
```
**BEFORE**
```
*** 2 TESTS FAILED ***
```
**AFTER**
```
All tests passed.
```
Closes#29281 from dongjoon-hyun/SPARK-32476.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to make `JsonProtocol.accumulablesToJson` deterministic.
### Why are the changes needed?
Currently, `JsonProtocol.accumulablesToJson` is indeterministic. So, `JsonProtocolSuite` itself is also using mixed test cases in terms of `"Accumulables": [ ... ]`.
Not only this is indeterministic, but also this causes a UT failure in `JsonProtocolSuite` in Scala 2.13.
### Does this PR introduce _any_ user-facing change?
Yes. However, this is a fix on indeterministic behavior.
### How was this patch tested?
- Scala 2.12: Pass the GitHub Action or Jenkins.
- Scala 2.13: Do the following.
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.util.JsonProtocolSuite
```
**BEFORE**
```
*** 1 TEST FAILED ***
```
**AFTER**
```
All tests passed.
```
Closes#29282 from dongjoon-hyun/SPARK-32477.
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 changes the order between initialization for ExecutorPlugin and starting heartbeat thread in Executor.
### Why are the changes needed?
In the current master, heartbeat thread in a executor starts after plugin initialization so if the initialization takes long time, heartbeat is not sent to driver and the executor will be removed from cluster.
### Does this PR introduce _any_ user-facing change?
Yes. Plugins for executors will be allowed to take long time for initialization.
### How was this patch tested?
New testcase.
Closes#29002 from sarutak/fix-heartbeat-issue.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
`spark.kryo.registrator` in 3.0 has a regression problem. From [SPARK-12080](https://issues.apache.org/jira/browse/SPARK-12080), it supports multiple user registrators by
```scala
private val userRegistrators = conf.get("spark.kryo.registrator", "")
.split(',').map(_.trim)
.filter(!_.isEmpty)
```
But it donsn't work in 3.0. Fix it by `toSequence` in `Kryo.scala`
### Why are the changes needed?
In previous Spark version (2.x), it supported multiple user registrators by
```scala
private val userRegistrators = conf.get("spark.kryo.registrator", "")
.split(',').map(_.trim)
.filter(!_.isEmpty)
```
But it doesn't work in 3.0. It's should be a regression.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existed unit tests.
Closes#29123 from LantaoJin/SPARK-32283.
Authored-by: LantaoJin <jinlantao@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR aims to use `command -v` in non-Window operating systems instead of executing the given command.
### Why are the changes needed?
1. `command` is POSIX-compatible
- **POSIX.1-2017**: https://pubs.opengroup.org/onlinepubs/9699919799/utilities/command.html
2. `command` is faster and safer than the direct execution
- `command` doesn't invoke another process.
```scala
scala> sys.process.Process("ls").run().exitValue()
LICENSE
NOTICE
bin
doc
lib
man
res1: Int = 0
```
3. The existing way behaves inconsistently.
- `rm` cannot be checked.
**AS-IS**
```scala
scala> sys.process.Process("rm").run().exitValue()
usage: rm [-f | -i] [-dPRrvW] file ...
unlink file
res0: Int = 64
```
**TO-BE**
```
Welcome to Scala 2.13.3 (OpenJDK 64-Bit Server VM, Java 1.8.0_262).
Type in expressions for evaluation. Or try :help.
scala> sys.process.Process(Seq("sh", "-c", s"command -v ls")).run().exitValue()
/bin/ls
val res1: Int = 0
```
4. The existing logic is already broken in Scala 2.13 environment because it hangs like the following.
```scala
$ bin/scala
Welcome to Scala 2.13.3 (OpenJDK 64-Bit Server VM, Java 1.8.0_262).
Type in expressions for evaluation. Or try :help.
scala> sys.process.Process("cat").run().exitValue() // hang here.
```
### Does this PR introduce _any_ user-facing change?
No. Although this is inside `main` source directory, this is used for testing purpose.
```
$ git grep testCommandAvailable | grep -v 'def testCommandAvailable'
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(TestUtils.testCommandAvailable("cat"))
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(TestUtils.testCommandAvailable("wc"))
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(TestUtils.testCommandAvailable("cat"))
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(TestUtils.testCommandAvailable("cat"))
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(TestUtils.testCommandAvailable("cat"))
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(TestUtils.testCommandAvailable(envCommand))
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(!TestUtils.testCommandAvailable("some_nonexistent_command"))
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(TestUtils.testCommandAvailable("cat"))
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(TestUtils.testCommandAvailable("cat"))
core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala: assume(TestUtils.testCommandAvailable(envCommand))
sql/core/src/test/scala/org/apache/spark/sql/IntegratedUDFTestUtils.scala: private lazy val isPythonAvailable: Boolean = TestUtils.testCommandAvailable(pythonExec)
sql/core/src/test/scala/org/apache/spark/sql/IntegratedUDFTestUtils.scala: if (TestUtils.testCommandAvailable(pythonExec)) {
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala: skip = !TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala: skip = !TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala: skip = !TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala: skip = !TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala: skip = !TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala: skip = !TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala: skip = !TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala: skip = !TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveScriptTransformationSuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveScriptTransformationSuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveScriptTransformationSuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveScriptTransformationSuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveScriptTransformationSuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveScriptTransformationSuite.scala: assume(TestUtils.testCommandAvailable("python"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveScriptTransformationSuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveScriptTransformationSuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala: assume(TestUtils.testCommandAvailable("echo | sed"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala: assume(TestUtils.testCommandAvailable("/bin/bash"))
```
### How was this patch tested?
- **Scala 2.12**: Pass the Jenkins with the existing tests and one modified test.
- **Scala 2.13**: Do the following manually. It should pass instead of `hang`.
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.rdd.PipedRDDSuite
...
Tests: succeeded 12, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#29241 from dongjoon-hyun/SPARK-32443.
Lead-authored-by: HyukjinKwon <gurwls223@apache.org>
Co-authored-by: Dongjoon Hyun <dongjoon@apache.org>
Co-authored-by: Hyukjin Kwon <gurwls223@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Support set off heap memory in `ExecutorResourceRequests`
### Why are the changes needed?
Support stage level scheduling
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added UT in `ResourceProfileSuite` and `DAGSchedulerSuite`
Closes#28972 from warrenzhu25/30794.
Authored-by: Warren Zhu <zhonzh@microsoft.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
This PR aims to increase the memory parameter in `BlockManagerSuite`'s worker decommission test cases.
### Why are the changes needed?
Scala 2.13 generates different Java objects and this affects Spark's `SizeEstimator/SizeTracker/SizeTrackingVector`. This causes UT failures like the following. If we decrease the values, those test cases fails in Scala 2.12, too.
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.storage.BlockManagerSuite
...
- test decommission block manager should not be part of peers *** FAILED ***
0 did not equal 2 (BlockManagerSuite.scala:1869)
- test decommissionRddCacheBlocks should offload all cached blocks *** FAILED ***
0 did not equal 2 (BlockManagerSuite.scala:1884)
...
Tests: succeeded 81, failed 2, canceled 0, ignored 0, pending 0
*** 2 TESTS FAILED ***
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.storage.BlockManagerSuite
...
Tests: succeeded 83, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#29238 from dongjoon-hyun/SPARK-32440.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Since Scala 2.13, `HashMap` is changed to become a final in the future and `.withDefault` is recommended. This PR aims to use `HashMap.withDefaultValue` instead of overriding manually in the test case.
- https://www.scala-lang.org/api/current/scala/collection/mutable/HashMap.html
```scala
deprecatedInheritance(message =
"HashMap wil be made final; use .withDefault for the common use case of computing a default value",
since = "2.13.0")
```
### Why are the changes needed?
In Scala 2.13, the existing code causes a failure because the default value function doesn't work correctly.
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.rdd.RDDSuite
- aggregate *** FAILED ***
org.apache.spark.SparkException: Job aborted due to stage failure:
Task 0 in stage 61.0 failed 1 times, most recent failure: Lost task 0.0 in stage 61.0 (TID 198, localhost, executor driver):
java.util.NoSuchElementException: key not found: a
```
### Does this PR introduce _any_ user-facing change?
No. This is a test case change.
### How was this patch tested?
1. **Scala 2.12:** Pass the Jenkins or GitHub with the existing tests.
2. **Scala 2.13**: Manually do the following.
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.rdd.RDDSuite
...
Tests: succeeded 72, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#29235 from dongjoon-hyun/SPARK-32438.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to initialize `numNonEmptyBlocks` in `HighlyCompressedMapStatus.readExternal`.
In Scala 2.12, this is initialized to `-1` via the following.
```scala
protected def this() = this(null, -1, null, -1, null, -1) // For deserialization only
```
### Why are the changes needed?
In Scala 2.13, this causes several UT failures because `HighlyCompressedMapStatus.readExternal` doesn't initialize this field. The following is one example.
- org.apache.spark.scheduler.MapStatusSuite
```
MapStatusSuite:
- compressSize
- decompressSize
*** RUN ABORTED ***
java.lang.NoSuchFieldError: numNonEmptyBlocks
at org.apache.spark.scheduler.HighlyCompressedMapStatus.<init>(MapStatus.scala:181)
at org.apache.spark.scheduler.HighlyCompressedMapStatus$.apply(MapStatus.scala:281)
at org.apache.spark.scheduler.MapStatus$.apply(MapStatus.scala:73)
at org.apache.spark.scheduler.MapStatusSuite.$anonfun$new$8(MapStatusSuite.scala:64)
at scala.runtime.java8.JFunction1$mcVD$sp.apply(JFunction1$mcVD$sp.scala:18)
at scala.collection.immutable.List.foreach(List.scala:333)
at org.apache.spark.scheduler.MapStatusSuite.$anonfun$new$7(MapStatusSuite.scala:61)
at scala.runtime.java8.JFunction1$mcVJ$sp.apply(JFunction1$mcVJ$sp.scala:18)
at scala.collection.immutable.List.foreach(List.scala:333)
at org.apache.spark.scheduler.MapStatusSuite.$anonfun$new$6(MapStatusSuite.scala:60)
...
```
### Does this PR introduce _any_ user-facing change?
No. This is a private class.
### How was this patch tested?
1. Pass the GitHub Action or Jenkins with the existing tests.
2. Test with Scala-2.13 with `MapStatusSuite`.
```
$ dev/change-scala-version.sh 2.13
$ build/mvn test -pl core --am -Pscala-2.13 -Dtest=none -DwildcardSuites=org.apache.spark.scheduler.MapStatusSuite
...
MapStatusSuite:
- compressSize
- decompressSize
- MapStatus should never report non-empty blocks' sizes as 0
- large tasks should use org.apache.spark.scheduler.HighlyCompressedMapStatus
- HighlyCompressedMapStatus: estimated size should be the average non-empty block size
- SPARK-22540: ensure HighlyCompressedMapStatus calculates correct avgSize
- RoaringBitmap: runOptimize succeeded
- RoaringBitmap: runOptimize failed
- Blocks which are bigger than SHUFFLE_ACCURATE_BLOCK_THRESHOLD should not be underestimated.
- SPARK-21133 HighlyCompressedMapStatus#writeExternal throws NPE
Run completed in 7 seconds, 971 milliseconds.
Total number of tests run: 10
Suites: completed 2, aborted 0
Tests: succeeded 10, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#29231 from dongjoon-hyun/SPARK-32436.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to speed up `MapStatus` deserialization by 5~18% with the latest RoaringBitmap `0.9.0` and new APIs. Note that we focus on `deserialization` time because `serialization` occurs once while `deserialization` occurs many times.
### Why are the changes needed?
The current version is too old. We had better upgrade it to get the performance improvement and bug fixes.
Although `MapStatusesSerDeserBenchmark` is synthetic, the benchmark result is updated with this patch.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the Jenkins or GitHub Action.
Closes#29233 from dongjoon-hyun/SPARK-ROAR.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
`UninterruptibleThread` running functionality is baked into `KafkaOffsetReader` which can be extracted into a class. The main intention is to simplify `KafkaOffsetReader` in order to make easier to solve SPARK-32032. In this PR I've made this extraction without functionality change.
### Why are the changes needed?
`UninterruptibleThread` running functionality is baked into `KafkaOffsetReader`.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing + additional unit tests.
Closes#29187 from gaborgsomogyi/SPARK-32387.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
I wasn't able to reproduce the failure but the best I can tell is that the allocation manager timer triggers and call doRequest. The timeout is 10s so try to increase that to 30seconds.
### Why are the changes needed?
test failure
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
unit test
Closes#29225 from tgravescs/SPARK-32287.
Authored-by: Thomas Graves <tgraves@nvidia.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### 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?
In this change, when dynamic allocation is enabled instead of aborting immediately when there is an unschedulable taskset due to blacklisting, pass an event saying `SparkListenerUnschedulableTaskSetAdded` which will be handled by `ExecutorAllocationManager` and request more executors needed to schedule the unschedulable blacklisted tasks. Once the event is sent, we start the abortTimer similar to [SPARK-22148][SPARK-15815] to abort in the case when no new executors launched either due to max executors reached or cluster manager is out of capacity.
### Why are the changes needed?
This is an improvement. In the case when dynamic allocation is enabled, this would request more executors to schedule the unschedulable tasks instead of aborting the stage without even retrying upto spark.task.maxFailures times (in some cases not retrying at all). This is a potential issue with respect to Spark's Fault tolerance.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Added unit tests both in ExecutorAllocationManagerSuite and TaskSchedulerImplSuite
Closes#28287 from venkata91/SPARK-31418.
Authored-by: Venkata krishnan Sowrirajan <vsowrirajan@linkedin.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
This PR is a giant plumbing PR that plumbs an `ExecutorDecommissionInfo` along
with the DecommissionExecutor message.
### Why are the changes needed?
The primary motivation is to know whether a decommissioned executor
would also be loosing shuffle files -- and thus it is important to know
whether the host would also be decommissioned.
In the absence of this PR, the existing code assumes that decommissioning an executor does not loose the whole host with it, and thus does not clear the shuffle state if external shuffle service is enabled. While this may hold in some cases (like K8s decommissioning an executor pod, or YARN container preemption), it does not hold in others like when the cluster is managed by a Standalone Scheduler (Master). This is similar to the existing `workerLost` field in the `ExecutorProcessLost` message.
In the future, this `ExecutorDecommissionInfo` can be embellished for
knowing how long the executor has to live for scenarios like Cloud spot
kills (or Yarn preemption) and the like.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Tweaked an existing unit test in `AppClientSuite`
Closes#29032 from agrawaldevesh/plumb_decom_info.
Authored-by: Devesh Agrawal <devesh.agrawal@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
If an executor is lost, the `DAGScheduler` handles the executor loss by removing the executor but does not unregister its outputs if the external shuffle service is used. However, if the node on which the executor runs is lost, the shuffle service may not be able to serve the shuffle files.
In such a case, when fetches from the executor's outputs fail in the same stage, the `DAGScheduler` again removes the executor and by right, should unregister its outputs. It doesn't because the epoch used to track the executor failure has not increased.
We track the epoch for failed executors that result in lost file output separately, so we can unregister the outputs in this scenario. The idea to track a second epoch is due to Attila Zsolt Piros.
### Why are the changes needed?
Without the changes, the loss of a node could require two stage attempts to recover instead of one.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
New unit test. This test fails without the change and passes with it.
Closes#28848 from wypoon/SPARK-32003.
Authored-by: Wing Yew Poon <wypoon@cloudera.com>
Signed-off-by: Imran Rashid <irashid@cloudera.com>
### What changes were proposed in this pull request?
In PR, I propose to create input tables once before executing tests in `JDBCSuite` and `JdbcRDDSuite`. Currently, the table are created before every test in the test suites.
### Why are the changes needed?
This speed up the test suites up 30-40%.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Run the modified test suites
Closes#29176 from MaxGekk/jdbc-suite-before-all.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Catch the `RpcEnvStoppedException` and log debug it when stop is called for a `LocalSparkCluster`.
This PR also contains two small changes to fix the potential issues.
### Why are the changes needed?
Currently, there's always "RpcEnv already stopped" error if we exit spark-shell with local-cluster mode:
```
20/06/07 14:54:18 ERROR TransportRequestHandler: Error while invoking RpcHandler#receive() for one-way message.
org.apache.spark.rpc.RpcEnvStoppedException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:167)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:150)
at org.apache.spark.rpc.netty.NettyRpcHandler.receive(NettyRpcEnv.scala:691)
at org.apache.spark.network.server.TransportRequestHandler.processOneWayMessage(TransportRequestHandler.java:253)
at org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:111)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:140)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:53)
at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:99)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:379)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:365)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:357)
at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:286)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:379)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:365)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:357)
at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:379)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:365)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:357)
at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:102)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:379)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:365)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:357)
at io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1410)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:379)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:365)
at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:919)
at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:163)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:714)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:650)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:576)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:493)
at io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989)
at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
at java.lang.Thread.run(Thread.java:748)
```
When we call stop on `StandaloneSchedulerBackend`, the backend will firstly send `UnregisterApplication` to `Master` and then call stop on `LocalSparkCluster` immediately. On the other side, `Master` will send messages to `Worker` when it receives `UnregisterApplication`. However, the rpcEnv of the `Worker` has been already stoped by the backend. Therefore, the error message shows when the `Worker` tries to handle the messages.
It's only an error on shutdown, users would not like to care about it. So we could hide it in debug log and this is also what we've done previously in #18547.
### Does this PR introduce _any_ user-facing change?
Yes, users will not see the error message after this PR.
### How was this patch tested?
Tested manually.
Closes#28746 from Ngone51/fix-spark-31922.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
The idea is to improve the performance of HybridStore by adding batch write support to LevelDB. #28412 introduces HybridStore. HybridStore will write data to InMemoryStore at first and use a background thread to dump data to LevelDB once the writing to InMemoryStore is completed. In the comments section of #28412 , mridulm mentioned using batch writing can improve the performance of this dumping process and he wrote the code of writeAll().
### Why are the changes needed?
I did the comparison of the HybridStore switching time between one-by-one write and batch write on an HDD disk. When the disk is free, the batch-write has around 25% improvement, and when the disk is 100% busy, the batch-write has 7x - 10x improvement.
when the disk is at 0% utilization:
| log size, jobs and tasks per job | original switching time, with write() | switching time with writeAll() |
| ---------------------------------- | ------------------------------------- | ------------------------------ |
| 133m, 400 jobs, 100 tasks per job | 16s | 13s |
| 265m, 400 jobs, 200 tasks per job | 30s | 23s |
| 1.3g, 1000 jobs, 400 tasks per job | 136s | 108s |
when the disk is at 100% utilization:
| log size, jobs and tasks per job | original switching time, with write() | switching time with writeAll() |
| --------------------------------- | ------------------------------------- | ------------------------------ |
| 133m, 400 jobs, 100 tasks per job | 116s | 17s |
| 265m, 400 jobs, 200 tasks per job | 251s | 26s |
I also ran some write related benchmarking tests on LevelDBBenchmark.java and measured the total time of writing 1024 objects. The tests were conducted when the disk is at 0% utilization.
| Benchmark test | with write(), ms | with writeAll(), ms |
| ------------------------ | ---------------- | ------------------- |
| randomUpdatesIndexed | 213.06 | 157.356 |
| randomUpdatesNoIndex | 57.869 | 35.439 |
| randomWritesIndexed | 298.854 | 229.274 |
| randomWritesNoIndex | 66.764 | 38.361 |
| sequentialUpdatesIndexed | 87.019 | 56.219 |
| sequentialUpdatesNoIndex | 61.851 | 41.942 |
| sequentialWritesIndexed | 94.044 | 56.534 |
| sequentialWritesNoIndex | 118.345 | 66.483 |
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manually tested.
Closes#29149 from baohe-zhang/SPARK-32350.
Authored-by: Baohe Zhang <baohe.zhang@verizonmedia.com>
Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
### What is changed?
This pull request adds the ability to migrate shuffle files during Spark's decommissioning. The design document associated with this change is at https://docs.google.com/document/d/1xVO1b6KAwdUhjEJBolVPl9C6sLj7oOveErwDSYdT-pE .
To allow this change the `MapOutputTracker` has been extended to allow the location of shuffle files to be updated with `updateMapOutput`. When a shuffle block is put, a block update message will be sent which triggers the `updateMapOutput`.
Instead of rejecting remote puts of shuffle blocks `BlockManager` delegates the storage of shuffle blocks to it's shufflemanager's resolver (if supported). A new, experimental, trait is added for shuffle resolvers to indicate they handle remote putting of blocks.
The existing block migration code is moved out into a separate file, and a producer/consumer model is introduced for migrating shuffle files from the host as quickly as possible while not overwhelming other executors.
### Why are the changes needed?
Recomputting shuffle blocks can be expensive, we should take advantage of our decommissioning time to migrate these blocks.
### Does this PR introduce any user-facing change?
This PR introduces two new configs parameters, `spark.storage.decommission.shuffleBlocks.enabled` & `spark.storage.decommission.rddBlocks.enabled` that control which blocks should be migrated during storage decommissioning.
### How was this patch tested?
New unit test & expansion of the Spark on K8s decom test to assert that decommisioning with shuffle block migration means that the results are not recomputed even when the original executor is terminated.
This PR is a cleaned-up version of the previous WIP PR I made https://github.com/apache/spark/pull/28331 (thanks to attilapiros for his very helpful reviewing on it :)).
Closes#28708 from holdenk/SPARK-20629-copy-shuffle-data-when-nodes-are-being-shutdown-cleaned-up.
Lead-authored-by: Holden Karau <hkarau@apple.com>
Co-authored-by: Holden Karau <holden@pigscanfly.ca>
Co-authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Co-authored-by: Attila Zsolt Piros <attilazsoltpiros@apiros-mbp16.lan>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR adds functionality to consider the running tasks on decommission executors based on some config.
In spark-on-cloud , we sometimes already know that an executor won't be alive for more than fix amount of time. Ex- In AWS Spot nodes, once we get the notification, we know that a node will be gone in 120 seconds.
So if the running tasks on the decommissioning executors may run beyond currentTime+120 seconds, then they are candidate for speculation.
### Why are the changes needed?
Currently when an executor is decommission, we stop scheduling new tasks on those executors but the already running tasks keeps on running on them. Based on the cloud, we might know beforehand that an executor won't be alive for more than a preconfigured time. Different cloud providers gives different timeouts before they take away the nodes. For Ex- In case of AWS spot nodes, an executor won't be alive for more than 120 seconds. We can utilize this information in cloud environments and take better decisions about speculating the already running tasks on decommission executors.
### Does this PR introduce _any_ user-facing change?
Yes. This PR adds a new config "spark.executor.decommission.killInterval" which they can explicitly set based on the cloud environment where they are running.
### How was this patch tested?
Added UT.
Closes#28619 from prakharjain09/SPARK-21040-speculate-decommission-exec-tasks.
Authored-by: Prakhar Jain <prakharjain09@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR allows an external agent to inform the Master that certain hosts
are being decommissioned.
### Why are the changes needed?
The current decommissioning is triggered by the Worker getting getting a SIGPWR
(out of band possibly by some cleanup hook), which then informs the Master
about it. This approach may not be feasible in some environments that cannot
trigger a clean up hook on the Worker. In addition, when a large number of
worker nodes are being decommissioned then the master will get a flood of
messages.
So we add a new post endpoint `/workers/kill` on the MasterWebUI that allows an
external agent to inform the master about all the nodes being decommissioned in
bulk. The list of nodes is specified by providing a list of hostnames. All workers on those
hosts will be decommissioned.
This API is merely a new entry point into the existing decommissioning
logic. It does not change how the decommissioning request is handled in
its core.
### Does this PR introduce _any_ user-facing change?
Yes, a new endpoint `/workers/kill` is added to the MasterWebUI. By default only
requests originating from an IP address local to the MasterWebUI are allowed.
### How was this patch tested?
Added unit tests
Closes#29015 from agrawaldevesh/master_decom_endpoint.
Authored-by: Devesh Agrawal <devesh.agrawal@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Support fetching taskList by status as below:
```
/applications/[app-id]/stages/[stage-id]/[stage-attempt-id]/taskList?status=failed
```
### Why are the changes needed?
When there're large number of tasks in one stage, current api is hard to get taskList by status
### Does this PR introduce _any_ user-facing change?
Yes. Updated monitoring doc.
### How was this patch tested?
Added tests in `HistoryServerSuite`
Closes#28942 from warrenzhu25/SPARK-32125.
Authored-by: Warren Zhu <zhonzh@microsoft.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### 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?
Add a new class HybridStore to make the history server faster when loading event files. When rebuilding the application state from event logs, HybridStore will write data to InMemoryStore at first and use a background thread to dump data to LevelDB once the writing to InMemoryStore is completed. HybridStore is to make content serving faster by using more memory. It's only safe to enable it when the cluster is not having a heavy load.
### Why are the changes needed?
HybridStore can greatly reduce the event logs loading time, especially for large log files. In general, it has 4x - 6x UI loading speed improvement for large log files. The detailed result is shown in comments.
### Does this PR introduce any user-facing change?
This PR adds new configs `spark.history.store.hybridStore.enabled` and `spark.history.store.hybridStore.maxMemoryUsage`.
### How was this patch tested?
A test suite for HybridStore is added. I also manually tested it on 3.1.0 on mac os.
This is a follow-up for the work done by Hieu Huynh in 2019.
Closes#28412 from baohe-zhang/SPARK-31608.
Authored-by: Baohe Zhang <baohe.zhang@verizonmedia.com>
Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
### 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 change replaces the world slave with alternatives matching the context.
### Why are the changes needed?
There is no need to call things slave, we might as well use better clearer names.
### Does this PR introduce _any_ user-facing change?
Yes, the ouput JSON does change. To allow backwards compatibility this is an additive change.
The shell scripts for starting & stopping workers are renamed, and for backwards compatibility old scripts are added to call through to the new ones while printing a deprecation message to stderr.
### How was this patch tested?
Existing tests.
Closes#28864 from holdenk/SPARK-32004-drop-references-to-slave.
Lead-authored-by: Holden Karau <hkarau@apple.com>
Co-authored-by: Holden Karau <holden@pigscanfly.ca>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
When last partition's splitFile's split size is larger then maxSize, this partition will be lost
Origin logic error like below as 1, 2, 3, 4, 5
```scala
// 5. since index = partition.size now, jump out of the loop , then the last partition is lost since we won't call updatePartition() again.
while (index < partitions.size) {
// 1. we assume that when index = partitions.length -1(the last partition)
val partition = partitions(index)
val fileSplit =
partition.asInstanceOf[HadoopPartition].inputSplit.value.asInstanceOf[FileSplit]
val splitSize = fileSplit.getLength
// 2. if this partition's splitSize > maxSize
if (currentSum + splitSize < maxSize) {
addPartition(partition, splitSize)
index += 1
if (index == partitions.size) {
updateGroups
}
} else {
// 3. if currentGroup.partitions.size >0, this situation is possiable
if (currentGroup.partitions.size == 0) {
addPartition(partition, splitSize)
index += 1
} else {
// 4. then will just call updateGroups() here first, and index won't update in group
updateGroups
}
}
}
groups.toArray
}
}
```
### Why are the changes needed?
Fix bug
### Does this PR introduce any user-facing change?
NO
### How was this patch tested?
Manual code review.
Closes#27988 from AngersZhuuuu/SPARK-31226.
Authored-by: angerszhu <angers.zhu@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
The purpose of this PR is to partly resolve SPARK-29292, and fully resolve SPARK-30010, which should allow Spark to compile vs Scala 2.13 in Spark Core and up through GraphX (not SQL, Streaming, etc).
Note that we are not trying to determine here whether this makes Spark work on 2.13 yet, just compile, as a prerequisite for assessing test outcomes. However, of course, we need to ensure that the change does not break 2.12.
The changes are, in the main, adding .toSeq and .toMap calls where mutable collections / maps are returned as Seq / Map, which are immutable by default in Scala 2.13. The theory is that it should be a no-op for Scala 2.12 (these return themselves), and required for 2.13.
There are a few non-trivial changes highlighted below.
In particular, to get Core to compile, we need to resolve SPARK-30010 which removes a deprecated SparkConf method
### Why are the changes needed?
Eventually, we need to support a Scala 2.13 build, perhaps in Spark 3.1.
### Does this PR introduce _any_ user-facing change?
Yes, removal of the deprecated SparkConf.setAll overload, which isn't legal in Scala 2.13 anymore.
### How was this patch tested?
Existing tests. (2.13 was not _tested_; this is about getting it to compile without breaking 2.12)
Closes#28971 from srowen/SPARK-29292.1.
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 to change the HistoryServer to redirect to the history page when we access to /history without application id.
### Why are the changes needed?
In the current master, status code 400 will be returned when we access to /history.
So I wonder it's better to redirect to the history page for the better UX.
### Does this PR introduce _any_ user-facing change?
Yes. In the current master, if we access to /history without application id, we will see like the following page.
After this change applied, we will be redirected to the history page.
### How was this patch tested?
New test added.
Closes#29016 from sarutak/history-redirect.
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 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?
In IPv6 scenario, the current logic to split hostname and port is not correct.
### Why are the changes needed?
to support IPV6 deployment scenario
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
UT and IPV6 spark deployment with yarn
Closes#28931 from PavithraRamachandran/ipv6_issue.
Authored-by: Pavithraramachandran <pavi.rams@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR adds the check to see whether the executor is lost (by asking the `CoarseGrainedSchedulerBackend`) after timeout error raised in `BlockManagerMasterEndponit` due to removing blocks(e.g. RDD, broadcast, shuffle). If the executor is lost, we will ignore the error. Otherwise, throw the error.
### Why are the changes needed?
When removing blocks(e.g. RDD, broadcast, shuffle), `BlockManagerMaserEndpoint` will make RPC calls to each known `BlockManagerSlaveEndpoint` to remove the specific blocks. The PRC call sometimes could end in a timeout when the executor has been lost, but only notified the `BlockManagerMasterEndpoint` after the removing call has already happened. The timeout error could therefore fail the whole job.
In this case, we actually could just ignore the error since those blocks on the lost executor could be considered as removed already.
### Does this PR introduce _any_ user-facing change?
Yes. In case of users hits this issue, they will have the job executed successfully instead of throwing the exception.
### How was this patch tested?
Added unit tests.
Closes#28924 from Ngone51/ignore-timeout-error-for-inactive-executor.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR proposes to disallow to create `SparkContext` in executors, e.g., in UDFs.
### Why are the changes needed?
Currently executors can create SparkContext, but shouldn't be able to create it.
```scala
sc.range(0, 1).foreach { _ =>
new SparkContext(new SparkConf().setAppName("test").setMaster("local"))
}
```
### Does this PR introduce _any_ user-facing change?
Yes, users won't be able to create `SparkContext` in executors.
### How was this patch tested?
Addes tests.
Closes#28986 from ueshin/issues/SPARK-32160/disallow_spark_context_in_executors.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This patch fixes the test failure due to the missing when statements for destination path. Note that it didn't fail on master branch, because 245aee9 got rid of size call in destination path, but still good to not depend on 245aee9.
### Why are the changes needed?
The build against branch-3.0 / branch-2.4 starts to fail after merging SPARK-32024 (#28859) and this patch will fix it.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Ran modified UT against master / branch-3.0 / branch-2.4.
Closes#29046 from HeartSaVioR/QUICKFIX-SPARK-32024.
Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Enable test("static relative links are prefixed with uiRoot (spark.ui.proxyBase)")
### Why are the changes needed?
In Jira, the failed test is another one test("ajax rendered relative links are prefixed with uiRoot (spark.ui.proxyBase)"). This test has been fixed in 6a895d0
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Fix UT
Closes#28970 from warrenzhu25/31723.
Authored-by: Warren Zhu <zhonzh@microsoft.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Update ApplicationStoreInfo.size to real size during HistoryServerDiskManager initializing.
### Why are the changes needed?
This PR is for fixing bug [32024](https://issues.apache.org/jira/browse/SPARK-32024). We found after history server restart, below error would randomly happen: "java.lang.IllegalStateException: Disk usage tracker went negative (now = -***, delta = -***)" from `HistoryServerDiskManager`.
**Cause**: Reading data from level db would trigger table file compaction, which may also trigger size of level db directory changes. This size change may not be recorded in LevelDB (`ApplicationStoreInfo` in `listing`). When service restarts, `currentUsage` is calculated from real directory size, but `ApplicationStoreInfo` are loaded from leveldb, then `currentUsage` may be less then sum of `ApplicationStoreInfo.size`. In `makeRoom()` function, `ApplicationStoreInfo.size` is used to update usage. Then `currentUsage` becomes negative after several round of `release()` and `lease()` (`makeRoom()`).
**Reproduce**: we can reproduce this issue in dev environment by reducing config value of "spark.history.retainedApplications" and "spark.history.store.maxDiskUsage" to some small values. Here are steps: 1. start history server, load some applications and access some pages (maybe "stages" page to trigger leveldb compaction). 2. restart HS, and refresh pages.
I also added an UT to simulate this case in `HistoryServerDiskManagerSuite`.
**Benefit**: this change would help improve history server reliability.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Add unit test and manually tested it.
Closes#28859 from zhli1142015/update-ApplicationStoreInfo.size-during-disk-manager-initialize.
Authored-by: Zhen Li <zhli@microsoft.com>
Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
### What changes were proposed in this pull request?
Use the invalid value Int.MinValue to fill the map index when the event logs from the old Spark version.
### Why are the changes needed?
Follow up PR for #28941.
### Does this PR introduce _any_ user-facing change?
When we use the Spark version 3.0 history server reading the event log written by the old Spark version, we use the invalid value -2 to fill the map index.
### How was this patch tested?
Existing UT.
Closes#28965 from xuanyuanking/follow-up.
Authored-by: Yuanjian Li <xyliyuanjian@gmail.com>
Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
### What changes were proposed in this pull request?
Use Files.createDirectory() to create local directory instead of File.mkdir() in DiskBlockManager.
Many times, we will see such error log information like "Failed to create local dir in xxxxxx". But there is no clear information indicating why the directory creation failed.
When Files.createDirectory() fails to create a local directory, it can give specific error information for subsequent troubleshooting(also throws IOException).
### Why are the changes needed?
Throw clear error message when creating directory fails.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
`DiskBlockManagerSuite`
Closes#28997 from sidedoorleftroad/SPARK-32172.
Authored-by: sidedoorleftroad <sidedoorleftroad@163.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to reduce the required test resources in WorkerDecommissionExtendedSuite.
### Why are the changes needed?
When Jenkins farms is crowded, the following failure happens currently [here](https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-sbt-hadoop-3.2-hive-2.3/890/testReport/junit/org.apache.spark.scheduler/WorkerDecommissionExtendedSuite/Worker_decommission_and_executor_idle_timeout/)
```
java.util.concurrent.TimeoutException: Can't find 20 executors before 60000 milliseconds elapsed
at org.apache.spark.TestUtils$.waitUntilExecutorsUp(TestUtils.scala:326)
at org.apache.spark.scheduler.WorkerDecommissionExtendedSuite.$anonfun$new$2(WorkerDecommissionExtendedSuite.scala:45)
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the Jenkins.
Closes#29001 from dongjoon-hyun/SPARK-32100-2.
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 changes `webui.css` to fix a style issue on moving mouse cursor on the Spark logo.
### Why are the changes needed?
In the webui, the Spark logo is on the top right side.
When we move mouse cursor on the logo, a weird underline appears near the logo.
<img width="209" alt="logo_with_line" src="https://user-images.githubusercontent.com/4736016/86542828-3c6a9f00-bf54-11ea-9b9d-cc50c12c2c9b.png">
### Does this PR introduce _any_ user-facing change?
Yes. After this change applied, no more weird line shown even if mouse cursor moves on the logo.
<img width="207" alt="removed-line-from-logo" src="https://user-images.githubusercontent.com/4736016/86542877-98cdbe80-bf54-11ea-8695-ee39689673ab.png">
### How was this patch tested?
By moving mouse cursor on the Spark logo and confirmed no more weird line there.
Closes#29003 from sarutak/fix-logo-underline.
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 PR aims to add `PrometheusServletSuite`.
### Why are the changes needed?
This improves the test coverage.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the newly added test suite.
Closes#28865 from erenavsarogullari/spark_driver_prometheus_metrics_improvement.
Authored-by: Eren Avsarogullari <erenavsarogullari@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
`formatDate` in utils.js `org/apache/spark/ui/static/utils.js` is partly refactored.
### Why are the changes needed?
In branch-2.4，task launch time is returned as html string from driver,
while in branch-3.x，this is returned in JSON Object as`Date`type from `org.apache.spark.status.api.v1.TaskData`
Due to：
LaunchTime from jersey server in spark driver is correct, which will be converted to date string like `2020-06-28T02:57:42.605GMT` in json object, then the formatDate in utils.js treat it as date.split(".")[0].replace("T", " ").
So `2020-06-28T02:57:42.605GMT` will be converted to `2020-06-28 02:57:42`, but correct is `2020-06-28 10:57:42` in GMT+8 timezone.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manual test.
Closes#28918 from TJX2014/master-SPARK-32068-ui-task-lauch-time-tz.
Authored-by: TJX2014 <xiaoxingstack@gmail.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
This PR tries to unify the method `getReader` and `getReaderForRange` in `ShuffleManager`.
### Why are the changes needed?
Reduce the duplicate codes, simplify the implementation, and for better maintenance.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Covered by existing tests.
Closes#28895 from Ngone51/unify-getreader.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Fix bug of exception when parse event log of fetch failed task end reason without `Map Index`
### Why are the changes needed?
When Spark history server read event log produced by older version of spark 2.4 (which don't have `Map Index` field), parsing of TaskEndReason will fail. This will cause TaskEnd event being ignored.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
JsonProtocolSuite.test("FetchFailed Map Index backwards compatibility")
Closes#28941 from warrenzhu25/shs-task.
Authored-by: Warren Zhu <zhonzh@microsoft.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
**First**
`DAGSchedulerSuite` provides `completeNextStageWithFetchFailure` to make all tasks in non first stage occur `FetchFailed`.
But many test case uses complete directly as follows:
```scala
complete(taskSets(1), Seq(
(FetchFailed(makeBlockManagerId("hostA"),
shuffleDep1.shuffleId, 0L, 0, 0, "ignored"), null)))
```
We need to reuse `completeNextStageWithFetchFailure`.
**Second**
`DAGSchedulerSuite` also check the results show below:
```scala
complete(taskSets(0), Seq((Success, 42)))
assert(results === Map(0 -> 42))
```
We can extract it as a generic method of `checkAnswer`.
### Why are the changes needed?
Reuse `completeNextStageWithFetchFailure`
### Does this PR introduce _any_ user-facing change?
'No'.
### How was this patch tested?
Jenkins test
Closes#28866 from beliefer/reuse-completeNextStageWithFetchFailure.
Authored-by: gengjiaan <gengjiaan@360.cn>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to add `WorkerDecomissionExtendedSuite` for various worker decommission combinations.
### Why are the changes needed?
This will improve the test coverage.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the Jenkins.
Closes#28929 from dongjoon-hyun/SPARK-WD-TEST.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Fix app id link for multi attempts application in history summary page
If attempt id is available (yarn), app id link url will contain correct attempt id, like `/history/application_1561589317410_0002/1/jobs/`.
If attempt id is not available (standalone), app id link url will not contain fake attempt id, like `/history/app-20190404053606-0000/jobs/`.
### Why are the changes needed?
This PR is for fixing [32028](https://issues.apache.org/jira/browse/SPARK-32028). App id link use application attempt count as attempt id. this would cause link url wrong for below cases:
1. there are multi attempts, all links point to last attempt
2. if there is one attempt, but attempt id is not 1 (before attempt maybe crash or fail to gerenerate event file). link url points to worng attempt (1) here.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Tested this manually.
Closes#28867 from zhli1142015/fix-appid-link-in-history-page.
Authored-by: Zhen Li <zhli@microsoft.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
Introduces the concept of a `MapOutputMetadata` opaque object that can be returned from map output writers.
Note that this PR only proposes the API changes on the shuffle writer side. Following patches will be proposed for actually accepting the metadata on the driver and persisting it in the driver's shuffle metadata storage plugin.
### Why are the changes needed?
For a more complete design discussion on this subject as a whole, refer to [this design document](https://docs.google.com/document/d/1Aj6IyMsbS2sdIfHxLvIbHUNjHIWHTabfknIPoxOrTjk/edit#).
### Does this PR introduce any user-facing change?
Enables additional APIs for the shuffle storage plugin tree. Usage will become more apparent as the API evolves.
### How was this patch tested?
No tests here, since this is only an API-side change that is not consumed by core Spark itself.
Closes#28616 from mccheah/return-map-output-metadata.
Authored-by: mcheah <mcheah@palantir.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR changes the test to get an active executorId and set it as preferred location instead of setting a fixed preferred location.
### Why are the changes needed?
The test is flaky. After checking the [log](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/124086/artifact/core/), I find the root cause is:
Two test cases from different test suites got submitted at the same time because of concurrent execution. In this particular case, the two test cases (from DistributedSuite and BarrierTaskContextSuite) both launch under local-cluster mode. The two applications are submitted at the SAME time so they have the same applications(app-20200615210132-0000). Thus, when the cluster of BarrierTaskContextSuite is launching executors, it failed to create the directory for the executor 0, because the path (/home/jenkins/workspace/work/app-app-20200615210132-0000/0) has been used by the cluster of DistributedSuite. Therefore, it has to launch executor 1 and 2 instead, that lead to non of the tasks can get preferred locality thus they got scheduled together and lead to the test failure.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
The test can not be reproduced locally. We can only know it's been fixed when it's no longer flaky on Jenkins.
Closes#28849 from Ngone51/fix-spark-32000.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This aims to replace `executorIdsToBeRemoved` with `executorIdToBeRemoved`.
### Why are the changes needed?
Since a wrong variable is used currently, `ArrayBuffer()` is always displayed.
```
20/06/16 19:33:31 WARN ExecutorAllocationManager: Not removing executor ArrayBuffer() because the ResourceProfile was UNKNOWN!
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manual.
Closes#28847 from dongjoon-hyun/SPARK-29148.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Close LevelDBIterator when LevelDB.close() is called.
### Why are the changes needed?
This pull request would prevent JNI resources leaking from Level DB instance and its' iterators. In before implementation JNI resources from LevelDBIterator are cleaned by finalize() function. This behavior is also mentioned in comments of ["LevelDBIterator.java"](https://github.com/apache/spark/blob/master/common/kvstore/src/main/java/org/apache/spark/util/kvstore/LevelDBIterator.java) by squito . But if DB instance is already closed, then iterator's close method would be ignored. LevelDB's iterator would keep level db files opened (for the case table cache is filled up), till iterator.close() is called. Then these JNI resources (file handle) would be leaked.
This JNI resource leaking issue would cause the problem described in [SPARK-31929](https://issues.apache.org/jira/browse/SPARK-31929) on Windows: in spark history server, leaked file handle for level db files would trigger "IOException" when HistoryServerDiskManager try to remove them for releasing disk space.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Add unit test and manually tested it.
Closes#28769 from zhli1142015/close-leveldbiterator-when-leveldb.close.
Authored-by: Zhen Li <zhli@microsoft.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
`DAGSchedulerSuite `provides `completeShuffleMapStageSuccessfully `to make `ShuffleMapStage `successfully.
But many test case uses complete directly as follows:
`complete(taskSets(0), Seq((Success, makeMapStatus("hostA", 1))))`
We need to improve `completeShuffleMapStageSuccessfully `and reuse it.
`completeShuffleMapStageSuccessfully(0, 0, 1, Some(0), Seq("hostA"))`
### Why are the changes needed?
Improve and reuse completeShuffleMapStageSuccessfully
### Does this PR introduce _any_ user-facing change?
'No'.
### How was this patch tested?
Jenkins test
Closes#28641 from beliefer/improve-and-reuse-method.
Authored-by: gengjiaan <gengjiaan@360.cn>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
This PR proposes to use "mdc.XXX" as the consistent key for both `sc.setLocalProperty` and `log4j.properties` when setting up configurations for MDC.
### Why are the changes needed?
It's weird that we use "mdc.XXX" as key to set MDC value via `sc.setLocalProperty` while we use "XXX" as key to set MDC pattern in log4j.properties. It could also bring extra burden to the user.
### Does this PR introduce _any_ user-facing change?
No, as MDC feature is added in version 3.1, which hasn't been released.
### How was this patch tested?
Tested manually.
Closes#28801 from Ngone51/consistent-mdc.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
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This PR enriches the exception message when application summary is not available.
#28444 covers the case when application information is not available but the case application summary is not available is not covered.
### Why are the changes needed?
<!--
Please clarify why the changes are needed. For instance,
1. If you propose a new API, clarify the use case for a new API.
2. If you fix a bug, you can clarify why it is a bug.
-->
To complement #28444 .
### Does this PR introduce _any_ user-facing change?
<!--
Note that it means *any* user-facing change including all aspects such as the documentation fix.
If yes, please clarify the previous behavior and the change this PR proposes - provide the console output, description and/or an example to show the behavior difference if possible.
If possible, please also clarify if this is a user-facing change compared to the released Spark versions or within the unreleased branches such as master.
If no, write 'No'.
-->
Yes.
Before this change, we can get the following error message when we access to `/jobs` if application summary is not available.
<img width="707" alt="no-such-element-exception-error-message" src="https://user-images.githubusercontent.com/4736016/84562182-6aadf200-ad8d-11ea-8980-d63edde6fad6.png">
After this change, we can get the following error message. It's like #28444 does.
<img width="1349" alt="enriched-errorm-message" src="https://user-images.githubusercontent.com/4736016/84562189-85806680-ad8d-11ea-8346-4da2ec11df2b.png">
### How was this patch tested?
<!--
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If tests were not added, please describe why they were not added and/or why it was difficult to add.
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I checked with the following procedure.
1. Set breakpoint in the line of `kvstore.write(appSummary)` in `AppStatusListener#onStartApplicatin`. Only the thread reaching this line should be suspended.
2. Start spark-shell and wait few seconds.
3. Access to `/jobs`
Closes#28820 from sarutak/fix-no-such-element.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### 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?
#28747 reverted #28439 due to some flaky test case. This PR fixes the flaky test and adds pagination support.
### Why are the changes needed?
To support pagination for streaming tab
### Does this PR introduce _any_ user-facing change?
Yes, Now streaming tab tables will be paginated.
### How was this patch tested?
Manually.
Closes#28748 from iRakson/fixstreamingpagination.
Authored-by: iRakson <raksonrakesh@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR upgrades HtmlUnit.
Selenium and Jetty also upgraded because of dependency.
### Why are the changes needed?
Recently, a security issue which affects HtmlUnit is reported.
https://nvd.nist.gov/vuln/detail/CVE-2020-5529
According to the report, arbitrary code can be run by malicious users.
HtmlUnit is used for test so the impact might not be large but it's better to upgrade it just in case.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing testcases.
Closes#28585 from sarutak/upgrade-htmlunit.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR is a followup of #26624. This PR cleans up MDC properties if the original value is empty.
Besides, this PR adds a warning and ignore the value when the user tries to override the value of `taskName`.
### Why are the changes needed?
Before this PR, running the following jobs:
```
sc.setLocalProperty("mdc.my", "ABC")
sc.parallelize(1 to 100).count()
sc.setLocalProperty("mdc.my", null)
sc.parallelize(1 to 100).count()
```
there's still MDC value "ABC" in the log of the second count job even if we've unset the value.
### Does this PR introduce _any_ user-facing change?
Yes, user will 1) no longer see the MDC values after unsetting the value; 2) see a warning if he/she tries to override the value of `taskName`.
### How was this patch tested?
Tested Manaually.
Closes#28756 from Ngone51/followup-8981.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
After SPARK-31632 SparkException is thrown from def applicationInfo
`def applicationInfo(): v1.ApplicationInfo = {
try {
// The ApplicationInfo may not be available when Spark is starting up.
store.view(classOf[ApplicationInfoWrapper]).max(1).iterator().next().info
} catch {
case _: NoSuchElementException =>
throw new SparkException("Failed to get the application information. " +
"If you are starting up Spark, please wait a while until it's ready.")
}
}`
Where as the caller for this method def getSparkUser in Spark UI is not handling SparkException in the catch
`def getSparkUser: String = {
try {
Option(store.applicationInfo().attempts.head.sparkUser)
.orElse(store.environmentInfo().systemProperties.toMap.get("user.name"))
.getOrElse("<unknown>")
} catch {
case _: NoSuchElementException => "<unknown>"
}
}`
So On using this method (getSparkUser )we can get the application erred out.
As the part of this PR we will replace SparkException to NoSuchElementException for applicationInfo in AppStatusStore
### Why are the changes needed?
On invoking the method getSparkUser, we can get the SparkException on calling store.applicationInfo(). And this is not handled in the catch block and getSparkUser will error out in this scenario
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Done the manual testing using the spark-shell and spark-submit
Closes#28768 from SaurabhChawla100/SPARK-31941.
Authored-by: SaurabhChawla <saurabhc@qubole.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
This PR replaces constant config with the `ConfigEntry`.
### Why are the changes needed?
For better code maintenance.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Tested manually.
Closes#28775 from Ngone51/followup-SPARK-31486.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes to make `PythonFunction` holds `Seq[Byte]` instead of `Array[Byte]` to be able to compare if the byte array has the same values for the cache manager.
### Why are the changes needed?
Currently the cache manager doesn't use the cache for `udf` if the `udf` is created again even if the functions is the same.
```py
>>> func = lambda x: x
>>> df = spark.range(1)
>>> df.select(udf(func)("id")).cache()
```
```py
>>> df.select(udf(func)("id")).explain()
== Physical Plan ==
*(2) Project [pythonUDF0#14 AS <lambda>(id)#12]
+- BatchEvalPython [<lambda>(id#0L)], [pythonUDF0#14]
+- *(1) Range (0, 1, step=1, splits=12)
```
This is because `PythonFunction` holds `Array[Byte]`, and `equals` method of array equals only when the both array is the same instance.
### Does this PR introduce _any_ user-facing change?
Yes, if the user reuse the Python function for the UDF, the cache manager will detect the same function and use the cache for it.
### How was this patch tested?
I added a test case and manually.
```py
>>> df.select(udf(func)("id")).explain()
== Physical Plan ==
InMemoryTableScan [<lambda>(id)#12]
+- InMemoryRelation [<lambda>(id)#12], StorageLevel(disk, memory, deserialized, 1 replicas)
+- *(2) Project [pythonUDF0#5 AS <lambda>(id)#3]
+- BatchEvalPython [<lambda>(id#0L)], [pythonUDF0#5]
+- *(1) Range (0, 1, step=1, splits=12)
```
Closes#28774 from ueshin/issues/SPARK-31945/udf_cache.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR adds the check to see whether the allocated executors for the waiting application is empty before recognizing it as a possible hang application.
### Why are the changes needed?
It's a bugfix. The warning means there are not enough resources for the application to launch at least one executor. But we can still successfully run a job under this warning, which means it does have launched executor.
### Does this PR introduce _any_ user-facing change?
Yes. Before this PR, when using local cluster mode to start spark-shell, e.g. `./bin/spark-shell --master "local-cluster[2, 1, 1024]"`, the user would always see the warning:
```
20/06/06 22:21:02 WARN Utils: Your hostname, C02ZQ051LVDR resolves to a loopback address: 127.0.0.1; using 192.168.1.6 instead (on interface en0)
20/06/06 22:21:02 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
20/06/06 22:21:02 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
NOTE: SPARK_PREPEND_CLASSES is set, placing locally compiled Spark classes ahead of assembly.
NOTE: SPARK_PREPEND_CLASSES is set, placing locally compiled Spark classes ahead of assembly.
Spark context Web UI available at http://192.168.1.6:4040
Spark context available as 'sc' (master = local-cluster[2, 1, 1024], app id = app-20200606222107-0000).
Spark session available as 'spark'.
20/06/06 22:21:07 WARN Master: App app-20200606222107-0000 requires more resource than any of Workers could have.
20/06/06 22:21:07 WARN Master: App app-20200606222107-0000 requires more resource than any of Workers could have.
```
After this PR, the warning has gone.
### How was this patch tested?
Tested manually.
Closes#28742 from Ngone51/fix_warning.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
These changes implement an application wait mechanism which will allow spark-submit to wait until the application finishes in Standalone Spark Mode. This will delay the exit of spark-submit JVM until the job is completed. This implementation will keep monitoring the application until it is either finished, failed or killed. This will be controlled via a flag (spark.submit.waitForCompletion) which will be set to false by default.
### Why are the changes needed?
Currently, Livy API for Standalone Cluster Mode doesn't know when the job has finished. If this flag is enabled, this can be used by Livy API (/batches/{batchId}/state) to find out when the application has finished/failed. This flag is Similar to spark.yarn.submit.waitAppCompletion.
### Does this PR introduce any user-facing change?
Yes, this PR introduces a new flag but it will be disabled by default.
### How was this patch tested?
Couldn't implement unit tests since the pollAndReportStatus method has System.exit() calls. Please provide any suggestions.
Tested spark-submit locally for the following scenarios:
1. With the flag enabled, spark-submit exits once the job is finished.
2. With the flag enabled and job failed, spark-submit exits when the job fails.
3. With the flag disabled, spark-submit exists post submitting the job (existing behavior).
4. Existing behavior is unchanged when the flag is not added explicitly.
Closes#28258 from akshatb1/master.
Lead-authored-by: Akshat Bordia <akshat.bordia31@gmail.com>
Co-authored-by: Akshat Bordia <akshat.bordia@citrix.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Ignore internal accumulators that use unrecognized types rather than crashing so that an event log containing such accumulators can still be converted to JSON and logged.
### Why are the changes needed?
A user may use internal accumulators by adding the `internal.metrics.` prefix to the accumulator name to hide sensitive information from UI (Accumulators except internal ones will be shown in Spark UI).
However, `org.apache.spark.util.JsonProtocol.accumValueToJson` assumes an internal accumulator has only 3 possible types: `int`, `long`, and `java.util.List[(BlockId, BlockStatus)]`. When an internal accumulator uses an unexpected type, it will crash.
An event log that contains such accumulator will be dropped because it cannot be converted to JSON, and it will cause weird UI issue when rendering in Spark History Server. For example, if `SparkListenerTaskEnd` is dropped because of this issue, the user will see the task is still running even if it was finished.
It's better to make `accumValueToJson` more robust because it's up to the user to pick up the accumulator name.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
The new unit tests.
Closes#28744 from zsxwing/fix-internal-accum.
Authored-by: Shixiong Zhu <zsxwing@gmail.com>
Signed-off-by: Shixiong Zhu <zsxwing@gmail.com>
This PR reverts #28439 due to that PR breaks QA build.
Closes#28747 from sarutak/revert-SPARK-30119.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
* Pagination Support is added to all tables of streaming page in spark web UI.
For adding pagination support, existing classes from #7399 were used.
* Earlier streaming page has two tables `Active Batches` and `Completed Batches`. Now, we will have three tables `Running Batches`, `Waiting Batches` and `Completed Batches`. If we have large number of waiting and running batches then keeping track in a single table is difficult. Also other pages have different table for different type type of data.
* Earlier empty tables were shown. Now only non-empty tables will be shown.
`Active Batches` table used to show details of waiting batches followed by running batches.
### Why are the changes needed?
Pagination will allow users to analyse the table in much better way. All spark web UI pages support pagination apart from streaming pages, so this will add consistency as well. Also it might fix the potential OOM errors that can arise.
### Does this PR introduce _any_ user-facing change?
Yes. `Active Batches` table is split into two tables `Running Batches` and `Waiting Batches`. Pagination Support is added to the all the tables. Every other functionality is unchanged.
### How was this patch tested?
Manually.
Before changes:
<img width="1667" alt="Screenshot 2020-05-03 at 7 07 14 PM" src="https://user-images.githubusercontent.com/15366835/80915680-8fb44b80-8d71-11ea-9957-c4a3769b8b67.png">
After Changes:
<img width="1669" alt="Screenshot 2020-05-03 at 6 51 22 PM" src="https://user-images.githubusercontent.com/15366835/80915694-a9ee2980-8d71-11ea-8fc5-246413a4951d.png">
Closes#28439 from iRakson/streamingPagination.
Authored-by: iRakson <raksonrakesh@gmail.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
This PR fixes a wrong coloring issue in the DAG-viz.
In the Job Page and Stage Page, nodes which are associated with "barrier mode" in the DAG-viz will be colored pale green.
But, with some type of jobs, nodes which are not associated with the mode will also colored.
You can reproduce with the following operation.
```
sc.parallelize(1 to 10).barrier.mapPartitions(identity).repartition(1).collect()
```
<img width="376" alt="wrong-coloring" src="https://user-images.githubusercontent.com/4736016/83403670-1711df00-a444-11ea-9457-c683f75bc566.png">
In the screen shot above, `repartition` in `Stage 1` is not associated with barrier mode so the corresponding node should not be colored pale green.
The cause of this issue is the logic which chooses HTML elements to be colored is wrong.
The logic chooses such elements based on whether each element is associated with a style class (`clusterId` in the code).
But when an operation crosses over shuffle (like `repartition` above), a `clusterId` can be duplicated and non-barrier mode node is also associated with the same `clusterId`.
### Why are the changes needed?
This is a bug.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Newly added test case with the following command.
```
build/sbt -Dtest.default.exclude.tags= -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.ui.ChromeUISeleniumSuite -- -z SPARK-31886"
```
Closes#28694 from sarutak/fix-wrong-barrier-color.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
This PR fix an issue related to DAG-viz.
Because DAG-viz for a job fetches link urls for each stage from the stage table, rendering can fail with pagination.
You can reproduce this issue with the following operation.
```
sc.parallelize(1 to 10).map(value => (value ,value)).repartition(1).repartition(1).repartition(1).reduceByKey(_ + _).collect
```
And then, visit the corresponding job page.
There are 5 stages so show <5 stages in the paged table.
<img width="1440" alt="dag-rendering-issue1" src="https://user-images.githubusercontent.com/4736016/83376286-c29f3d00-a40c-11ea-891b-eb8f42afbb27.png">
<img width="1439" alt="dag-rendering-issue2" src="https://user-images.githubusercontent.com/4736016/83376288-c3d06a00-a40c-11ea-8bb2-38542e5010c1.png">
### Why are the changes needed?
This is a bug.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Newly added test case with following command.
`build/sbt -Dtest.default.exclude.tags= -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.ui.ChromeUISeleniumSuite -- -z SPARK-31882"`
Closes#28690 from sarutak/fix-dag-rendering-issue.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
This PR upgrades HtmlUnit.
Selenium and Jetty also upgraded because of dependency.
### Why are the changes needed?
Recently, a security issue which affects HtmlUnit is reported.
https://nvd.nist.gov/vuln/detail/CVE-2020-5529
According to the report, arbitrary code can be run by malicious users.
HtmlUnit is used for test so the impact might not be large but it's better to upgrade it just in case.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing testcases.
Closes#28585 from sarutak/upgrade-htmlunit.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR is to make the RDD api for stage level scheduling public. All the other jiras for functionality are in so now we can make it public for people to use and tag it properly.
### Why are the changes needed?
to make it usable.
### Does this PR introduce _any_ user-facing change?
Yes the api is now public
### How was this patch tested?
Unit tests and manually tested.
Closes#28697 from tgravescs/SPARK-29150.
Lead-authored-by: Thomas Graves <tgraves@apache.org>
Co-authored-by: Thomas Graves <tgraves@nvidia.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR adds two things.
Real headless browser support for HistoryServer tests.
A test suite using headless Chrome as one instance of those browsers.
### Why are the changes needed?
The motivation is same as #28578 .
In the current master, there is a testcase for HistoryServer which uses Ajax so we need the support for HistoryServer tests.
Also this change is necessary to upgrade HtmlUnit (See #28585)
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
I tested with following patterns. Both Chrome and Chrome driver should be installed to test.
1. sbt / with default excluded tags (ChromeUIHistoryServerSuite is expected to be skipped and SQLQueryTestSuite is expected to succeed)
`build/sbt -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.deploy.history.ChromeUIHistoryServerSuite org.apache.spark.sql.SQLQueryTestSuite"
2. sbt / overwrite default excluded tags as empty string (Both suites are expected to succeed)
`build/sbt -Dtest.default.exclude.tags= -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.deploy.history.ChromeUIHistoryServerSuite org.apache.spark.sql.SQLQueryTestSuite"
3. sbt / set `test.exclude.tags` to `org.apache.spark.tags.ExtendedSQLTest` (Both suites are expected to be skipped)
`build/sbt -Dtest.exclude.tags=org.apache.spark.tags.ExtendedSQLTest -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.deploy.history.ChromeUIHistoryServerSuite org.apache.spark.sql.SQLQueryTestSuite"
4. Maven / with default excluded tags (ChromeUIHistoryServerSuite is expected to be skipped and SQLQueryTestSuite is expected to succeed)
`build/mvn -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.deploy.history.ChromeUIHistoryServerSuite,org.apache.spark.sql.SQLQueryTestSuite test`
5. Maven / overwrite default excluded tags as empty string (Both suites are expected to succeed)
`build/mvn -Dtest.default.exclude.tags= -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.deploy.history.ChromeUIHistoryServerSuite,org.apache.spark.sql.SQLQueryTestSuite test`
6. Maven / set `test.exclude.tags` to `org.apache.spark.tags.ExtendedSQLTest` (Both suites are expected to be skipped)
`build/mvn -Dtest.exclude.tags=org.apache.spark.tags.ExtendedSQLTest -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.deploy.history.ChromeUIHistoryServerSuite,org.apache.spark.sql.SQLQueryTestSuite test`
Closes#28622 from sarutak/headless-browser-support-for-historyserver.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR proposes to shift to the new most local locality level if there're any new more local locality levels are added during `TaskSetManager.recomputeLocality`.
### Why are the changes needed?
There's a race condition between `resourceOffers` and `submitTasks`. If `submitTasks` happens before `resourceOffers`, especially when there are no executors added to `TaskSchedulerImpl` at all, the `TaskSetManager` 's `myLocalityLevels` will only have ANY locality level, see:
8b4862953a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala (L218)
And then, `resourceOffers` is called with new executors added to `TaskSchedulerImpl`. Then, `recomputeLocality` will be called because of `executorAdded`. During `recomputeLocality`, the TaskSetManager's `myLocalityLevels` might have PROCESS_LOCAL, NODE_LOCAL, ANY(because at this time we could find alive executors from TaskSchedulerImpl). But the `TaskSetManager` will stick to the previous locality level, which is ANY, see:
8b4862953a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala (L1107-L1114)
As a result, in the first round of `resourceOffers`, the new version delay scheduling won't take effect and `TaskSetManager` can only schedule tasks at ANY level.
Please note that the problem also exists in old version delay scheduling but the impact is minor because we always reset the locality level after successfully launching a task, which is broken in the new version of dealy scheduling.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Updated and added new test.
Closes#28656 from Ngone51/impr_recompute.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR mainly adds two things.
1. Real headless browser support for UI test
2. A test suite using headless Chrome as one instance of those browsers.
Also, for environment where Chrome and Chrome driver is not installed, `ChromeUITest` tag is added to filter out the test suite.
By default, test suites with `ChromeUITest` is disabled.
### Why are the changes needed?
In the current master, there are two problems for UI test.
1. Lots of tests especially JavaScript related ones are done manually.
Appearance is better to be confirmed by our eyes but logic should be tested by test cases ideally.
2. Compared to the real web browsers, HtmlUnit doesn't seem to support JavaScript enough.
I added a JavaScript related test before for SPARK-31534 using HtmlUnit which is simple library based headless browser for test.
The test I added works somehow but some JavaScript related error is shown in unit-tests.log.
```
======= EXCEPTION START ========
Exception class=[net.sourceforge.htmlunit.corejs.javascript.JavaScriptException]
com.gargoylesoftware.htmlunit.ScriptException: Error: TOOLTIP: Option "sanitizeFn" provided type "window" but expected type "(null|function)". (http://192.168.1.209:60724/static/jquery-3.4.1.min.js#2)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine$HtmlUnitContextAction.run(JavaScriptEngine.java:904)
at net.sourceforge.htmlunit.corejs.javascript.Context.call(Context.java:628)
at net.sourceforge.htmlunit.corejs.javascript.ContextFactory.call(ContextFactory.java:515)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine.callFunction(JavaScriptEngine.java:835)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine.callFunction(JavaScriptEngine.java:807)
at com.gargoylesoftware.htmlunit.InteractivePage.executeJavaScriptFunctionIfPossible(InteractivePage.java:216)
at com.gargoylesoftware.htmlunit.javascript.background.JavaScriptFunctionJob.runJavaScript(JavaScriptFunctionJob.java:52)
at com.gargoylesoftware.htmlunit.javascript.background.JavaScriptExecutionJob.run(JavaScriptExecutionJob.java:102)
at com.gargoylesoftware.htmlunit.javascript.background.JavaScriptJobManagerImpl.runSingleJob(JavaScriptJobManagerImpl.java:426)
at com.gargoylesoftware.htmlunit.javascript.background.DefaultJavaScriptExecutor.run(DefaultJavaScriptExecutor.java:157)
at java.lang.Thread.run(Thread.java:748)
Caused by: net.sourceforge.htmlunit.corejs.javascript.JavaScriptException: Error: TOOLTIP: Option "sanitizeFn" provided type "window" but expected type "(null|function)". (http://192.168.1.209:60724/static/jquery-3.4.1.min.js#2)
at net.sourceforge.htmlunit.corejs.javascript.Interpreter.interpretLoop(Interpreter.java:1009)
at net.sourceforge.htmlunit.corejs.javascript.Interpreter.interpret(Interpreter.java:800)
at net.sourceforge.htmlunit.corejs.javascript.InterpretedFunction.call(InterpretedFunction.java:105)
at net.sourceforge.htmlunit.corejs.javascript.ContextFactory.doTopCall(ContextFactory.java:413)
at com.gargoylesoftware.htmlunit.javascript.HtmlUnitContextFactory.doTopCall(HtmlUnitContextFactory.java:252)
at net.sourceforge.htmlunit.corejs.javascript.ScriptRuntime.doTopCall(ScriptRuntime.java:3264)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine$4.doRun(JavaScriptEngine.java:828)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine$HtmlUnitContextAction.run(JavaScriptEngine.java:889)
... 10 more
JavaScriptException value = Error: TOOLTIP: Option "sanitizeFn" provided type "window" but expected type "(null|function)".
== CALLING JAVASCRIPT ==
function () {
throw e;
}
======= EXCEPTION END ========
```
I tried to upgrade HtmlUnit to 2.40.0 but what is worse, the test become not working even though it works on real browsers like Chrome, Safari and Firefox without error.
```
[info] UISeleniumSuite:
[info] - SPARK-31534: text for tooltip should be escaped *** FAILED *** (17 seconds, 745 milliseconds)
[info] The code passed to eventually never returned normally. Attempted 2 times over 12.910785232 seconds. Last failure message: com.gargoylesoftware.htmlunit.ScriptException: ReferenceError: Assignment to undefined "regeneratorRuntime" in strict mode (http://192.168.1.209:62132/static/vis-timeline-graph2d.min.js#52(Function)#1)
```
To resolve those problems, it's better to support headless browser for UI test.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
I tested with following patterns. Both Chrome and Chrome driver should be installed to test.
1. sbt / with default excluded tags (ChromeUISeleniumSuite is expected to be skipped and SQLQueryTestSuite is expected to succeed)
`build/sbt -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.ui.ChromeUISeleniumSuite org.apache.spark.sql.SQLQueryTestSuite"
2. sbt / overwrite default excluded tags as empty string (Both suites are expected to succeed)
`build/sbt -Dtest.default.exclude.tags= -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.ui.ChromeUISeleniumSuite org.apache.spark.sql.SQLQueryTestSuite"
3. sbt / set `test.exclude.tags` to `org.apache.spark.tags.ExtendedSQLTest` (Both suites are expected to be skipped)
`build/sbt -Dtest.exclude.tags=org.apache.spark.tags.ExtendedSQLTest -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.ui.ChromeUISeleniumSuite org.apache.spark.sql.SQLQueryTestSuite"
4. Maven / with default excluded tags (ChromeUISeleniumSuite is expected to be skipped and SQLQueryTestSuite is expected to succeed)
`build/mvn -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite,org.apache.spark.sql.SQLQueryTestSuite test`
5. Maven / overwrite default excluded tags as empty string (Both suites are expected to succeed)
`build/mvn -Dtest.default.exclude.tags= -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite,org.apache.spark.sql.SQLQueryTestSuite test`
6. Maven / set `test.exclude.tags` to `org.apache.spark.tags.ExtendedSQLTest` (Both suites are expected to be skipped)
`build/mvn -Dtest.exclude.tags=org.apache.spark.tags.ExtendedSQLTest -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite,org.apache.spark.sql.SQLQueryTestSuite test`
Closes#28627 from sarutak/real-headless-browser-support-take2.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
To wait until all the executors have started before submitting any job. This could avoid the flakiness caused by waiting for executors coming up.
### How was this patch tested?
Existing tests.
Closes#28584 from jiangxb1987/barrierTest.
Authored-by: Xingbo Jiang <xingbo.jiang@databricks.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
This PR changes JsonProtocol to write RDDInfos#isBarrier.
### Why are the changes needed?
JsonProtocol reads RDDInfos#isBarrier but not write it so it's a bug.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
I added a testcase.
Closes#28583 from sarutak/SPARK-31764.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
Pagination code across pages needs to be cleaned.
I have tried to clear out these things :
* Unused methods
* Unused method arguments
* remove redundant `if` expressions
* fix indentation
### Why are the changes needed?
This fix will make code more readable and remove unnecessary methods and variables.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manually
Closes#28448 from iRakson/refactorPagination.
Authored-by: iRakson <raksonrakesh@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Currently, the data source scan node stores all the paths in its metadata. The metadata is kept when a SparkPlan is converted into SparkPlanInfo. SparkPlanInfo can be used to construct the Spark plan graph in UI.
However, the paths can be very large (e.g. it can be many partitions after partition pruning), while UI pages only require up to 100 bytes for the location metadata. We can reduce the paths stored in metadata to reduce memory usage.
### Why are the changes needed?
Reduce unnecessary memory cost.
In the heap dump of a driver, the SparkPlanInfo instances are quite large and it should be avoided:
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unit tests
Closes#28610 from gengliangwang/improveLocationMetadata.
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?
Increase the timeout and register the listener earlier to avoid any race condition of the job starting before the listener is registered.
### Why are the changes needed?
The test is currently semi-flaky.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
I'm currently running the following bash script on my dev machine to verify the flakiness decreases. It has gotten to 356 iterations without any test failures so I believe issue is fixed.
```
set -ex
./build/sbt clean compile package
((failures=0))
for (( i=0;i<1000;++i )); do
echo "Run $i"
((failed=0))
./build/sbt "core/testOnly org.apache.spark.scheduler.WorkerDecommissionSuite" || ((failed=1))
echo "Resulted in $failed"
((failures=failures+failed))
echo "Current status is failures: $failures out of $i runs"
done
```
Closes#28614 from holdenk/SPARK-31791-improve-cache-block-migration-test-reliability.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR mainly adds two things.
1. Real headless browser support for UI test
2. A test suite using headless Chrome as one instance of those browsers.
Also, for environment where Chrome and Chrome driver is not installed, `ChromeUITest` tag is added to filter out the test suite.
### Why are the changes needed?
In the current master, there are two problems for UI test.
1. Lots of tests especially JavaScript related ones are done manually.
Appearance is better to be confirmed by our eyes but logic should be tested by test cases ideally.
2. Compared to the real web browsers, HtmlUnit doesn't seem to support JavaScript enough.
I added a JavaScript related test before for SPARK-31534 using HtmlUnit which is simple library based headless browser for test.
The test I added works somehow but some JavaScript related error is shown in unit-tests.log.
```
======= EXCEPTION START ========
Exception class=[net.sourceforge.htmlunit.corejs.javascript.JavaScriptException]
com.gargoylesoftware.htmlunit.ScriptException: Error: TOOLTIP: Option "sanitizeFn" provided type "window" but expected type "(null|function)". (http://192.168.1.209:60724/static/jquery-3.4.1.min.js#2)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine$HtmlUnitContextAction.run(JavaScriptEngine.java:904)
at net.sourceforge.htmlunit.corejs.javascript.Context.call(Context.java:628)
at net.sourceforge.htmlunit.corejs.javascript.ContextFactory.call(ContextFactory.java:515)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine.callFunction(JavaScriptEngine.java:835)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine.callFunction(JavaScriptEngine.java:807)
at com.gargoylesoftware.htmlunit.InteractivePage.executeJavaScriptFunctionIfPossible(InteractivePage.java:216)
at com.gargoylesoftware.htmlunit.javascript.background.JavaScriptFunctionJob.runJavaScript(JavaScriptFunctionJob.java:52)
at com.gargoylesoftware.htmlunit.javascript.background.JavaScriptExecutionJob.run(JavaScriptExecutionJob.java:102)
at com.gargoylesoftware.htmlunit.javascript.background.JavaScriptJobManagerImpl.runSingleJob(JavaScriptJobManagerImpl.java:426)
at com.gargoylesoftware.htmlunit.javascript.background.DefaultJavaScriptExecutor.run(DefaultJavaScriptExecutor.java:157)
at java.lang.Thread.run(Thread.java:748)
Caused by: net.sourceforge.htmlunit.corejs.javascript.JavaScriptException: Error: TOOLTIP: Option "sanitizeFn" provided type "window" but expected type "(null|function)". (http://192.168.1.209:60724/static/jquery-3.4.1.min.js#2)
at net.sourceforge.htmlunit.corejs.javascript.Interpreter.interpretLoop(Interpreter.java:1009)
at net.sourceforge.htmlunit.corejs.javascript.Interpreter.interpret(Interpreter.java:800)
at net.sourceforge.htmlunit.corejs.javascript.InterpretedFunction.call(InterpretedFunction.java:105)
at net.sourceforge.htmlunit.corejs.javascript.ContextFactory.doTopCall(ContextFactory.java:413)
at com.gargoylesoftware.htmlunit.javascript.HtmlUnitContextFactory.doTopCall(HtmlUnitContextFactory.java:252)
at net.sourceforge.htmlunit.corejs.javascript.ScriptRuntime.doTopCall(ScriptRuntime.java:3264)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine$4.doRun(JavaScriptEngine.java:828)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine$HtmlUnitContextAction.run(JavaScriptEngine.java:889)
... 10 more
JavaScriptException value = Error: TOOLTIP: Option "sanitizeFn" provided type "window" but expected type "(null|function)".
== CALLING JAVASCRIPT ==
function () {
throw e;
}
======= EXCEPTION END ========
```
I tried to upgrade HtmlUnit to 2.40.0 but what is worse, the test become not working even though it works on real browsers like Chrome, Safari and Firefox without error.
```
[info] UISeleniumSuite:
[info] - SPARK-31534: text for tooltip should be escaped *** FAILED *** (17 seconds, 745 milliseconds)
[info] The code passed to eventually never returned normally. Attempted 2 times over 12.910785232 seconds. Last failure message: com.gargoylesoftware.htmlunit.ScriptException: ReferenceError: Assignment to undefined "regeneratorRuntime" in strict mode (http://192.168.1.209:62132/static/vis-timeline-graph2d.min.js#52(Function)#1)
```
To resolve those problems, it's better to support headless browser for UI test.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
I tested with following patterns. Both Chrome and Chrome driver should be installed to test.
1. sbt / with chromedriver / include tag (expect to succeed)
`build/sbt -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.ui.ChromeUISeleniumSuite"`
2. sbt / with chromedriver / exclude tag (expect to be ignored)
`build/sbt -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.ui.ChromeUISeleniumSuite -l org.apache.spark.tags.ChromeUITest"`
3. sbt / without chromedriver / include tag (expect to be failed)
`build/sbt "testOnly org.apache.spark.ui.ChromeUISeleniumSuite"`
4. sbt / without chromedriver / exclude tag (expect to be skipped)
`build/sbt -Dtest.exclude.tags=org.apache.spark.tags.ChromeUITest "testOnly org.apache.spark.ui.ChromeUISeleniumSuite"`
5. Maven / wth chromedriver / include tag (expect to succeed)
`build/mvn -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite test`
6. Maven / with chromedriver / exclude tag (expect to be skipped)
`build/mvn -Dtest.exclude.tags="org.apache.spark.tags.ChromeUITest" -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite test`
7. Maven / without chromedriver / include tag (expect to be failed)
`build/mvn -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite test`
8. Maven / without chromedriver / exclude tag (expect to be skipped)
`build/mvn -Dtest.exclude.tags=org.apache.spark.tags.ChromeUITest -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite test`
Closes#28578 from sarutak/real-headless-browser-support.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
The function `HistoryServerDiskManager`.`updateAccessTime()` would recompute the application store directory size every time it's triggered, this effort could be avoided because we already computed the new size outside the function call.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing test cases.
Closes#28579 from jiangxb1987/updateInfo.
Authored-by: Xingbo Jiang <xingbo.jiang@databricks.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
Change from `messages.toList.iterator` to `Iterator.single(messages.toList)`.
### Why are the changes needed?
In this test, the expected result of `rdd2.collect().head` should actually be `List("0", "1", "2", "3")` but is `"0"` now.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Updated test.
Thanks WeichenXu123 reported this problem.
Closes#28596 from Ngone51/fix_allgather_test.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
This reverts commit 92877c4ef2.
Closes#28602 from gengliangwang/revertSPARK-31765.
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?
This PR upgrades HtmlUnit.
Selenium and Jetty also upgraded because of dependency.
### Why are the changes needed?
Recently, a security issue which affects HtmlUnit is reported.
https://nvd.nist.gov/vuln/detail/CVE-2020-5529
According to the report, arbitrary code can be run by malicious users.
HtmlUnit is used for test so the impact might not be large but it's better to upgrade it just in case.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing testcases.
Closes#28585 from sarutak/upgrade-htmlunit.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
This adds UI updates to support stage level scheduling and ResourceProfiles. 3 main things have been added. ResourceProfile id added to the Stage page, the Executors page now has an optional selectable column to show the ResourceProfile Id of each executor, and the Environment page now has a section with the ResourceProfile ids. Along with this the rest api for environment page was updated to include the Resource profile information.
I debating on splitting the resource profile information into its own page but I wasn't sure it called for a completely separate page. Open to peoples thoughts on this.
Screen shots:
### Why are the changes needed?
For user to be able to know what resource profile was used with which stage and executors. The resource profile information is also available so user debugging can see exactly what resources were requested with that profile.
### Does this PR introduce any user-facing change?
Yes, UI updates.
### How was this patch tested?
Unit tests and tested on yarn both active applications and with the history server.
Closes#28094 from tgravescs/SPARK-29303-pr.
Lead-authored-by: Thomas Graves <tgraves@nvidia.com>
Co-authored-by: Thomas Graves <tgraves@apache.org>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
Currently while implementing pagination using the existing pagination framework, a lot of code is being copied as pointed out [here](https://github.com/apache/spark/pull/28485#pullrequestreview-408881656).
I introduced some changes in `PagedTable` which is the main trait for implementing the pagination.
* Added function for getting table parameters.
* Added a function for table header row. This will help in maintaining consistency across the tables. All the header rows across tables will be consistent now.
### Why are the changes needed?
* A lot of code is copied every time pagination is implemented for any table.
* Code readability is not great as lot of HTML is embedded.
* Paginating other tables will be a lot easier now.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manually. This is mainly refactoring work, no new functionality introduced. Existing test cases should pass.
Closes#28512 from iRakson/refactorPaginationFramework.
Authored-by: iRakson <raksonrakesh@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Added `since 3.0.0` for `ResourceDiscoveryScriptPlugin` and `ResourceInformation`.
### Why are the changes needed?
It's required for exposed APIs(https://github.com/apache/spark/pull/27689#discussion_r426488851).
### Does this PR introduce _any_ user-facing change?
Yes, they can easily know when does Spark introduces the API.
### How was this patch tested?
Pass Jenkins.
Closes#28591 from Ngone51/followup-30689.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Added MDC support in all thread pools.
ThreaddUtils create new pools that pass over MDC.
### Why are the changes needed?
In many cases, it is very hard to understand from which actions the logs in the executor come from.
when you are doing multi-thread work in the driver and send actions in parallel.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
No test added because no new functionality added it is thread pull change and all current tests pass.
Closes#26624 from igreenfield/master.
Authored-by: Izek Greenfield <igreenfield@axiomsl.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
With SPARK-18107, we will disable the underlying replace(overwrite) and instead do delete in spark side and only do copy in hive side to bypass the performance issue - [HIVE-11940](https://issues.apache.org/jira/browse/HIVE-11940)
Conditionally, if the table location and partition location do not belong to the same `FileSystem`, We should not disable hive overwrite. Otherwise, hive will use the `FileSystem` instance belong to the table location to copy files, which will fail in `FileSystem#checkPath`
https://github.com/apache/hive/blob/rel/release-2.3.7/ql/src/java/org/apache/hadoop/hive/ql/metadata/Hive.java#L1657
In this PR, for Hive 2.0.0 and onwards, as [HIVE-11940](https://issues.apache.org/jira/browse/HIVE-11940) has been fixed, and there is no performance issue anymore. We should leave the overwrite logic to hive to avoid failure in `FileSystem#checkPath`
**NOTE THAT** For Hive 2.2.0 and earlier, if the table and partition locations do not belong together, we will still get the same error thrown by hive encryption check due to [HIVE-14380]( https://issues.apache.org/jira/browse/HIVE-14380) which need to fix in another ticket SPARK-31675.
### Why are the changes needed?
bugfix. a logic table can be decoupled with the storage layer and may contain data from remote storage systems.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
Currently verified manually. add benchmark tests
```sql
-INSERT INTO DYNAMIC 7742 7918 248 0.0 756044.0 1.0X
-INSERT INTO HYBRID 1289 1307 26 0.0 125866.3 6.0X
-INSERT INTO STATIC 371 393 38 0.0 36219.4 20.9X
-INSERT OVERWRITE DYNAMIC 8456 8554 138 0.0 825790.3 0.9X
-INSERT OVERWRITE HYBRID 1303 1311 12 0.0 127198.4 5.9X
-INSERT OVERWRITE STATIC 434 447 13 0.0 42373.8 17.8X
+INSERT INTO DYNAMIC 7382 7456 105 0.0 720904.8 1.0X
+INSERT INTO HYBRID 1128 1129 1 0.0 110169.4 6.5X
+INSERT INTO STATIC 349 370 39 0.0 34095.4 21.1X
+INSERT OVERWRITE DYNAMIC 8149 8362 301 0.0 795821.8 0.9X
+INSERT OVERWRITE HYBRID 1317 1318 2 0.0 128616.7 5.6X
+INSERT OVERWRITE STATIC 387 408 37 0.0 37804.1 19.1X
```
+ for master
- for this PR
both using hive 2.3.7
Closes#28511 from yaooqinn/SPARK-31684.
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 improves handling the case where different barrier sync types in a single sync:
- use `clear` instead of `cleanupBarrierStage `
- make sure all requesters are failed because of "different barrier sync types"
### Why are the changes needed?
Currently, we use `cleanupBarrierStage` to clean up a barrier stage when we detecting the case of "different barrier sync types". But this leads to a problem that we could create new a `ContextBarrierState` for the same stage again if there're on-way requests from tasks. As a result, those task will fail because of killing instead of "different barrier sync types".
Besides, we don't handle the current request which is being handling properly as it will fail due to epoch mismatch instead of "different barrier sync types".
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Updated a existed test.
Closes#28462 from Ngone51/impr_barrier_req.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
After changes in SPARK-20628, CoarseGrainedSchedulerBackend can decommission an executor and stop assigning new tasks on it. We should also decommission the corresponding blockmanagers in the same way. i.e. Move the cached RDD blocks from those executors to other active executors.
### Why are the changes needed?
We need to gracefully decommission the block managers so that the underlying RDD cache blocks are not lost in case the executors are taken away forcefully after some timeout (because of spotloss/pre-emptible VM etc). Its good to save as much cache data as possible.
Also In future once the decommissioning signal comes from Cluster Manager (say YARN/Mesos etc), dynamic allocation + this change gives us opportunity to downscale the executors faster by making the executors free of cache data.
Note that this is a best effort approach. We try to move cache blocks from decommissioning executors to active executors. If the active executors don't have free resources available on them for caching, then the decommissioning executors will keep the cache block which it was not able to move and it will still be able to serve them.
Current overall Flow:
1. CoarseGrainedSchedulerBackend receives a signal to decommissionExecutor. On receiving the signal, it do 2 things - Stop assigning new tasks (SPARK-20628), Send another message to BlockManagerMasterEndpoint (via BlockManagerMaster) to decommission the corresponding BlockManager.
2. BlockManagerMasterEndpoint receives "DecommissionBlockManagers" message. On receiving this, it moves the corresponding block managers to "decommissioning" state. All decommissioning BMs are excluded from the getPeers RPC call which is used for replication. All these decommissioning BMs are also sent message from BlockManagerMasterEndpoint to start decommissioning process on themselves.
3. BlockManager on worker (say BM-x) receives the "DecommissionBlockManager" message. Now it will start BlockManagerDecommissionManager thread to offload all the RDD cached blocks. This thread can make multiple reattempts to decommission the existing cache blocks (multiple reattempts might be needed as there might not be sufficient space in other active BMs initially).
### Does this PR introduce any user-facing change?
NO
### How was this patch tested?
Added UTs.
Closes#28370 from prakharjain09/SPARK-20732-rddcache-1.
Authored-by: Prakhar Jain <prakharjain09@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR proposes to enhance Spark's `ClosureCleaner` to support "indylambda" style of Scala closures to the same level as the existing implementation for the old (inner class) style ones. The goal is to reach feature parity with the support of the old style Scala closures, with as close to bug-for-bug compatibility as possible.
Specifically, this PR addresses one lacking support for indylambda closures vs the inner class closures:
- When a closure is declared in a Scala REPL and captures the enclosing REPL line object, such closure should be cleanable (unreferenced fields on the enclosing REPL line object should be cleaned)
This PR maintains the same limitations in the new indylambda closure support as the old inner class closures, in particular the following two:
- Cleaning is only available for one level of REPL line object. If a closure captures state from a REPL line object further out from the immediate enclosing one, it won't be subject to cleaning. See example below.
- "Sibling" closures are not handled yet. A "sibling" closure is defined here as a closure that is directly or indirectly referenced by the starting closure, but isn't lexically enclosing. e.g.
```scala
{
val siblingClosure = (x: Int) => x + this.fieldA // captures `this`, references `fieldA` on `this`.
val startingClosure = (y: Int) => y + this.fieldB + siblingClosure(y) // captures `this` and `siblingClosure`, references `fieldB` on `this`.
}
```
The changes are intended to be minimal, with further code cleanups planned in separate PRs.
Jargons:
- old, inner class style Scala closures, aka `delambdafy:inline`: default in Scala 2.11 and before
- new, "indylambda" style Scala closures, aka `delambdafy:method`: default in Scala 2.12 and later
### Why are the changes needed?
There had been previous effortsto extend Spark's `ClosureCleaner` to support "indylambda" Scala closures, which is necessary for proper Scala 2.12 support. Most notably the work done for [SPARK-14540](https://issues.apache.org/jira/browse/SPARK-14540).
But the previous efforts had missed one import scenario: a Scala closure declared in a Scala REPL, and it captures the enclosing `this` -- a REPL line object. e.g. in a Spark Shell:
```scala
:pa
class NotSerializableClass(val x: Int)
val ns = new NotSerializableClass(42)
val topLevelValue = "someValue"
val func = (j: Int) => {
(1 to j).flatMap { x =>
(1 to x).map { y => y + topLevelValue }
}
}
<Ctrl+D>
sc.parallelize(0 to 2).map(func).collect
```
In this example, `func` refers to a Scala closure that captures the enclosing `this` because it needs to access `topLevelValue`, which is in turn implemented as a field on the enclosing REPL line object.
The existing `ClosureCleaner` in Spark supports cleaning this case in Scala 2.11-, and this PR brings feature parity to Scala 2.12+.
Note that the existing cleaning logic only supported one level of REPL line object nesting. This PR does not go beyond that. When a closure references state declared a few commands earlier, the cleaning will fail in both Scala 2.11 and Scala 2.12. e.g.
```scala
scala> :pa
// Entering paste mode (ctrl-D to finish)
class NotSerializableClass1(val x: Int)
case class Foo(id: String)
val ns = new NotSerializableClass1(42)
val topLevelValue = "someValue"
// Exiting paste mode, now interpreting.
defined class NotSerializableClass1
defined class Foo
ns: NotSerializableClass1 = NotSerializableClass1615b1baf
topLevelValue: String = someValue
scala> :pa
// Entering paste mode (ctrl-D to finish)
val closure2 = (j: Int) => {
(1 to j).flatMap { x =>
(1 to x).map { y => y + topLevelValue } // 2 levels
}
}
// Exiting paste mode, now interpreting.
closure2: Int => scala.collection.immutable.IndexedSeq[String] = <function1>
scala> sc.parallelize(0 to 2).map(closure2).collect
org.apache.spark.SparkException: Task not serializable
...
```
in the Scala 2.11 / Spark 2.4.x case:
```
Caused by: java.io.NotSerializableException: NotSerializableClass1
Serialization stack:
- object not serializable (class: NotSerializableClass1, value: NotSerializableClass1615b1baf)
- field (class: $iw, name: ns, type: class NotSerializableClass1)
- object (class $iw, $iw64df3f4b)
- field (class: $iw, name: $iw, type: class $iw)
- object (class $iw, $iw66e6e5e9)
- field (class: $line14.$read, name: $iw, type: class $iw)
- object (class $line14.$read, $line14.$readc310aa3)
- field (class: $iw, name: $line14$read, type: class $line14.$read)
- object (class $iw, $iw79224636)
- field (class: $iw, name: $outer, type: class $iw)
- object (class $iw, $iw636d4cdc)
- field (class: $anonfun$1, name: $outer, type: class $iw)
- object (class $anonfun$1, <function1>)
```
in the Scala 2.12 / Spark master case after this PR:
```
Caused by: java.io.NotSerializableException: NotSerializableClass1
Serialization stack:
- object not serializable (class: NotSerializableClass1, value: NotSerializableClass16f3b4c9a)
- field (class: $iw, name: ns, type: class NotSerializableClass1)
- object (class $iw, $iw2945a3c1)
- field (class: $iw, name: $iw, type: class $iw)
- object (class $iw, $iw152705d0)
- field (class: $line14.$read, name: $iw, type: class $iw)
- object (class $line14.$read, $line14.$read7cf311eb)
- field (class: $iw, name: $line14$read, type: class $line14.$read)
- object (class $iw, $iwd980dac)
- field (class: $iw, name: $outer, type: class $iw)
- object (class $iw, $iw557d9532)
- element of array (index: 0)
- array (class [Ljava.lang.Object;, size 1)
- field (class: java.lang.invoke.SerializedLambda, name: capturedArgs, type: class [Ljava.lang.Object;)
- object (class java.lang.invoke.SerializedLambda, SerializedLambda[capturingClass=class $iw, functionalInterfaceMethod=scala/Function1.apply:(Ljava/lang/Object;)Ljava/lang/Object;, implementation=invokeStatic $anonfun$closure2$1$adapted:(L$iw;Ljava/lang/Object;)Lscala/collection/immutable/IndexedSeq;, instantiatedMethodType=(Ljava/lang/Object;)Lscala/collection/immutable/IndexedSeq;, numCaptured=1])
- writeReplace data (class: java.lang.invoke.SerializedLambda)
- object (class $Lambda$2103/815179920, $Lambda$2103/815179920569b57c4)
```
For more background of the new and old ways Scala lowers closures to Java bytecode, please see [A note on how NSC (New Scala Compiler) lowers lambdas](https://gist.github.com/rednaxelafx/e9ecd09bbd1c448dbddad4f4edf25d48#file-notes-md).
For more background on how Spark's `ClosureCleaner` works and what's needed to make it support "indylambda" Scala closures, please refer to [A Note on Apache Spark's ClosureCleaner](https://gist.github.com/rednaxelafx/e9ecd09bbd1c448dbddad4f4edf25d48#file-spark_closurecleaner_notes-md).
#### tl;dr
The `ClosureCleaner` works like a mark-sweep algorithm on fields:
- Finding (a chain of) outer objects referenced by the starting closure;
- Scanning the starting closure and its inner closures and marking the fields on the outer objects accessed;
- Cloning the outer objects, nulling out fields that are not accessed by any closure of concern.
##### Outer Objects
For the old, inner class style Scala closures, the "outer objects" is defined as the lexically enclosing closures of the starting closure, plus an optional enclosing REPL line object if these closures are defined in a Scala REPL. All of them are on a singly-linked `$outer` chain.
For the new, "indylambda" style Scala closures, the capturing implementation changed, so closures no longer refer to their enclosing closures via an `$outer` chain. However, a closure can still capture its enclosing REPL line object, much like the old style closures. The name of the field that captures this reference would be `arg$1` (instead of `$outer`).
So what's missing in the `ClosureCleaner` for the "indylambda" support is find and potentially clone+clean the captured enclosing `this` REPL line object. That's what this PR implements.
##### Inner Closures
The old, inner class style of Scala closures are compiled into separate inner classes, one per lambda body. So in order to discover the implementation (bytecode) of the inner closures, one has to jump over multiple classes. The name of such a class would contain the marker substring `$anonfun$`.
The new, "indylambda" style Scala closures are compiled into **static methods** in the class where the lambdas were declared. So for lexically nested closures, their lambda bodies would all be compiled into static methods **in the same class**. This makes it much easier to discover the implementation (bytecode) of the nested lambda bodies. The name of such a static method would contain the marker substring `$anonfun$`.
Discovery of inner closures involves scanning bytecode for certain patterns that represent the creation of a closure object for the inner closure.
- For inner class style: the closure object creation site is like `new <InnerClassForTheClosure>(captured args)`
- For "indylambda" style: the closure object creation site would be compiled into an `invokedynamic` instruction, with its "bootstrap method" pointing to the same one used by Java 8 for its serializable lambdas, and with the bootstrap method arguments pointing to the implementation method.
### Does this PR introduce _any_ user-facing change?
Yes. Before this PR, Spark 2.4 / 3.0 / master on Scala 2.12 would not support Scala closures declared in a Scala REPL that captures anything from the REPL line objects. After this PR, such scenario is supported.
### How was this patch tested?
Added new unit test case to `org.apache.spark.repl.SingletonReplSuite`. The new test case fails without the fix in this PR, and pases with the fix.
Closes#28463 from rednaxelafx/closure-cleaner-indylambda.
Authored-by: Kris Mok <kris.mok@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR aims to add `spark_info` metric into `PrometheusResource`.
### Why are the changes needed?
This exposes Apache Spark version and revision like the following.
### Does this PR introduce _any_ user-facing change?
Yes, but it's exposed as an additional metric.
### How was this patch tested?
Manual.
```
$ bin/spark-shell --driver-memory 4G -c spark.ui.prometheus.enabled=true
$ curl -s http://localhost:4041/metrics/executors/prometheus/ | head -n1
spark_info{version="3.1.0", revision="097d5098cca987e5f7bbb8394783c01517ebed0f"} 1.0
```
Closes#28563 from dongjoon-hyun/SPARK-31743.
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 is kind of a follow up of SPARK-31631. In some cases, it only attempts once for ~35 seconds. Seems 10 seconds are not enough to try multiple times - took a quick look and seems difficult to manipulate the socket configuration as well.
It simply proposes to increase the time limit for now. It affects master and branch-3.0.
```
sbt.ForkMain$ForkError: org.scalatest.exceptions.TestFailedDueToTimeoutException: The code passed to eventually never returned normally. Attempted 1 times over 34.294744142999996 seconds. Last failure message: Address already in use.
at org.scalatest.concurrent.Eventually.tryTryAgain$1(Eventually.scala:432)
at org.scalatest.concurrent.Eventually.eventually(Eventually.scala:439)
at org.scalatest.concurrent.Eventually.eventually$(Eventually.scala:391)
at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:479)
at org.scalatest.concurrent.Eventually.eventually(Eventually.scala:308)
at org.scalatest.concurrent.Eventually.eventually$(Eventually.scala:307)
at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:479)
at org.apache.spark.deploy.security.HadoopDelegationTokenManagerSuite.$anonfun$new$4(HadoopDelegationTokenManagerSuite.scala:106)
at org.scalatest.OutcomeOf.outcomeOf(OutcomeOf.scala:85)
at org.scalatest.OutcomeOf.outcomeOf$(OutcomeOf.scala:83)
at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
at org.scalatest.Transformer.apply(Transformer.scala:22)
at org.scalatest.Transformer.apply(Transformer.scala:20)
at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:186)
at org.apache.spark.SparkFunSuite.withFixture(SparkFunSuite.scala:157)
at org.scalatest.FunSuiteLike.invokeWithFixture$1(FunSuiteLike.scala:184)
at org.scalatest.FunSuiteLike.$anonfun$runTest$1(FunSuiteLike.scala:196)
at org.scalatest.SuperEngine.runTestImpl(Engine.scala:286)
at org.scalatest.FunSuiteLike.runTest(FunSuiteLike.scala:196)
at org.scalatest.FunSuiteLike.runTest$(FunSuiteLike.scala:178)
at org.apache.spark.SparkFunSuite.org$scalatest$BeforeAndAfterEach$$super$runTest(SparkFunSuite.scala:59)
at org.scalatest.BeforeAndAfterEach.runTest(BeforeAndAfterEach.scala:221)
at org.scalatest.BeforeAndAfterEach.runTest$(BeforeAndAfterEach.scala:214)
at org.apache.spark.SparkFunSuite.runTest(SparkFunSuite.scala:59)
at org.scalatest.FunSuiteLike.$anonfun$runTests$1(FunSuiteLike.scala:229)
at org.scalatest.SuperEngine.$anonfun$runTestsInBranch$1(Engine.scala:393)
at scala.collection.immutable.List.foreach(List.scala:392)
at org.scalatest.SuperEngine.traverseSubNodes$1(Engine.scala:381)
at org.scalatest.SuperEngine.runTestsInBranch(Engine.scala:376)
at org.scalatest.SuperEngine.runTestsImpl(Engine.scala:458)
at org.scalatest.FunSuiteLike.runTests(FunSuiteLike.scala:229)
at org.scalatest.FunSuiteLike.runTests$(FunSuiteLike.scala:228)
at org.scalatest.FunSuite.runTests(FunSuite.scala:1560)
at org.scalatest.Suite.run(Suite.scala:1124)
at org.scalatest.Suite.run$(Suite.scala:1106)
at org.scalatest.FunSuite.org$scalatest$FunSuiteLike$$super$run(FunSuite.scala:1560)
at org.scalatest.FunSuiteLike.$anonfun$run$1(FunSuiteLike.scala:233)
at org.scalatest.SuperEngine.runImpl(Engine.scala:518)
at org.scalatest.FunSuiteLike.run(FunSuiteLike.scala:233)
at org.scalatest.FunSuiteLike.run$(FunSuiteLike.scala:232)
at org.apache.spark.SparkFunSuite.org$scalatest$BeforeAndAfterAll$$super$run(SparkFunSuite.scala:59)
at org.scalatest.BeforeAndAfterAll.liftedTree1$1(BeforeAndAfterAll.scala:213)
at org.scalatest.BeforeAndAfterAll.run(BeforeAndAfterAll.scala:210)
at org.scalatest.BeforeAndAfterAll.run$(BeforeAndAfterAll.scala:208)
at org.apache.spark.SparkFunSuite.run(SparkFunSuite.scala:59)
at org.scalatest.tools.Framework.org$scalatest$tools$Framework$$runSuite(Framework.scala:317)
at org.scalatest.tools.Framework$ScalaTestTask.execute(Framework.scala:510)
at sbt.ForkMain$Run$2.call(ForkMain.java:296)
at sbt.ForkMain$Run$2.call(ForkMain.java:286)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: sbt.ForkMain$ForkError: java.net.BindException: Address already in use
at sun.nio.ch.Net.bind0(Native Method)
at sun.nio.ch.Net.bind(Net.java:433)
at sun.nio.ch.Net.bind(Net.java:425)
at sun.nio.ch.ServerSocketChannelImpl.bind(ServerSocketChannelImpl.java:223)
at sun.nio.ch.ServerSocketAdaptor.bind(ServerSocketAdaptor.java:74)
at org.apache.mina.transport.socket.nio.NioSocketAcceptor.open(NioSocketAcceptor.java:198)
at org.apache.mina.transport.socket.nio.NioSocketAcceptor.open(NioSocketAcceptor.java:51)
at org.apache.mina.core.polling.AbstractPollingIoAcceptor.registerHandles(AbstractPollingIoAcceptor.java:547)
at org.apache.mina.core.polling.AbstractPollingIoAcceptor.access$400(AbstractPollingIoAcceptor.java:68)
at org.apache.mina.core.polling.AbstractPollingIoAcceptor$Acceptor.run(AbstractPollingIoAcceptor.java:422)
at org.apache.mina.util.NamePreservingRunnable.run(NamePreservingRunnable.java:64)
... 3 more
```
### Why are the changes needed?
To fix flakiness in the tests.
### Does this PR introduce _any_ user-facing change?
No, dev-only.
### How was this patch tested?
Jenkins will test it out.
Closes#28562 from HyukjinKwon/SPARK-31742.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
## What changes were proposed in this pull request?
a typo in logging. (just added `: `)
Closes#28505 from sungpeo/typo_fshistoryprovider.
Authored-by: Sungpeo Kook <elixir.kook@kakaocorp.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Set default time zone and locale in the default constructor of `SparkFunSuite`:
- Default time zone to `America/Los_Angeles`
- Default locale to `Locale.US`
### Why are the changes needed?
1. To deduplicate code by moving common time zone and locale settings to one place SparkFunSuite
2. To have the same default time zone and locale in all tests. This should prevent errors like https://github.com/apache/spark/pull/28538
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
by running all affected test suites
Closes#28548 from MaxGekk/timezone-settings-SparkFunSuite.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
It's quite annoying to be blocked by flaky tests in several PRs. This PR disables them. The tests come from 3 PRs I'm recently watching:
https://github.com/apache/spark/pull/28526https://github.com/apache/spark/pull/28463https://github.com/apache/spark/pull/28517
### Why are the changes needed?
To make PR builder more stable
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
N/A
Closes#28547 from cloud-fan/test.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
When reading/writing datetime values that before the rebase switch day, from/to Avro/Parquet files, fail by default and ask users to set a config to explicitly do rebase or not.
### Why are the changes needed?
Rebase or not rebase have different behaviors and we should let users decide it explicitly. In most cases, users won't hit this exception as it only affects ancient datetime values.
### Does this PR introduce _any_ user-facing change?
Yes, now users will see an error when reading/writing dates before 1582-10-15 or timestamps before 1900-01-01 from/to Parquet/Avro files, with an error message to ask setting a config.
### How was this patch tested?
updated tests
Closes#28477 from cloud-fan/rebase.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR caught the `NoSuchElementException` and enriched the error message for `AppStatusStore.applicationInfo()` when Spark is starting up and the application information is unavailable.
### Why are the changes needed?
During the initialization of `SparkContext`, it first starts the Web UI and then set up the `LiveListenerBus` thread for dispatching the `SparkListenerApplicationStart` event (which will trigger writing the requested `ApplicationInfo` to `InMemoryStore`). If the Web UI is accessed before this info's being written to `InMemoryStore`, the following `NoSuchElementException` will be thrown.
```
WARN org.eclipse.jetty.server.HttpChannel: /jobs/
java.util.NoSuchElementException
at java.util.Collections$EmptyIterator.next(Collections.java:4191)
at org.apache.spark.util.kvstore.InMemoryStore$InMemoryIterator.next(InMemoryStore.java:467)
at org.apache.spark.status.AppStatusStore.applicationInfo(AppStatusStore.scala:39)
at org.apache.spark.ui.jobs.AllJobsPage.render(AllJobsPage.scala:266)
at org.apache.spark.ui.WebUI.$anonfun$attachPage$1(WebUI.scala:89)
at org.apache.spark.ui.JettyUtils$$anon$1.doGet(JettyUtils.scala:80)
at javax.servlet.http.HttpServlet.service(HttpServlet.java:687)
at javax.servlet.http.HttpServlet.service(HttpServlet.java:790)
at org.eclipse.jetty.servlet.ServletHolder.handle(ServletHolder.java:873)
at org.eclipse.jetty.servlet.ServletHandler$CachedChain.doFilter(ServletHandler.java:1623)
at org.apache.spark.ui.HttpSecurityFilter.doFilter(HttpSecurityFilter.scala:95)
at org.eclipse.jetty.servlet.ServletHandler$CachedChain.doFilter(ServletHandler.java:1610)
at org.eclipse.jetty.servlet.ServletHandler.doHandle(ServletHandler.java:540)
at org.eclipse.jetty.server.handler.ScopedHandler.nextHandle(ScopedHandler.java:255)
at org.eclipse.jetty.server.handler.ContextHandler.doHandle(ContextHandler.java:1345)
at org.eclipse.jetty.server.handler.ScopedHandler.nextScope(ScopedHandler.java:203)
at org.eclipse.jetty.servlet.ServletHandler.doScope(ServletHandler.java:480)
at org.eclipse.jetty.server.handler.ScopedHandler.nextScope(ScopedHandler.java:201)
at org.eclipse.jetty.server.handler.ContextHandler.doScope(ContextHandler.java:1247)
at org.eclipse.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:144)
at org.eclipse.jetty.server.handler.gzip.GzipHandler.handle(GzipHandler.java:753)
at org.eclipse.jetty.server.handler.ContextHandlerCollection.handle(ContextHandlerCollection.java:220)
at org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:132)
at org.eclipse.jetty.server.Server.handle(Server.java:505)
at org.eclipse.jetty.server.HttpChannel.handle(HttpChannel.java:370)
at org.eclipse.jetty.server.HttpConnection.onFillable(HttpConnection.java:267)
at org.eclipse.jetty.io.AbstractConnection$ReadCallback.succeeded(AbstractConnection.java:305)
at org.eclipse.jetty.io.FillInterest.fillable(FillInterest.java:103)
at org.eclipse.jetty.io.ChannelEndPoint$2.run(ChannelEndPoint.java:117)
at org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:698)
at org.eclipse.jetty.util.thread.QueuedThreadPool$Runner.run(QueuedThreadPool.java:804)
at java.lang.Thread.run(Thread.java:748)
```
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manually tested.
This can be reproduced:
1. `./bin/spark-shell`
2. at the same time, open `http://localhost:4040/jobs/` in your browser with quickly refreshing.
Closes#28444 from xccui/SPARK-31632.
Authored-by: Xingcan Cui <xccui@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR changes HistoryServer to set Content-Type.
I noticed that we will get html as plain text when we access to wrong URLs which represent non-existence appId on HistoryServer.
```
<html>
<head>
<meta http-equiv="Content-type" content="text/html; charset=utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="/static/bootstrap.min.css" type="text/css"/><link rel="stylesheet" href="/static/vis-timeline-graph2d.min.css" type="text/css"/><link rel="stylesheet" href="/static/webui.css" type="text/css"/><link rel="stylesheet" href="/static/timeline-view.css" type="text/css"/><script src="/static/sorttable.js"></script><script src="/static/jquery-3.4.1.min.js"></script><script src="/static/vis-timeline-graph2d.min.js"></script><script src="/static/bootstrap.bundle.min.js"></script><script src="/static/initialize-tooltips.js"></script><script src="/static/table.js"></script><script src="/static/timeline-view.js"></script><script src="/static/log-view.js"></script><script src="/static/webui.js"></script><script>setUIRoot('')</script>
<link rel="shortcut icon" href="/static/spark-logo-77x50px-hd.png"></link>
<title>Not Found</title>
</head>
<body>
<div class="container-fluid">
<div class="row">
<div class="col-12">
<h3 style="vertical-align: middle; display: inline-block;">
<a style="text-decoration: none" href="/">
<img src="/static/spark-logo-77x50px-hd.png"/>
<span class="version" style="margin-right: 15px;">3.1.0-SNAPSHOT</span>
</a>
Not Found
</h3>
</div>
</div>
<div class="row">
<div class="col-12">
<div class="row">Application local-1589239 not found.</div>
</div>
</div>
</div>
</body>
</html>
```
The reason is Content-Type not set. I confirmed it with `curl -I http://localhost:18080/history/<wrong-appId>`
```
HTTP/1.1 404 Not Found
Date: Wed, 13 May 2020 06:59:29 GMT
Cache-Control: no-cache, no-store, must-revalidate
X-Frame-Options: SAMEORIGIN
X-XSS-Protection: 1; mode=block
X-Content-Type-Options: nosniff
Content-Length: 1778
Server: Jetty(9.4.18.v20190429)
```
### Why are the changes needed?
This is a bug.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
I added a test case for this issue.
Closes#28519 from sarutak/fix-content-type.
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 PR removes `bootstrap-tooltip.js` which is no longer used.
That script is replaced with `bootstrap.bundle.min.js` in SPARK-30654 ( #27370 ).
### Why are the changes needed?
For cleaning up repository..
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manually checked whether tooltips are shown in the UI and no error message shown in the debug console.
Closes#28515 from sarutak/remove-tooltipjs.
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 PR aims to update Prometheus-related output format to be consistent with DropWizard 4.1 result.
- Add `Number` metrics for gauges metrics.
- Add `type` labels.
### Why are the changes needed?
SPARK-29032 added Prometheus support. After that, SPARK-29674 upgraded DropWizard for JDK9+ support and this caused difference in output labels and number of keys for Guage metrics. The current status is different from Apache Spark 2.4.5. Since we cannot change DropWizard, this PR aims to be consistent in Apache Spark 3.0.0 only.
**DropWizard 3.x**
```
metrics_master_aliveWorkers_Value 1.0
```
**DropWizard 4.1**
```
metrics_master_aliveWorkers_Value{type="gauges",} 1.0
metrics_master_aliveWorkers_Number{type="gauges",} 1.0
```
### Does this PR introduce _any_ user-facing change?
Yes, but this is a new feature in 3.0.0.
### How was this patch tested?
Manually check the output like the following.
**JMXExporter Result**
```
$ curl -s http://localhost:8088/ | grep "^metrics_master" | sort
metrics_master_aliveWorkers_Number{type="gauges",} 1.0
metrics_master_aliveWorkers_Value{type="gauges",} 1.0
metrics_master_apps_Number{type="gauges",} 0.0
metrics_master_apps_Value{type="gauges",} 0.0
metrics_master_waitingApps_Number{type="gauges",} 0.0
metrics_master_waitingApps_Value{type="gauges",} 0.0
metrics_master_workers_Number{type="gauges",} 1.0
metrics_master_workers_Value{type="gauges",} 1.0
```
**This PR**
```
$ curl -s http://localhost:8080/metrics/master/prometheus/ | grep master
metrics_master_aliveWorkers_Number{type="gauges"} 1
metrics_master_aliveWorkers_Value{type="gauges"} 1
metrics_master_apps_Number{type="gauges"} 0
metrics_master_apps_Value{type="gauges"} 0
metrics_master_waitingApps_Number{type="gauges"} 0
metrics_master_waitingApps_Value{type="gauges"} 0
metrics_master_workers_Number{type="gauges"} 1
metrics_master_workers_Value{type="gauges"} 1
```
Closes#28510 from dongjoon-hyun/SPARK-31683.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: DB Tsai <d_tsai@apple.com>
### What changes were proposed in this pull request?
Fix application order for shutdown hooks for the priorities of Int.MaxValue, Int.MinValue
### Why are the changes needed?
The bug causes out-of-order execution of shutdown hooks if their priorities were Int.MinValue or Int.MaxValue
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added a test covering the change.
Closes#28494 from oleg-smith/SPARK-31456_shutdown_hook_priority.
Authored-by: oleg <oleg@nexla.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR aims to new Prometheus-format metric endpoints experimental in Apache Spark 3.0.0.
### Why are the changes needed?
Although the new metrics are disabled by default, we had better make it experimental explicitly in Apache Spark 3.0.0 since the output format is still not fixed. We can finalize it in Apache Spark 3.1.0.
### Does this PR introduce _any_ user-facing change?
Only doc-change is visible to the users.
### How was this patch tested?
Manually check the code since this is a documentation and class annotation change.
Closes#28495 from dongjoon-hyun/SPARK-31674.
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 added a workaround for the issue which occasionally happens when SparkContext#stop() is called.
I think this issue can occurs on macOS with OpenJDK / OracleJDK 1.8.
If this issue happens, following stack trace is shown.
```
20/05/03 02:17:54 WARN AbstractConnector:
java.io.IOException: No such file or directory
at sun.nio.ch.NativeThread.signal(Native Method)
at sun.nio.ch.ServerSocketChannelImpl.implCloseSelectableChannel(ServerSocketChannelImpl.java:292)
at java.nio.channels.spi.AbstractSelectableChannel.implCloseChannel(AbstractSelectableChannel.java:234)
at java.nio.channels.spi.AbstractInterruptibleChannel.close(AbstractInterruptibleChannel.java:115)
at org.eclipse.jetty.server.ServerConnector.close(ServerConnector.java:368)
at org.eclipse.jetty.server.AbstractNetworkConnector.shutdown(AbstractNetworkConnector.java:105)
at org.eclipse.jetty.server.Server.doStop(Server.java:439)
at org.eclipse.jetty.util.component.AbstractLifeCycle.stop(AbstractLifeCycle.java:89)
at org.apache.spark.ui.ServerInfo.stop(JettyUtils.scala:501)
at org.apache.spark.ui.WebUI.$anonfun$stop$2(WebUI.scala:173)
at org.apache.spark.ui.WebUI.$anonfun$stop$2$adapted(WebUI.scala:173)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.ui.WebUI.stop(WebUI.scala:173)
at org.apache.spark.ui.SparkUI.stop(SparkUI.scala:101)
at org.apache.spark.SparkContext.$anonfun$stop$6(SparkContext.scala:1966)
at org.apache.spark.SparkContext.$anonfun$stop$6$adapted(SparkContext.scala:1966)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.SparkContext.$anonfun$stop$5(SparkContext.scala:1966)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1357)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1966)
at org.apache.spark.repl.Main$.$anonfun$doMain$3(Main.scala:79)
at org.apache.spark.repl.Main$.$anonfun$doMain$3$adapted(Main.scala:79)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.repl.Main$.doMain(Main.scala:79)
at org.apache.spark.repl.Main$.main(Main.scala:58)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:934)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1013)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1022)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
```
This issue happens when the Jetty's acceptor thread shrinks before the main thread sends a signal to the thread.
Jetty's acceptor thread waits for a new connection request and blocked by `accept(this.fd, newfd, isaa)` in [`sun.nio.ch.ServerSocketChannelImpl#accept`](http://hg.openjdk.java.net/jdk8/jdk8/jdk/file/tip/src/share/classes/sun/nio/ch/ServerSocketChannelImpl.java#l241).
When `org.eclipse.jetty.server.Server.doStop` is called in the main thread, the thread reaches [this code](http://hg.openjdk.java.net/jdk8/jdk8/jdk/file/tip/src/share/classes/sun/nio/ch/ServerSocketChannelImpl.java#l280).
The server socket descriptor will be closed by `nd.preClose` in the main thread.
Then, `accept()` in acceptor thread throws an Exception due to "Bad file descriptor" in case of macOS.
After the exception is thrown, the acceptor thread will continue to [fetch a task](https://github.com/eclipse/jetty.project/blob/jetty-9.4.18.v20190429/jetty-util/src/main/java/org/eclipse/jetty/util/thread/QueuedThreadPool.java#L783).
If the thread obtain the `SHRINK` task [here](https://github.com/eclipse/jetty.project/blob/jetty-9.4.18.v20190429/jetty-util/src/main/java/org/eclipse/jetty/util/thread/QueuedThreadPool.java#L854), the thread will be shrink.
If, the acceptor thread finishes before `NativeThread.signal` is called in the main thread, this issue happens.
I have confirmed this issue happens even `jetty-9.4.28.v20200408`.
Because the stack trace is displayed by the [logger](https://github.com/eclipse/jetty.project/blob/jetty-9.4.18.v20190429/jetty-server/src/main/java/org/eclipse/jetty/server/ServerConnector.java#L372), it's difficult to suppress it.
According to [this condition](https://github.com/eclipse/jetty.project/blob/jetty-9.4.18.v20190429/jetty-util/src/main/java/org/eclipse/jetty/util/thread/QueuedThreadPool.java#L842), shrink doesn't happen if the idle time is 0. So this PR adds a workaround that set the idle time to 0 immediately before stop.
In case of Linux, the acceptor thread is still blocked by `accept` even though `np.preClose` is called in the main thread.
The acceptor thread will return from `accept` when `NativeThread.signal` is called in the main thread.
It seems that the implementation of `accept systemcall` called in `accept` is different between Linux and macOS.
So, I believe this issue doesn't happen on Linux.
Also, the implementation of `NativeThread.signal` is a little bit changed in [OpenJDK 9](http://hg.openjdk.java.net/jdk9/jdk9/jdk/rev/7b17bff2ea36) for macOS.
So this issue doesn't happen for macOS with OpenJDK 9+.
You can reproduce this issue by following instructions using debugger.
1. Launch spark-shell in local mode with JDWP enabled.
2. Access to WebUI. This is needed to increase the number of SparkUI thread to greater than minThreads to meet the condition of shrink.
3. Enable the following breakpoints. Note that don't suspend all threads when a thread reaches one of the breakpoints. Only the threads which reach the line should be suspended.
3.1 [long now = System.nanoTime(); at org.eclipse.jetty.util.thread.QueuedThreadPool#idleJobPoll](https://github.com/eclipse/jetty.project/blob/jetty-9.4.18.v20190429/jetty-util/src/main/java/org/eclipse/jetty/util/thread/QueuedThreadPool.java#L850)
3.2 [NativeThread.signal(th); at sun.nio.ch.ServerSocketChannelImpl#implCloseSelectableChannel](http://hg.openjdk.java.net/jdk8/jdk8/jdk/file/tip/src/share/classes/sun/nio/ch/ServerSocketChannelImpl.java#l283)
3.3 [thread = 0; at ServerSocketChannelImpl#accept](http://hg.openjdk.java.net/jdk8/jdk8/jdk/file/tip/src/share/classes/sun/nio/ch/ServerSocketChannelImpl.java#l247)
4. Quit spark-shell.
5. Waiting for a thread reaching the breakpoint `3.1` and until the following condition become true (The idle time of those threads are 1min and you can confirm it using the expression evaluation feature if your debugger supports ).
`(System.nanoTime() - last) > TimeUnit.MILLISECONDS.toNanos(_idleTimeout)`
6. The acceptor thread named `SparkUI-<N>-acceptor-0` should be suspended at the breakpoint `3.3` so continue this thread. This thread will reach the breakpoint at `3.1` and continue further. Then, the acceptor thread will be shrink.
7. Continue all the threads rest.
### Why are the changes needed?
This stack trace is not brought by Spark but it confuses users.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Tested by the reproduce procedure above and confirmed acceptor thread is no longer shrink.
Closes#28437 from sarutak/SPARK-30385.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Remove unused `registeredConnections` counter from `ExternalBlockHandler#ShuffleMetrics`
This was added by SPARK-25642 at 3.0.0
- 8dd29fe36b
### Why are the changes needed?
It's `registeredConnections` counter created in `TransportContext` that's really counting the numbers and it's misleading for people who want to add new metrics like `registeredConnections`.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Add UTs to ensure all expected metrics are registered for `ExternalShuffleService` and `YarnShuffleService`
Closes#28457 from manuzhang/spark-31611-pre.
Lead-authored-by: tianlzhang <tianlzhang@ebay.com>
Co-authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
The `Kafka*Suite`s are flaky because of the Hadoop MiniKdc issue - https://issues.apache.org/jira/browse/HADOOP-12656
> Looking at MiniKdc implementation, if port is 0, the constructor use ServerSocket to find an unused port, assign the port number to the member variable port and close the ServerSocket object; later, in initKDCServer(), instantiate a TcpTransport object and bind at that port.
> It appears that the port may be used in between, and then throw the exception.
Related test failures are suspected, such as https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/122225/testReport/org.apache.spark.sql.kafka010/KafkaDelegationTokenSuite/_It_is_not_a_test_it_is_a_sbt_testing_SuiteSelector_/
```scala
[info] org.apache.spark.sql.kafka010.KafkaDelegationTokenSuite *** ABORTED *** (15 seconds, 426 milliseconds)
[info] java.net.BindException: Address already in use
[info] at sun.nio.ch.Net.bind0(Native Method)
[info] at sun.nio.ch.Net.bind(Net.java:433)
[info] at sun.nio.ch.Net.bind(Net.java:425)
[info] at sun.nio.ch.ServerSocketChannelImpl.bind(ServerSocketChannelImpl.java:223)
[info] at sun.nio.ch.ServerSocketAdaptor.bind(ServerSocketAdaptor.java:74)
[info] at org.apache.mina.transport.socket.nio.NioSocketAcceptor.open(NioSocketAcceptor.java:198)
[info] at org.apache.mina.transport.socket.nio.NioSocketAcceptor.open(NioSocketAcceptor.java:51)
[info] at org.apache.mina.core.polling.AbstractPollingIoAcceptor.registerHandles(AbstractPollingIoAcceptor.java:547)
[info] at org.apache.mina.core.polling.AbstractPollingIoAcceptor.access$400(AbstractPollingIoAcceptor.java:68)
[info] at org.apache.mina.core.polling.AbstractPollingIoAcceptor$Acceptor.run(AbstractPollingIoAcceptor.java:422)
[info] at org.apache.mina.util.NamePreservingRunnable.run(NamePreservingRunnable.java:64)
[info] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
[info] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
[info] at java.lang.Thread.run(Thread.java:748)
```
After comparing the error stack trace with similar issues reported in different projects, such as
https://issues.apache.org/jira/browse/KAFKA-3453https://issues.apache.org/jira/browse/HBASE-14734
We can be sure that they are caused by the same problem issued in HADOOP-12656.
In the PR, We apply the approach from HBASE first before we finally drop Hadoop 2.7.x
### Why are the changes needed?
fix test flakiness
### Does this PR introduce _any_ user-facing change?
NO
### How was this patch tested?
the test itself passing Jenkins
Closes#28442 from yaooqinn/SPARK-31631.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
### What changes were proposed in this pull request?
1, add new param `blockSize`;
2, add a new class InstanceBlock;
3, **if `blockSize==1`, keep original behavior; if `blockSize>1`, stack input vectors to blocks (like ALS/MLP);**
4, if `blockSize>1`, standardize the input outside of optimization procedure;
### Why are the changes needed?
1, reduce RAM to persist traing dataset; (save about 40% RAM)
2, use Level-2 BLAS routines; (4x ~ 5x faster on dataset `epsilon`)
### Does this PR introduce any user-facing change?
Yes, a new param is added
### How was this patch tested?
existing and added testsuites
Closes#28349 from zhengruifeng/blockify_svc_II.
Authored-by: zhengruifeng <ruifengz@foxmail.com>
Signed-off-by: zhengruifeng <ruifengz@foxmail.com>
### What changes were proposed in this pull request?
Make sure the task has nearly reached `context.barrier()` before killing.
### Why are the changes needed?
In case of the task is killed before it reaches `context.barrier()`, the task will not create the expected file.
```
Error Message
org.scalatest.exceptions.TestFailedException: new java.io.File(dir, killedFlagFile).exists() was false Expect barrier task being killed.
Stacktrace
sbt.ForkMain$ForkError: org.scalatest.exceptions.TestFailedException: new java.io.File(dir, killedFlagFile).exists() was false Expect barrier task being killed.
at org.scalatest.Assertions.newAssertionFailedException(Assertions.scala:530)
at org.scalatest.Assertions.newAssertionFailedException$(Assertions.scala:529)
at org.scalatest.FunSuite.newAssertionFailedException(FunSuite.scala:1560)
at org.scalatest.Assertions$AssertionsHelper.macroAssert(Assertions.scala:503)
at org.apache.spark.scheduler.BarrierTaskContextSuite.$anonfun$testBarrierTaskKilled$1(BarrierTaskContextSuite.scala:266)
at org.apache.spark.scheduler.BarrierTaskContextSuite.$anonfun$testBarrierTaskKilled$1$adapted(BarrierTaskContextSuite.scala:226)
at org.apache.spark.SparkFunSuite.withTempDir(SparkFunSuite.scala:163)
at org.apache.spark.scheduler.BarrierTaskContextSuite.testBarrierTaskKilled(BarrierTaskContextSuite.scala:226)
at org.apache.spark.scheduler.BarrierTaskContextSuite.$anonfun$new$29(BarrierTaskContextSuite.scala:277)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
```
[Here's](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/122273/testReport/org.apache.spark.scheduler/BarrierTaskContextSuite/barrier_task_killed__interrupt/) the full error messages.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
Closes#28454 from Ngone51/fix_kill_interrupt.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Fixing an issue where Spark Master UI Fails to load if the application is waiting for workers to launch driver.
**Root Cause:**
This is happening due to the fact that the submitted application is waiting for a worker to be free to run the driver. Due to this resource is set to null in the formatResourcesAddresses method and this is running into null pointer exception.
**Fix:**
Added a null check before forming a resource address and display "None" if the driver isn't launched yet.
### Why are the changes needed?
Spark Master UI should load as expected when applications are waiting for workers to run driver.
### Does this PR introduce _any_ user-facing change?
The worker column in Spark Master UI will show "None" if the driver hasn't been launched yet.
### How was this patch tested?
Tested on a local setup. Launched 2 applications and ensured that Spark Master UI loads fine.
Closes#28429 from akshatb1/MasterUIBug.
Authored-by: Akshat Bordia <akshat.bordia31@gmail.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
This PR aims to remove `for testing` from `CleanerListener` class description to promote this private class more clearly.
### Why are the changes needed?
After SPARK-27963 (Allow dynamic allocation without a shuffle service), `CleanerListener` is used in `ExecutorMonitor` during dynamic allocation. Specifically, `CleanerListener.shuffleCleaned` is used.
- https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/scheduler/dynalloc/ExecutorMonitor.scala#L385-L392
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
This is a private doc-only change.
Closes#28452 from dongjoon-hyun/SPARK-MINOR.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Allow customized timeouts for `runSparkSubmit`, which will make flaky tests more likely to pass by using a larger timeout value.
I was able to reproduce the test failure on my laptop, which took 1.5 - 2 minutes to finish the test. After increasing the timeout, the test now can pass locally.
### Why are the changes needed?
This allows slow tests to use a larger timeout, so they are more likely to succeed.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
The test was able to pass on my local env after the change.
Closes#28438 from tianshizz/SPARK-31267.
Authored-by: Tianshi Zhu <zhutianshirea@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
The "spark.dynamicAllocation.shuffleTimeout" configuration only takes effect if "spark.dynamicAllocation.shuffleTracking.enabled" is true, so we should re-namespace that configuration so that it's nested under the "shuffleTracking" one.
### How was this patch tested?
Covered by current existing test cases.
Closes#28426 from jiangxb1987/confName.
Authored-by: Xingbo Jiang <xingbo.jiang@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
I add a new API in pyspark RDD class:
def collectWithJobGroup(self, groupId, description, interruptOnCancel=False)
This API do the same thing with `rdd.collect`, but it can specify the job group when do collect.
The purpose of adding this API is, if we use:
```
sc.setJobGroup("group-id...")
rdd.collect()
```
The `setJobGroup` API in pyspark won't work correctly. This related to a bug discussed in
https://issues.apache.org/jira/browse/SPARK-31549
Note:
This PR is a rather temporary workaround for `PYSPARK_PIN_THREAD`, and as a step to migrate to `PYSPARK_PIN_THREAD` smoothly. It targets Spark 3.0.
- `PYSPARK_PIN_THREAD` is unstable at this moment that affects whole PySpark applications.
- It is impossible to make it runtime configuration as it has to be set before JVM is launched.
- There is a thread leak issue between Python and JVM. We should address but it's not a release blocker for Spark 3.0 since the feature is experimental. I plan to handle this after Spark 3.0 due to stability.
Once `PYSPARK_PIN_THREAD` is enabled by default, we should remove this API out ideally. I will target to deprecate this API in Spark 3.1.
### Why are the changes needed?
Fix bug.
### Does this PR introduce any user-facing change?
A develop API in pyspark: `pyspark.RDD. collectWithJobGroup`
### How was this patch tested?
Unit test.
Closes#28395 from WeichenXu123/collect_with_job_group.
Authored-by: Weichen Xu <weichen.xu@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Fix the wrong fetch size.
### Why are the changes needed?
The fetch size should be the sum of the size of merged block and the total size of those merging blocks. But we missed the size of merged block.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Added a regression test.
Closes#28301 from Ngone51/fix_merged_block_size.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
After changes in SPARK-20628, CoarseGrainedSchedulerBackend can decommission an executor and stop assigning new tasks on it. We should also decommission the corresponding blockmanagers in the same way. i.e. Move the cached RDD blocks from those executors to other active executors.
### Why are the changes needed?
We need to gracefully decommission the block managers so that the underlying RDD cache blocks are not lost in case the executors are taken away forcefully after some timeout (because of spotloss/pre-emptible VM etc). Its good to save as much cache data as possible.
Also In future once the decommissioning signal comes from Cluster Manager (say YARN/Mesos etc), dynamic allocation + this change gives us opportunity to downscale the executors faster by making the executors free of cache data.
Note that this is a best effort approach. We try to move cache blocks from decommissioning executors to active executors. If the active executors don't have free resources available on them for caching, then the decommissioning executors will keep the cache block which it was not able to move and it will still be able to serve them.
Current overall Flow:
1. CoarseGrainedSchedulerBackend receives a signal to decommissionExecutor. On receiving the signal, it do 2 things - Stop assigning new tasks (SPARK-20628), Send another message to BlockManagerMasterEndpoint (via BlockManagerMaster) to decommission the corresponding BlockManager.
2. BlockManagerMasterEndpoint receives "DecommissionBlockManagers" message. On receiving this, it moves the corresponding block managers to "decommissioning" state. All decommissioning BMs are excluded from the getPeers RPC call which is used for replication. All these decommissioning BMs are also sent message from BlockManagerMasterEndpoint to start decommissioning process on themselves.
3. BlockManager on worker (say BM-x) receives the "DecommissionBlockManager" message. Now it will start BlockManagerDecommissionManager thread to offload all the RDD cached blocks. This thread can make multiple reattempts to decommission the existing cache blocks (multiple reattempts might be needed as there might not be sufficient space in other active BMs initially).
### Does this PR introduce any user-facing change?
NO
### How was this patch tested?
Added UTs.
Closes#27864 from prakharjain09/SPARK-20732-rddcache-1.
Authored-by: Prakhar Jain <prakharjain09@gmail.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
Use `dagScheduler.taskSetFailed` to abort a barrier stage instead of throwing exception within `resourceOffers`.
### Why are the changes needed?
Any non fatal exception thrown within Spark RPC framework can be swallowed:
100fc58da5/core/src/main/scala/org/apache/spark/rpc/netty/Inbox.scala (L202-L211)
The method `TaskSchedulerImpl.resourceOffers` is also within the scope of Spark RPC framework. Thus, throw exception inside `resourceOffers` won't fail the application.
As a result, if a barrier stage fail the require check at `require(addressesWithDescs.size == taskSet.numTasks, ...)`, the barrier stage will fail the check again and again util all tasks from `TaskSetManager` dequeued. But since the barrier stage isn't really executed, the application will hang.
The issue can be reproduced by the following test:
```scala
initLocalClusterSparkContext(2)
val rdd0 = sc.parallelize(Seq(0, 1, 2, 3), 2)
val dep = new OneToOneDependency[Int](rdd0)
val rdd = new MyRDD(sc, 2, List(dep), Seq(Seq("executor_h_0"),Seq("executor_h_0")))
rdd.barrier().mapPartitions { iter =>
BarrierTaskContext.get().barrier()
iter
}.collect()
```
### Does this PR introduce any user-facing change?
Yes, application hang previously but fail-fast after this fix.
### How was this patch tested?
Added a regression test.
Closes#28257 from Ngone51/fix_barrier_abort.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This exposes the `filterByRange` method from `OrderedRDDFunctions` in the Java API (as a method of JavaPairRDD).
This is the only method of `OrderedRDDFunctions` which is not exposed in the Java API so far.
### Why are the changes needed?
This improves the consistency between the Scala and Java APIs. Calling the Scala method manually from a Java context is cumbersome as it requires passing many ClassTags.
### Does this PR introduce any user-facing change?
Yes, a new method in the Java API.
### How was this patch tested?
With unit tests. The implementation of the Scala method is already tested independently and it was not touched in this PR.
Suggesting srowen as a reviewer.
Closes#28293 from wetneb/SPARK-31518.
Authored-by: Antonin Delpeuch <antonin@delpeuch.eu>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
As part of the Stage level scheduling features, add the Python api's to set resource profiles.
This also adds the functionality to properly apply the pyspark memory configuration when specified in the ResourceProfile. The pyspark memory configuration is being passed in the task local properties. This was an easy way to get it to the PythonRunner that needs it. I modeled this off how the barrier task scheduling is passing the addresses. As part of this I added in the JavaRDD api's because those are needed by python.
### Why are the changes needed?
python api for this feature
### Does this PR introduce any user-facing change?
Yes adds the java and python apis for user to specify a ResourceProfile to use stage level scheduling.
### How was this patch tested?
unit tests and manually tested on yarn. Tests also run to verify it errors properly on standalone and local mode where its not yet supported.
Closes#28085 from tgravescs/SPARK-29641-pr-base.
Lead-authored-by: Thomas Graves <tgraves@nvidia.com>
Co-authored-by: Thomas Graves <tgraves@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Remove the requirement to launch a task in order to reset locality wait timer.
### Why are the changes needed?
Recently https://github.com/apache/spark/pull/27207 was merged, but contained a bug which leads to undesirable behavior.
The crux of the issue is that single resource offers couldn't reset the timer, if there had been a previous reject followed by an allResourceOffer with no available resources.
This lead to a problem where once locality level reached ANY, single resource offers are all accepted, leading allResourceOffers to be left with no resources to utilize (hence no task being launched on an all resource offer -> no timer reset). The task manager would be stuck in ANY locality level.
Noting down here the downsides of using below reset conditions, in case we want to follow up.
As this is quite complex, I could easily be missing something, so please comment/respond if you have more bad behavior scenarios or find something wrong here:
The format is:
> **Reset condition**
> - the unwanted side effect
> - the cause/use case
Below references to locality increase/decrease mean:
```
PROCESS_LOCAL, NODE_LOCAL ... .. ANY
------ locality decrease --->
<----- locality increase -----
```
**Task launch:**
- locality decrease:
- Blacklisting, FAIR/FIFO scheduling, or task resource requirements can minimize tasks launched
- locality increase:
- single task launch decreases locality despite many tasks remaining
**No delay schedule reject since last allFreeResource offer**
- locality decrease:
- locality wait less than allFreeResource offer frequency, which occurs at least 1 per second
- locality increase:
- single resource (or none) not rejected despite many tasks remaining (other lower priority tasks utilizing resources)
**Current impl - No delay schedule reject since last (allFreeResource offer + task launch)**
- locality decrease:
- all from above
- locality increase:
- single resource accepted and task launched despite many tasks remaining
The current impl is an improvement on the legacy (task launch) in that unintended locality decrease case is similar and the unintended locality increase case only occurs when the cluster is fully utilized.
For the locality increase cases, perhaps a config which specifies a certain % of tasks in a taskset to finish before resetting locality levels would be helpful.
**If** that was considered a good approach then perhaps removing the task launch as a requirement would eliminate most of downsides listed above.
Lemme know if you have more ideas for eliminating locality increase downside of **No delay schedule reject since last allFreeResource offer**
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
TaskSchedulerImplSuite
Also manually tested similar to how I tested in https://github.com/apache/spark/pull/27207 using [this simple app](https://github.com/bmarcott/spark-test-apps/blob/master/src/main/scala/TestLocalityWait.scala).
With the new changes, given locality wait of 10s the behavior is generally:
10 seconds of locality being respected, followed by a single full utilization of resources using ANY locality level, followed by 10 seconds of locality being respected, and so on
If the legacy flag is enabled (spark.locality.wait.legacyResetOnTaskLaunch=true), the behavior is only scheduling PROCESS_LOCAL tasks (only utilizing a single executor)
cloud-fan
tgravescs
Closes#28188 from bmarcott/nmarcott-locality-fix.
Authored-by: Nicholas Marcott <481161+bmarcott@users.noreply.github.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
As suggested by https://github.com/apache/spark/pull/28255#discussion_r412619438, this patch proposes to use taskAttemptId in checkpoint filename, instead of stageAttemptNumber + attemptNumber.
### Why are the changes needed?
To simplify checkpoint simplified and unique.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Existing tests.
Closes#28289 from viirya/SPARK-31484-followup.
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 increases the thread safety of the `BytesToBytesMap`:
- It makes the `iterator()` and `destructiveIterator()` methods used their own `Location` object. This used to be shared, and this was causing issues when the map was being iterated over in two threads by two different iterators.
- Removes the `safeIterator()` function. This is not needed anymore.
- Improves the documentation of a couple of methods w.r.t. thread-safety.
### Why are the changes needed?
It is unexpected an iterator shares the object it is returning with all other iterators. This is a violation of the iterator contract, and it causes issues with iterators over a map that are consumed in different threads.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Existing tests.
Closes#28286 from hvanhovell/SPARK-31511.
Authored-by: herman <herman@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
askAbortable method throw TimeoutException while it does no complete in time. Currently, the error message contains null as remoteAddr when receiver is in client mode.
This change is to print out correct rpcAddress instead of null in the error message.
### Why are the changes needed?
It provides the address of an endpoint which does not reply in time. It helps users to find slow executors when timeout happens.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Add a unit test.
Closes#28002 from Huang-yi-3456/SPARK-31233-enhance-rpctimeoutexception-log.
Authored-by: Huang-Yi <huang.yi.3456@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Rewrite the periodically check logic of `abortableRpcFuture` to make sure that barrier task would always return either desired messages or expected exception.
This PR also simplify a bit around `AbortableRpcFuture`.
### Why are the changes needed?
Currently, the periodically check logic of `abortableRpcFuture` is done by following:
```scala
...
var messages: Array[String] = null
while (!abortableRpcFuture.toFuture.isCompleted) {
messages = ThreadUtils.awaitResult(abortableRpcFuture.toFuture, 1.second)
...
}
return messages
```
It's possible that `abortableRpcFuture` complete before next invocation on `messages = ...`. In this case, the task may return null messages or execute successfully while it should throw exception(e.g. `SparkException` from `BarrierCoordinator`).
And here's a flaky test which caused by this bug:
```
[info] BarrierTaskContextSuite:
[info] - share messages with allGather() call *** FAILED *** (18 seconds, 705 milliseconds)
[info] org.apache.spark.SparkException: Job aborted due to stage failure: Could not recover from a failed barrier ResultStage. Most recent failure reason: Stage failed because barrier task ResultTask(0, 2) finished unsuccessfully.
[info] java.lang.NullPointerException
[info] at scala.collection.mutable.ArrayOps$ofRef$.length$extension(ArrayOps.scala:204)
[info] at scala.collection.mutable.ArrayOps$ofRef.length(ArrayOps.scala:204)
[info] at scala.collection.IndexedSeqOptimized.toList(IndexedSeqOptimized.scala:285)
[info] at scala.collection.IndexedSeqOptimized.toList$(IndexedSeqOptimized.scala:284)
[info] at scala.collection.mutable.ArrayOps$ofRef.toList(ArrayOps.scala:198)
[info] at org.apache.spark.scheduler.BarrierTaskContextSuite.$anonfun$new$4(BarrierTaskContextSuite.scala:68)
...
```
The test exception can be reproduced by changing the line `messages = ...` to the following:
```scala
messages = ThreadUtils.awaitResult(abortableRpcFuture.toFuture, 10.micros)
Thread.sleep(5000)
```
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Manually test and update some unit tests.
Closes#28245 from Ngone51/fix_barrier.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
`spark.driver.cores` configuration is used to set the amount of parallelism in kubernetes cluster mode drivers. Previously the amount of parallelism in the drivers were the number of cores in the host when running on JDK 8u120 or older, or the maximum of driver containers resource requests and limits when running on [JDK 8u121 or newer](https://bugs.openjdk.java.net/browse/JDK-8173345). This will enable users to specify `spark.driver.cores` to set parallelism, and specify `spark.kubernetes.driver.requests.cores` to limit the resource requests of the driver container, effectively decoupling the two
### Why are the changes needed?
Drivers submitted in kubernetes cluster mode set the parallelism of various components like `RpcEnv`, `MemoryManager`, `BlockManager` from inferring the number of available cores by calling `Runtime.getRuntime().availableProcessors()`. By using this, spark applications running on JDK 8u120 or older incorrectly get the total number of cores in the host, [ignoring the cgroup limits set by kubernetes](https://bugs.openjdk.java.net/browse/JDK-6515172). JDK 8u121 and newer runtimes do not have this problem.
Orthogonal to this, it is currently not possible to decouple resource limits on the driver container with the amount of parallelism of the various network and memory components listed above.
### Does this PR introduce any user-facing change?
Yes. Previously the amount of parallelism in kubernetes cluster mode submitted drivers were the number of cores in the host when running on JDK 8u120 or older, or the maximum of driver containers resource requests and limits when running on JDK 8u121 or newer. Now the value of `spark.driver.cores` is used.
### How was this patch tested?
happy to add tests if my proposal looks reasonable
Closes#27695 from onursatici/os/decouple-requests-and-parallelism.
Authored-by: Onur Satici <onursatici@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
