## What changes were proposed in this pull request?
Currently the update interval for the console progress bar is hardcoded. This PR makes it configurable for users.
## How was this patch tested?
Ran a long running job and with a high value of update interval, the updates were shown less frequently.
Author: Tejas Patil <tejasp@fb.com>
Closes#14507 from tejasapatil/SPARK-16919.
As per the postgreSQL JDBC driver [implementation](ab2a6d8908/pgjdbc/src/main/java/org/postgresql/PGProperty.java (L99)), the default record fetch size is 0(which means, it caches all record)
This fix enforces default record fetch size as 10 to enable streaming of data.
Author: Prince J Wesley <princejohnwesley@gmail.com>
Closes#14502 from princejwesley/spark-postgres.
## What changes were proposed in this pull request?
This patch fixes a bug in Spark's standalone Master which could cause applications to hang if tasks cause executors to exit with zero exit codes.
As an example of the bug, run
```
sc.parallelize(1 to 1, 1).foreachPartition { _ => System.exit(0) }
```
on a standalone cluster which has a single Spark application. This will cause all executors to die but those executors won't be replaced unless another Spark application or worker joins or leaves the cluster (or if an executor exits with a non-zero exit code). This behavior is caused by a bug in how the Master handles the `ExecutorStateChanged` event: the current implementation calls `schedule()` only if the executor exited with a non-zero exit code, so a task which causes a JVM to unexpectedly exit "cleanly" will skip the `schedule()` call.
This patch addresses this by modifying the `ExecutorStateChanged` to always unconditionally call `schedule()`. This should be safe because it should always be safe to call `schedule()`; adding extra `schedule()` calls can only affect performance and should not introduce correctness bugs.
## How was this patch tested?
I added a regression test in `DistributedSuite`.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#14510 from JoshRosen/SPARK-16925.
## What changes were proposed in this pull request?
Mask `spark.authenticate.secret` on Spark environment page (Web UI).
This is addition to https://github.com/apache/spark/pull/14409
## How was this patch tested?
`./dev/run-tests`
[info] ScalaTest
[info] Run completed in 1 hour, 8 minutes, 38 seconds.
[info] Total number of tests run: 2166
[info] Suites: completed 65, aborted 0
[info] Tests: succeeded 2166, failed 0, canceled 0, ignored 590, pending 0
[info] All tests passed.
Author: Artur Sukhenko <artur.sukhenko@gmail.com>
Closes#14484 from Devian-ua/SPARK-16796.
## What changes were proposed in this pull request?
As reported by Bryan Cutler on the mailing list, AccumulatorV2 does not have a += method, yet the documentation still references it.
## How was this patch tested?
N/A
Author: petermaxlee <petermaxlee@gmail.com>
Closes#14466 from petermaxlee/accumulator.
## What changes were proposed in this pull request?
Add the missing args-checking for randomSplit and sample
## How was this patch tested?
unit tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#14478 from zhengruifeng/fix_randomSplit.
## What changes were proposed in this pull request?
SpillReader NPE when spillFile has no data. See follow logs:
16/07/31 20:54:04 INFO collection.ExternalSorter: spill memory to file:/data4/yarnenv/local/usercache/tesla/appcache/application_1465785263942_56138/blockmgr-db5f46c3-d7a4-4f93-8b77-565e469696fb/09/temp_shuffle_ec3ece08-4569-4197-893a-4a5dfcbbf9fa, fileSize:0.0 B
16/07/31 20:54:04 WARN memory.TaskMemoryManager: leak 164.3 MB memory from org.apache.spark.util.collection.ExternalSorter3db4b52d
16/07/31 20:54:04 ERROR executor.Executor: Managed memory leak detected; size = 190458101 bytes, TID = 2358516/07/31 20:54:04 ERROR executor.Executor: Exception in task 1013.0 in stage 18.0 (TID 23585)
java.lang.NullPointerException
at org.apache.spark.util.collection.ExternalSorter$SpillReader.cleanup(ExternalSorter.scala:624)
at org.apache.spark.util.collection.ExternalSorter$SpillReader.nextBatchStream(ExternalSorter.scala:539)
at org.apache.spark.util.collection.ExternalSorter$SpillReader.<init>(ExternalSorter.scala:507)
at org.apache.spark.util.collection.ExternalSorter$SpillableIterator.spill(ExternalSorter.scala:816)
at org.apache.spark.util.collection.ExternalSorter.forceSpill(ExternalSorter.scala:251)
at org.apache.spark.util.collection.Spillable.spill(Spillable.scala:109)
at org.apache.spark.memory.TaskMemoryManager.acquireExecutionMemory(TaskMemoryManager.java:154)
at org.apache.spark.memory.TaskMemoryManager.allocatePage(TaskMemoryManager.java:249)
at org.apache.spark.memory.MemoryConsumer.allocatePage(MemoryConsumer.java:112)
at org.apache.spark.shuffle.sort.ShuffleExternalSorter.acquireNewPageIfNecessary(ShuffleExternalSorter.java:346)
at org.apache.spark.shuffle.sort.ShuffleExternalSorter.insertRecord(ShuffleExternalSorter.java:367)
at org.apache.spark.shuffle.sort.UnsafeShuffleWriter.insertRecordIntoSorter(UnsafeShuffleWriter.java:237)
at org.apache.spark.shuffle.sort.UnsafeShuffleWriter.write(UnsafeShuffleWriter.java:164)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
16/07/31 20:54:30 INFO executor.Executor: Executor is trying to kill task 1090.1 in stage 18.0 (TID 23793)
16/07/31 20:54:30 INFO executor.CoarseGrainedExecutorBackend: Driver commanded a shutdown
## How was this patch tested?
Manual test.
Author: sharkd <sharkd.tu@gmail.com>
Author: sharkdtu <sharkdtu@tencent.com>
Closes#14479 from sharkdtu/master.
## What changes were proposed in this pull request?
Mask spark.ssl.keyPassword, spark.ssl.keyStorePassword, spark.ssl.trustStorePassword in Web UI environment page.
(Changes their values to ***** in env. page)
## How was this patch tested?
I've built spark, run spark shell and checked that this values have been masked with *****.
Also run tests:
./dev/run-tests
[info] ScalaTest
[info] Run completed in 1 hour, 9 minutes, 5 seconds.
[info] Total number of tests run: 2166
[info] Suites: completed 65, aborted 0
[info] Tests: succeeded 2166, failed 0, canceled 0, ignored 590, pending 0
[info] All tests passed.
Author: Artur Sukhenko <artur.sukhenko@gmail.com>
Closes#14409 from Devian-ua/maskpass.
## What changes were proposed in this pull request?
The behavior of `SparkContext.addFile()` changed slightly with the introduction of the Netty-RPC-based file server, which was introduced in Spark 1.6 (where it was disabled by default) and became the default / only file server in Spark 2.0.0.
Prior to 2.0, calling `SparkContext.addFile()` with files that have the same name and identical contents would succeed. This behavior was never explicitly documented but Spark has behaved this way since very early 1.x versions.
In 2.0 (or 1.6 with the Netty file server enabled), the second `addFile()` call will fail with a requirement error because NettyStreamManager tries to guard against duplicate file registration.
This problem also affects `addJar()` in a more subtle way: the `fileServer.addJar()` call will also fail with an exception but that exception is logged and ignored; I believe that the problematic exception-catching path was mistakenly copied from some old code which was only relevant to very old versions of Spark and YARN mode.
I believe that this change of behavior was unintentional, so this patch weakens the `require` check so that adding the same filename at the same path will succeed.
At file download time, Spark tasks will fail with exceptions if an executor already has a local copy of a file and that file's contents do not match the contents of the file being downloaded / added. As a result, it's important that we prevent files with the same name and different contents from being served because allowing that can effectively brick an executor by preventing it from successfully launching any new tasks. Before this patch's change, this was prevented by forbidding `addFile()` from being called twice on files with the same name. Because Spark does not defensively copy local files that are passed to `addFile` it is vulnerable to files' contents changing, so I think it's okay to rely on an implicit assumption that these files are intended to be immutable (since if they _are_ mutable then this can lead to either explicit task failures or implicit incorrectness (in case new executors silently get newer copies of the file while old executors continue to use an older version)). To guard against this, I have decided to only update the file addition timestamps on the first call to `addFile()`; duplicate calls will succeed but will not update the timestamp. This behavior is fine as long as we assume files are immutable, which seems reasonable given the behaviors described above.
As part of this change, I also improved the thread-safety of the `addedJars` and `addedFiles` maps; this is important because these maps may be concurrently read by a task launching thread and written by a driver thread in case the user's driver code is multi-threaded.
## How was this patch tested?
I added regression tests in `SparkContextSuite`.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#14396 from JoshRosen/SPARK-16787.
## What changes were proposed in this pull request?
Casting ConcurrentHashMap to ConcurrentMap allows to run code compiled with Java 8 on Java 7
## How was this patch tested?
Compilation. Existing automatic tests
Author: Maciej Brynski <maciej.brynski@adpilot.pl>
Closes#14459 from maver1ck/spark-15541-master.
## What changes were proposed in this pull request?
Use foreach/for instead of map where operation requires execution of body, not actually defining a transformation
## How was this patch tested?
Jenkins
Author: Sean Owen <sowen@cloudera.com>
Closes#14332 from srowen/SPARK-16694.
## What changes were proposed in this pull request?
New config var: spark.mesos.docker.containerizer={"mesos","docker" (default)}
This adds support for running docker containers via the Mesos unified containerizer: http://mesos.apache.org/documentation/latest/container-image/
The benefit is losing the dependency on `dockerd`, and all the costs which it incurs.
I've also updated the supported Mesos version to 0.28.2 for support of the required protobufs.
This is blocked on: https://github.com/apache/spark/pull/14167
## How was this patch tested?
- manually testing jobs submitted with both "mesos" and "docker" settings for the new config var.
- spark/mesos integration test suite
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#14275 from mgummelt/unified-containerizer.
## What changes were proposed in this pull request?
Adding a new property to SparkConf called spark.metrics.namespace that allows users to
set a custom namespace for executor and driver metrics in the metrics systems.
By default, the root namespace used for driver or executor metrics is
the value of `spark.app.id`. However, often times, users want to be able to track the metrics
across apps for driver and executor metrics, which is hard to do with application ID
(i.e. `spark.app.id`) since it changes with every invocation of the app. For such use cases,
users can set the `spark.metrics.namespace` property to another spark configuration key like
`spark.app.name` which is then used to populate the root namespace of the metrics system
(with the app name in our example). `spark.metrics.namespace` property can be set to any
arbitrary spark property key, whose value would be used to set the root namespace of the
metrics system. Non driver and executor metrics are never prefixed with `spark.app.id`, nor
does the `spark.metrics.namespace` property have any such affect on such metrics.
## How was this patch tested?
Added new unit tests, modified existing unit tests.
Author: Mark Grover <mark@apache.org>
Closes#14270 from markgrover/spark-5847.
## What changes were proposed in this pull request?
This change adds a new configuration entry to specify the size of the spark listener bus event queue. The value for this config ("spark.scheduler.listenerbus.eventqueue.size") is set to a default to 10000.
Note:
I haven't currently documented the configuration entry. We can decide whether it would be appropriate to make it a public configuration or keep it as an undocumented one. Refer JIRA for more details.
## How was this patch tested?
Ran existing jobs and verified the event queue size with debug logs and from the Spark WebUI Environment tab.
Author: Dhruve Ashar <dhruveashar@gmail.com>
Closes#14269 from dhruve/bug/SPARK-15703.
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Mesos agents by default will not pull docker images which are cached
locally already. In order to run Spark executors from mutable tags like
`:latest` this commit introduces a Spark setting
(`spark.mesos.executor.docker.forcePullImage`). Setting this flag to
true will tell the Mesos agent to force pull the docker image (default is `false` which is consistent with the previous
implementation and Mesos' default
behaviour).
Author: Philipp Hoffmann <mail@philipphoffmann.de>
Closes#14348 from philipphoffmann/force-pull-image.
## What changes were proposed in this pull request?
This patch adds pagination support for the Job Tables in the Jobs tab. Pagination is provided for all of the three Job Tables (active, completed, and failed). Interactions (jumping, sorting, and setting page size) for paged tables are also included.
The diff didn't keep track of some lines based on the original ones. The function `makeRow`of the original `AllJobsPage.scala` is reused. They are separated at the beginning of the function `jobRow` (L427-439) and the function `row`(L594-618) in the new `AllJobsPage.scala`.
## How was this patch tested?
Tested manually by using checking the Web UI after completing and failing hundreds of jobs.
Generate completed jobs by:
```scala
val d = sc.parallelize(Array(1,2,3,4,5))
for(i <- 1 to 255){ var b = d.collect() }
```
Generate failed jobs by calling the following code multiple times:
```scala
var b = d.map(_/0).collect()
```
Interactions like jumping, sorting, and setting page size are all tested.
This shows the pagination for completed jobs:
This shows the sorting works in job tables:
This shows the pagination for failed jobs and the effect of jumping and setting page size:
Author: Tao Lin <nblintao@gmail.com>
Closes#13620 from nblintao/dev.
## What changes were proposed in this pull request?
Currently in the log and UI display, only on-heap storage memory is calculated and displayed,
```
16/06/27 13:41:52 INFO MemoryStore: Block rdd_5_0 stored as values in memory (estimated size 17.8 KB, free 665.9 MB)
```
<img width="1232" alt="untitled" src="https://cloud.githubusercontent.com/assets/850797/16369960/53fb614e-3c6e-11e6-8fa3-7ffe65abcb49.png">
With [SPARK-13992](https://issues.apache.org/jira/browse/SPARK-13992) off-heap memory is supported for data persistence, so here change to also take off-heap storage memory into consideration.
## How was this patch tested?
Unit test and local verification.
Author: jerryshao <sshao@hortonworks.com>
Closes#13920 from jerryshao/SPARK-16166.
## What changes were proposed in this pull request?
Mesos agents by default will not pull docker images which are cached
locally already. In order to run Spark executors from mutable tags like
`:latest` this commit introduces a Spark setting
`spark.mesos.executor.docker.forcePullImage`. Setting this flag to
true will tell the Mesos agent to force pull the docker image (default is `false` which is consistent with the previous
implementation and Mesos' default
behaviour).
## How was this patch tested?
I ran a sample application including this change on a Mesos cluster and verified the correct behaviour for both, with and without, force pulling the executor image. As expected the image is being force pulled if the flag is set.
Author: Philipp Hoffmann <mail@philipphoffmann.de>
Closes#13051 from philipphoffmann/force-pull-image.
…close between each partition
## What changes were proposed in this pull request?
Replace commitAndClose with separate commit and close to avoid opening and closing
the file between partitions.
## How was this patch tested?
Run existing unit tests, add a few unit tests regarding reverts.
Observed a ~20% reduction in total time in tasks on stages with shuffle
writes to many partitions.
JoshRosen
Author: Brian Cho <bcho@fb.com>
Closes#13382 from dafrista/separatecommit-master.
## What changes were proposed in this pull request?
Force eager creation of loggers to avoid shutdown hook conflicts.
## How was this patch tested?
Manually tested with a project using Log4j 2, verified that the shutdown hook conflict issue was solved.
Author: Mikael Ståldal <mikael.staldal@magine.com>
Closes#14320 from mikaelstaldal/shutdown-hook-logging.
## What changes were proposed in this pull request?
Added new configuration namespace: spark.mesos.env.*
This allows a user submitting a job in cluster mode to set arbitrary environment variables on the driver.
spark.mesos.driverEnv.KEY=VAL will result in the env var "KEY" being set to "VAL"
I've also refactored the tests a bit so we can re-use code in MesosClusterScheduler.
And I've refactored the command building logic in `buildDriverCommand`. Command builder values were very intertwined before, and now it's easier to determine exactly how each variable is set.
## How was this patch tested?
unit tests
Author: Michael Gummelt <mgummelt@mesosphere.io>
Closes#14167 from mgummelt/driver-env-vars.
This allows configuration to be more flexible, for example, when the cluster does
not have a homogeneous configuration (e.g. packages are installed on different
paths in different nodes). By allowing one to reference the environment from
the conf, it becomes possible to work around those in certain cases.
As part of the implementation, ConfigEntry now keeps track of all "known" configs
(i.e. those created through the use of ConfigBuilder), since that list is used
by the resolution code. This duplicates some code in SQLConf, which could potentially
be merged with this now. It will also make it simpler to implement some missing
features such as filtering which configs show up in the UI or in event logs - which
are not part of this change.
Another change is in the way ConfigEntry reads config data; it now takes a string
map and a function that reads env variables, so that it can be called both from
SparkConf and SQLConf. This makes it so both places follow the same read path,
instead of having to replicate certain logic in SQLConf. There are still a
couple of methods in SQLConf that peek into fields of ConfigEntry directly,
though.
Tested via unit tests, and by using the new variable expansion functionality
in a shell session with a custom spark.sql.hive.metastore.jars value.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#14022 from vanzin/SPARK-16272.
1. Create the executorspage-template.html for displaying application information in datables.
2. Added REST API endpoint "allexecutors" to be able to see all executors created for particular job.
3. The executorspage.js uses jQuery to access the data from /api/v1/applications/appid/allexecutors REST API, and use DataTable to display executors for the application. It also, generates summary of dead/live and total executors created during life of the application.
4. Similar changes applicable to Executors Page on history server for a given application.
Snapshots for how it looks like now:
<img width="938" alt="screen shot 2016-06-14 at 2 45 44 pm" src="https://cloud.githubusercontent.com/assets/6090397/16060092/ad1de03a-324b-11e6-8469-9eaa3f2548b5.png">
New Executors Page screenshot looks like this:
<img width="1436" alt="screen shot 2016-06-15 at 10 12 01 am" src="https://cloud.githubusercontent.com/assets/6090397/16085514/ee7004f0-32e1-11e6-9340-33d91e407f2b.png">
Author: Kishor Patil <kpatil@yahoo-inc.com>
Closes#13670 from kishorvpatil/execTemplates.
## What changes were proposed in this pull request?
Document RDD.pipe semantics; don't execute process for empty input partitions.
Note this includes the fix in https://github.com/apache/spark/pull/14256 because it's necessary to even test this. One or the other will merge the fix.
## How was this patch tested?
Jenkins tests including new test.
Author: Sean Owen <sowen@cloudera.com>
Closes#14260 from srowen/SPARK-16613.
## What changes were proposed in this pull request?
This change moves the include jar test from R to SparkSubmitSuite and uses a dynamically compiled jar. This helps us remove the binary jar from the R package and solves both the CRAN warnings and the lack of source being available for this jar.
## How was this patch tested?
SparkR unit tests, SparkSubmitSuite, check-cran.sh
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#14243 from shivaram/sparkr-jar-move.
## What changes were proposed in this pull request?
Adds a few public methods to `SparkLauncher` to allow configuring some extra features of the `ProcessBuilder`, including the working directory, output and error stream redirection.
## How was this patch tested?
Unit testing + simple Spark driver programs
Author: Andrew Duffy <root@aduffy.org>
Closes#14201 from andreweduffy/feature/launcher.
## What changes were proposed in this pull request?
Currently `RDD.pipe(command: String)`:
- works only when the command is specified without any options, such as `RDD.pipe("wc")`
- does NOT work when the command is specified with some options, such as `RDD.pipe("wc -l")`
This is a regression from Spark 1.6.
This patch adds back the tokenization process in `RDD.pipe(command: String)` to fix this regression.
## How was this patch tested?
Added a test which:
- would pass in `1.6`
- _[prior to this patch]_ would fail in `master`
- _[after this patch]_ would pass in `master`
Author: Liwei Lin <lwlin7@gmail.com>
Closes#14256 from lw-lin/rdd-pipe.
https://issues.apache.org/jira/browse/SPARK-16535
## What changes were proposed in this pull request?
When I scan through the pom.xml of sub projects, I found this warning as below and attached screenshot
```
Definition of groupId is redundant, because it's inherited from the parent
```
I've tried to remove some of the lines with groupId definition, and the build on my local machine is still ok.
```
<groupId>org.apache.spark</groupId>
```
As I just find now `<maven.version>3.3.9</maven.version>` is being used in Spark 2.x, and Maven-3 supports versionless parent elements: Maven 3 will remove the need to specify the parent version in sub modules. THIS is great (in Maven 3.1).
ref: http://stackoverflow.com/questions/3157240/maven-3-worth-it/3166762#3166762
## How was this patch tested?
I've tested by re-building the project, and build succeeded.
Author: Xin Ren <iamshrek@126.com>
Closes#14189 from keypointt/SPARK-16535.
## What changes were proposed in this pull request?
With the fix from SPARK-13112, I see that `LaunchTask` is always processed after `RegisteredExecutor` is done and so it gets chance to do all retries to startup an executor. There is still a problem that if `Executor` creation itself fails and there is some exception, it gets unnoticed and the executor is killed when it tries to process the `LaunchTask` as `executor` is null : https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala#L88 So if one looks at the logs, it does not tell that there was problem during `Executor` creation and thats why it was killed.
This PR explicitly catches exception in `Executor` creation, logs a proper message and then exits the JVM. Also, I have changed the `exitExecutor` method to accept `reason` so that backends can use that reason and do stuff like logging to a DB to get an aggregate of such exits at a cluster level
## How was this patch tested?
I am relying on existing tests
Author: Tejas Patil <tejasp@fb.com>
Closes#14202 from tejasapatil/exit_executor_failure.
## What changes were proposed in this pull request?
Currently when running spark on yarn, jars specified with --jars, --packages will be added twice, one is Spark's own file server, another is yarn's distributed cache, this can be seen from log:
for example:
```
./bin/spark-shell --master yarn-client --jars examples/target/scala-2.11/jars/scopt_2.11-3.3.0.jar
```
If specified the jar to be added is scopt jar, it will added twice:
```
...
16/07/14 15:06:48 INFO Server: Started 5603ms
16/07/14 15:06:48 INFO Utils: Successfully started service 'SparkUI' on port 4040.
16/07/14 15:06:48 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://192.168.0.102:4040
16/07/14 15:06:48 INFO SparkContext: Added JAR file:/Users/sshao/projects/apache-spark/examples/target/scala-2.11/jars/scopt_2.11-3.3.0.jar at spark://192.168.0.102:63996/jars/scopt_2.11-3.3.0.jar with timestamp 1468480008637
16/07/14 15:06:49 INFO RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
16/07/14 15:06:49 INFO Client: Requesting a new application from cluster with 1 NodeManagers
16/07/14 15:06:49 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container)
16/07/14 15:06:49 INFO Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
16/07/14 15:06:49 INFO Client: Setting up container launch context for our AM
16/07/14 15:06:49 INFO Client: Setting up the launch environment for our AM container
16/07/14 15:06:49 INFO Client: Preparing resources for our AM container
16/07/14 15:06:49 WARN Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
16/07/14 15:06:50 INFO Client: Uploading resource file:/private/var/folders/tb/8pw1511s2q78mj7plnq8p9g40000gn/T/spark-a446300b-84bf-43ff-bfb1-3adfb0571a42/__spark_libs__6486179704064718817.zip -> hdfs://localhost:8020/user/sshao/.sparkStaging/application_1468468348998_0009/__spark_libs__6486179704064718817.zip
16/07/14 15:06:51 INFO Client: Uploading resource file:/Users/sshao/projects/apache-spark/examples/target/scala-2.11/jars/scopt_2.11-3.3.0.jar -> hdfs://localhost:8020/user/sshao/.sparkStaging/application_1468468348998_0009/scopt_2.11-3.3.0.jar
16/07/14 15:06:51 INFO Client: Uploading resource file:/private/var/folders/tb/8pw1511s2q78mj7plnq8p9g40000gn/T/spark-a446300b-84bf-43ff-bfb1-3adfb0571a42/__spark_conf__326416236462420861.zip -> hdfs://localhost:8020/user/sshao/.sparkStaging/application_1468468348998_0009/__spark_conf__.zip
...
```
So here try to avoid adding jars to Spark's fileserver unnecessarily.
## How was this patch tested?
Manually verified both in yarn client and cluster mode, also in standalone mode.
Author: jerryshao <sshao@hortonworks.com>
Closes#14196 from jerryshao/SPARK-16540.
## What changes were proposed in this pull request?
Currently if `spark.dynamicAllocation.initialExecutors` is less than `spark.dynamicAllocation.minExecutors`, Spark will automatically pick the minExecutors without any warning. While in 1.6 Spark will throw exception if configured like this. So here propose to add warning log if these parameters are configured invalidly.
## How was this patch tested?
Unit test added to verify the scenario.
Author: jerryshao <sshao@hortonworks.com>
Closes#14149 from jerryshao/SPARK-16435.
## What changes were proposed in this pull request?
I fixed a misassigned var, numCompletedTasks was assigned to numSkippedTasks in the convertJobData method
## How was this patch tested?
dev/run-tests
Author: Alex Bozarth <ajbozart@us.ibm.com>
Closes#14141 from ajbozarth/spark16375.
## What changes were proposed in this pull request?
Since externalShuffleService is essential for spark, better monitoring for shuffle service is necessary. In order to do so, we added various metrics in shuffle service and imported into ExternalShuffleServiceSource for metric system.
Metrics added in shuffle service:
* registeredExecutorsSize
* openBlockRequestLatencyMillis
* registerExecutorRequestLatencyMillis
* blockTransferRateBytes
JIRA Issue: https://issues.apache.org/jira/browse/SPARK-16405
## How was this patch tested?
Some test cases are added to verify metrics as expected in metric system. Those unit test cases are shown in `ExternalShuffleBlockHandlerSuite `
Author: Yangyang Liu <yangyangliu@fb.com>
Closes#14080 from lovexi/yangyang-metrics.
## What changes were proposed in this pull request?
After SPARK-16476 (committed earlier today as #14128), we can finally bump the version number.
## How was this patch tested?
N/A
Author: Reynold Xin <rxin@databricks.com>
Closes#14130 from rxin/SPARK-16477.
## What changes were proposed in this pull request?
It's possible to also change the callers to not pass in empty chunks, but it seems cleaner to just allow `ChunkedByteBuffer` to handle empty arrays. cc JoshRosen
## How was this patch tested?
Unit tests, also checked that the original reproduction case in https://github.com/apache/spark/pull/11748#issuecomment-230760283 is resolved.
Author: Eric Liang <ekl@databricks.com>
Closes#14099 from ericl/spark-16432.
## What changes were proposed in this pull request?
Avoid error finding max of empty Seq when stageIds is empty. It does fix the immediate problem; I don't know if it results in meaningful output, but not an error at least.
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#14105 from srowen/SPARK-16376.
## What changes were proposed in this pull request?
This uses the try/finally pattern to ensure streams are closed after use. `UnsafeShuffleWriter` wasn't closing compression streams, causing them to leak resources until garbage collected. This was causing a problem with codecs that use off-heap memory.
## How was this patch tested?
Current tests are sufficient. This should not change behavior.
Author: Ryan Blue <blue@apache.org>
Closes#14093 from rdblue/SPARK-16420-unsafe-shuffle-writer-leak.
## What changes were proposed in this pull request?
This moves over old PR https://github.com/apache/spark/pull/13664 to target master rather than branch-1.6.
Added links to logs (or an indication that there are no logs) for entries which list an executor in the stage details page of the UI.
This helps streamline the workflow where a user views a stage details page and determines that they would like to see the associated executor log for further examination. Previously, a user would have to cross reference the executor id listed on the stage details page with the corresponding entry on the executors tab.
Link to the JIRA: https://issues.apache.org/jira/browse/SPARK-15885
## How was this patch tested?
Ran existing unit tests.
Ran test queries on a platform which did not record executor logs and again on a platform which did record executor logs and verified that the new table column was empty and links to the logs (which were verified as linking to the appropriate files), respectively.
Attached is a screenshot of the UI page with no links, with the new columns highlighted. Additional screenshot of these columns with the populated links.
Without links:
With links:
This contribution is my original work and I license the work to the project under the Apache Spark project's open source license.
Author: Tom Magrino <tmagrino@fb.com>
Closes#13861 from tmagrino/uilogstweak.
## What changes were proposed in this pull request?
Make SparkContext `cancelJob` and `cancelStage` APIs public. This allows applications to use `SparkListener` to do their own management of jobs via events, but without using the REST API.
## How was this patch tested?
Existing tests (dev/run-tests)
Author: MasterDDT <miteshp@live.com>
Closes#14072 from MasterDDT/SPARK-16398.
## What changes were proposed in this pull request?
The commit 044971eca0 introduced a lazy val to simplify code in Logging. Simple enough, though one side effect is that accessing log now means grabbing the instance's lock. This in turn turned up a form of deadlock in the Mesos code. It was arguably a bit of a problem in how this code is structured, but, in any event the safest thing to do seems to be to revert the commit, and that's 90% of the change here; it's just not worth the risk of similar more subtle issues.
What I didn't revert here was the removal of this odd override of log in the Mesos code. In retrospect it might have been put in place at some stage as a defense against this type of problem. After all the Logging code still involved a lock at initialization before the change in question.
Even after the revert, it doesn't seem like it does anything, given how Logging works now, so I left it removed. However, I also removed the particular log message that ended up playing a part in this problem anyway, maybe being paranoid, to make sure this type of problem can't happen even with how the current locking works in logging initialization.
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#14069 from srowen/SPARK-16379.
## What changes were proposed in this pull request?
This patch updates the failure handling logic so Spark executor does not crash when seeing LinkageError.
## How was this patch tested?
Added an end-to-end test in FailureSuite.
Author: petermaxlee <petermaxlee@gmail.com>
Closes#13982 from petermaxlee/SPARK-16304.
## What changes were proposed in this pull request?
This patch adds pagination support for the Stage Tables in the Stage tab. Pagination is provided for all of the four Job Tables (active, pending, completed, and failed). Besides, the paged stage tables are also used in JobPage (the detail page for one job) and PoolPage.
Interactions (jumping, sorting, and setting page size) for paged tables are also included.
## How was this patch tested?
Tested manually by using checking the Web UI after completing and failing hundreds of jobs. Same as the testings for [Paginate Job Table in Jobs tab](https://github.com/apache/spark/pull/13620).
This shows the pagination for completed stages:
Author: Tao Lin <nblintao@gmail.com>
Closes#13708 from nblintao/stageTable.
Using "Method.invoke" causes an exception to be thrown, not an error, so
Utils.waitForProcess() was always throwing an exception when run on Java 7.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#14056 from vanzin/SPARK-16385.
## What changes were proposed in this pull request?
Coincidentally, I discovered that a couple images were unused in `docs/`, and then searched and found more, and then realized some PNGs were pretty big and could be crushed, and before I knew it, had done the same for the ASF site (not committed yet).
No functional change at all, just less superfluous image data.
## How was this patch tested?
`jekyll serve`
Author: Sean Owen <sowen@cloudera.com>
Closes#14029 from srowen/RemoveCompressImages.
## What changes were proposed in this pull request?
This PR fixes the minor Java linter errors like the following.
```
- public int read(char cbuf[], int off, int len) throws IOException {
+ public int read(char[] cbuf, int off, int len) throws IOException {
```
## How was this patch tested?
Manual.
```
$ build/mvn -T 4 -q -DskipTests -Pyarn -Phadoop-2.3 -Pkinesis-asl -Phive -Phive-thriftserver install
$ dev/lint-java
Using `mvn` from path: /usr/local/bin/mvn
Checkstyle checks passed.
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#14017 from dongjoon-hyun/minor_build_java_linter_error.
## What changes were proposed in this pull request?
In structured streaming, Spark does not report errors when the specified directory does not exist. This is a behavior different from the batch mode. This patch changes the behavior to fail if the directory does not exist (when the path is not a glob pattern).
## How was this patch tested?
Updated unit tests to reflect the new behavior.
Author: Reynold Xin <rxin@databricks.com>
Closes#14002 from rxin/SPARK-16335.
## What changes were proposed in this pull request?
Utils.terminateProcess should `destroy()` first and only fall back to `destroyForcibly()` if it fails. It's kind of bad that we're force-killing executors -- and only in Java 8. See JIRA for an example of the impact: no shutdown
While here: `Utils.waitForProcess` should use the Java 8 method if available instead of a custom implementation.
## How was this patch tested?
Existing tests, which cover the force-kill case, and Amplab tests, which will cover both Java 7 and Java 8 eventually. However I tested locally on Java 8 and the PR builder will try Java 7 here.
Author: Sean Owen <sowen@cloudera.com>
Closes#13973 from srowen/SPARK-16182.
## What changes were proposed in this pull request?
Before this change, when you turn on blacklisting with `spark.scheduler.executorTaskBlacklistTime`, but you have fewer than `spark.task.maxFailures` executors, you can end with a job "hung" after some task failures.
Whenever a taskset is unable to schedule anything on resourceOfferSingleTaskSet, we check whether the last pending task can be scheduled on *any* known executor. If not, the taskset (and any corresponding jobs) are failed.
* Worst case, this is O(maxTaskFailures + numTasks). But unless many executors are bad, this should be small
* This does not fail as fast as possible -- when a task becomes unschedulable, we keep scheduling other tasks. This is to avoid an O(numPendingTasks * numExecutors) operation
* Also, it is conceivable this fails too quickly. You may be 1 millisecond away from unblacklisting a place for a task to run, or acquiring a new executor.
## How was this patch tested?
Added unit test which failed before the change, ran new test 5k times manually, ran all scheduler tests manually, and the full suite via jenkins.
Author: Imran Rashid <irashid@cloudera.com>
Closes#13603 from squito/progress_w_few_execs_and_blacklist.
## What changes were proposed in this pull request?
Force the sorter to Spill when number of elements in the pointer array reach a certain size. This is to workaround the issue of timSort failing on large buffer size.
## How was this patch tested?
Tested by running a job which was failing without this change due to TimSort bug.
Author: Sital Kedia <skedia@fb.com>
Closes#13107 from sitalkedia/fix_TimSort.
