Currently, the Spark AM relies on the initial set of tokens created by
the submission client to be able to talk to HDFS and other services that
require delegation tokens. This means that after those tokens expire, a
new AM will fail to start (e.g. when there is an application failure and
re-attempts are enabled).
This PR makes it so that the first thing the AM does when the user provides
a principal and keytab is to create new delegation tokens for use. This
makes sure that the AM can be started irrespective of how old the original
token set is. It also allows all of the token management to be done by the
AM - there is no need for the submission client to set configuration values
to tell the AM when to renew tokens.
Note that even though in this case the AM will not be using the delegation
tokens created by the submission client, those tokens still need to be provided
to YARN, since they are used to do log aggregation.
To be able to re-use the code in the AMCredentialRenewal for the above
purposes, I refactored that class a bit so that it can fetch tokens into
a pre-defined UGI, insted of always logging in.
Another issue with re-attempts is that, after the fix that allows the AM
to restart correctly, new executors would get confused about when to
update credentials, because the credential updater used the update time
initially set up by the submission code. This could make the executor
fail to update credentials in time, since that value would be very out
of date in the situation described in the bug.
To fix that, I changed the YARN code to use the new RPC-based mechanism
for distributing tokens to executors. This allowed the old credential
updater code to be removed, and a lot of code in the renewer to be
simplified.
I also made two currently hardcoded values (the renewal time ratio, and
the retry wait) configurable; while this probably never needs to be set
by anyone in a production environment, it helps with testing; that's also
why they're not documented.
Tested on real cluster with a specially crafted application to test this
functionality: checked proper access to HDFS, Hive and HBase in cluster
mode with token renewal on and AM restarts. Tested things still work in
client mode too.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#20657 from vanzin/SPARK-23361.
A few different things going on:
- Remove unused methods.
- Move JSON methods to the only class that uses them.
- Move test-only methods to TestUtils.
- Make getMaxResultSize() a config constant.
- Reuse functionality from existing libraries (JRE or JavaUtils) where possible.
The change also includes changes to a few tests to call `Utils.createTempFile` correctly,
so that temp dirs are created under the designated top-level temp dir instead of
potentially polluting git index.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#20706 from vanzin/SPARK-23550.
## What changes were proposed in this pull request?
There is a race condition introduced in SPARK-11141 which could cause data loss.
The problem is that ReceivedBlockTracker.insertAllocatedBatch function assumes that all blocks from streamIdToUnallocatedBlockQueues allocated to the batch and clears the queue.
In this PR only the allocated blocks will be removed from the queue which will prevent data loss.
## How was this patch tested?
Additional unit test + manually.
Author: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Closes#20620 from gaborgsomogyi/SPARK-23438.
The code was ignoring the error code from the AddBlock RPC, which
means that a failure to write to the WAL was being ignored by the
receiver, and would lead to the block being acked (in the case of
the Flume receiver) and data potentially lost.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#20161 from vanzin/SPARK-21525.
## What changes were proposed in this pull request?
When using the Kubernetes cluster-manager and spawning a Streaming workload, it is important to reset many spark.kubernetes.* properties that are generated by spark-submit but which would get rewritten when restoring a Checkpoint. This is so, because the spark-submit codepath creates Kubernetes resources, such as a ConfigMap, a Secret and other variables, which have an autogenerated name and the previous one will not resolve anymore.
In short, this change enables checkpoint restoration for streaming workloads, and thus enables Spark Streaming workloads in Kubernetes, which were not possible to restore from a checkpoint before if the workload went down.
## How was this patch tested?
This patch was tested with the twitter-streaming example in AWS, using checkpoints in s3 with the s3a:// protocol, as supported by Hadoop.
This is similar to the YARN related code for resetting a Spark Streaming workload, but for the Kubernetes scheduler. I'm adding the initcontainers properties because even if the discussion is not completely settled on the mailing list, my understanding is that at this moment they are going forward for the moment.
For a previous discussion, see the non-rebased work at: https://github.com/apache-spark-on-k8s/spark/pull/516
Author: Santiago Saavedra <ssaavedra@openshine.com>
Closes#20383 from ssaavedra/fix-k8s-checkpointing.
## What changes were proposed in this pull request?
Increased timeout from 50 ms to 300 ms (50 ms was really too low).
## How was this patch tested?
Multiple rounds of tests.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#20371 from tdas/SPARK-23197.
## What changes were proposed in this pull request?
This patch bumps the master branch version to `2.4.0-SNAPSHOT`.
## How was this patch tested?
N/A
Author: gatorsmile <gatorsmile@gmail.com>
Closes#20222 from gatorsmile/bump24.
Still look at the old one in case any Spark user is setting it
explicitly, though.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#19983 from vanzin/SPARK-22788.
…a-2.12 and JDK9
## What changes were proposed in this pull request?
Some compile error after upgrading to scala-2.12
```javascript
spark_source/core/src/main/scala/org/apache/spark/executor/Executor.scala:455: ambiguous reference to overloaded definition, method limit in class ByteBuffer of type (x$1: Int)java.nio.ByteBuffer
method limit in class Buffer of type ()Int
match expected type ?
val resultSize = serializedDirectResult.limit
error
```
The limit method was moved from ByteBuffer to the superclass Buffer and it can no longer be called without (). The same reason for position method.
```javascript
/home/zly/prj/oss/jdk9_HOS_SOURCE/spark_source/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformationExec.scala:427: ambiguous reference to overloaded definition, [error] both method putAll in class Properties of type (x$1: java.util.Map[_, _])Unit [error] and method putAll in class Hashtable of type (x$1: java.util.Map[_ <: Object, _ <: Object])Unit [error] match argument types (java.util.Map[String,String])
[error] props.putAll(outputSerdeProps.toMap.asJava)
[error] ^
```
This is because the key type is Object instead of String which is unsafe.
## How was this patch tested?
running tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: kellyzly <kellyzly@126.com>
Closes#19854 from kellyzly/SPARK-22660.
The only remaining use of this class was the SparkStatusTracker, which
was modified to use the new status store. The test code to wait for
executors was moved to TestUtils and now uses the SparkStatusTracker API.
Indirectly, ConsoleProgressBar also uses this data. Because it has
some lower latency requirements, a shortcut to efficiently get the
active stages from the active listener was added to the AppStateStore.
Now that all UI code goes through the status store to get its data,
the FsHistoryProvider can be cleaned up to only replay event logs
when needed - that is, when there is no pre-existing disk store for
the application.
As part of this change I also modified the streaming UI to read the needed
data from the store, which was missed in the previous patch that made
JobProgressListener redundant.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#19750 from vanzin/SPARK-20650.
## What changes were proposed in this pull request?
ScalaTest 3.0 uses an implicit `Signaler`. This PR makes it sure all Spark tests uses `ThreadSignaler` explicitly which has the same default behavior of interrupting a thread on the JVM like ScalaTest 2.2.x. This will reduce potential flakiness.
## How was this patch tested?
This is testsuite-only update. This should passes the Jenkins tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#19784 from dongjoon-hyun/use_thread_signaler.
With the new UI store, the API resource classes have a lot less code,
since there's no need for complicated translations between the UI
types and the API types. So the code ended up with a bunch of files
with a single method declared in them.
This change re-structures the API code so that it uses less classes;
mainly, most sub-resources were removed, and the code to deal with
single-attempt and multi-attempt apps was simplified.
The only change was the addition of a method to return a single
attempt's information; that was missing in the old API, so trying
to retrieve "/v1/applications/appId/attemptId" would result in a
404 even if the attempt existed (and URIs under that one would
return valid data).
The streaming API resources also overtook the same treatment, even
though the data is not stored in the new UI store.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#19748 from vanzin/SPARK-20649.
## What changes were proposed in this pull request?
It seems that recovering from a checkpoint can replace the old
driver and executor IP addresses, as the workload can now be taking
place in a different cluster configuration. It follows that the
bindAddress for the master may also have changed. Thus we should not be
keeping the old one, and instead be added to the list of properties to
reset and recreate from the new environment.
## How was this patch tested?
This patch was tested via manual testing on AWS, using the experimental (not yet merged) Kubernetes scheduler, which uses bindAddress to bind to a Kubernetes service (and thus was how I first encountered the bug too), but it is not a code-path related to the scheduler and this may have slipped through when merging SPARK-4563.
Author: Santiago Saavedra <ssaavedra@openshine.com>
Closes#19427 from ssaavedra/fix-checkpointing-master.
## What changes were proposed in this pull request?
Preliminary changes to get ClosureCleaner to work with Scala 2.12. Makes many usages just work, but not all. This does _not_ resolve the JIRA.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#19675 from srowen/SPARK-14540.0.
## What changes were proposed in this pull request?
SPARK-14930/SPARK-13693 put in a change to set the fs object to null after a failure, however the retry loop does not include initialization. Moved fs initialization inside the retry while loop to aid recoverability.
## How was this patch tested?
Passes all existing unit tests.
Author: Tristan Stevens <tristan@cloudera.com>
Closes#19645 from tmgstevens/SPARK-22429.
## What changes were proposed in this pull request?
Scala test source files like TestHiveSingleton.scala should be in scala source root
## How was this patch tested?
Just move scala file from java directory to scala directory
No new test case in this PR.
```
renamed: mllib/src/test/java/org/apache/spark/ml/util/IdentifiableSuite.scala -> mllib/src/test/scala/org/apache/spark/ml/util/IdentifiableSuite.scala
renamed: streaming/src/test/java/org/apache/spark/streaming/JavaTestUtils.scala -> streaming/src/test/scala/org/apache/spark/streaming/JavaTestUtils.scala
renamed: streaming/src/test/java/org/apache/spark/streaming/api/java/JavaStreamingListenerWrapperSuite.scala -> streaming/src/test/scala/org/apache/spark/streaming/api/java/JavaStreamingListenerWrapperSuite.scala
renamed: sql/hive/src/test/java/org/apache/spark/sql/hive/test/TestHiveSingleton.scala sql/hive/src/test/scala/org/apache/spark/sql/hive/test/TestHiveSingleton.scala
```
Author: xubo245 <601450868@qq.com>
Closes#19639 from xubo245/scalaDirectory.
## What changes were proposed in this pull request?
the previous [PR](https://github.com/apache/spark/pull/19469) is deleted by mistake.
the solution is straight forward.
adding "spark.yarn.jars" to propertiesToReload so this property will load from config.
## How was this patch tested?
manual tests
Author: ZouChenjun <zouchenjun@youzan.com>
Closes#19637 from ChenjunZou/checkpoint-yarn-jars.
## What changes were proposed in this pull request?
Scala 2.12's `Future` defines two new methods to implement, `transform` and `transformWith`. These can be implemented naturally in Spark's `FutureAction` extension and subclasses, but, only in terms of the new methods that don't exist in Scala 2.11. To support both at the same time, reflection is used to implement these.
## How was this patch tested?
Existing tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#19561 from srowen/SPARK-22322.
## What changes were proposed in this pull request?
Enable Scala 2.12 REPL. Fix most remaining issues with 2.12 compilation and warnings, including:
- Selecting Kafka 0.10.1+ for Scala 2.12 and patching over a minor API difference
- Fixing lots of "eta expansion of zero arg method deprecated" warnings
- Resolving the SparkContext.sequenceFile implicits compile problem
- Fixing an odd but valid jetty-server missing dependency in hive-thriftserver
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#19307 from srowen/Scala212.
This change modifies the live listener bus so that all listeners are
added to queues; each queue has its own thread to dispatch events,
making it possible to separate slow listeners from other more
performance-sensitive ones.
The public API has not changed - all listeners added with the existing
"addListener" method, which after this change mostly means all
user-defined listeners, end up in a default queue. Internally, there's
an API allowing listeners to be added to specific queues, and that API
is used to separate the internal Spark listeners into 3 categories:
application status listeners (e.g. UI), executor management (e.g. dynamic
allocation), and the event log.
The queueing logic, while abstracted away in a separate class, is kept
as much as possible hidden away from consumers. Aside from choosing their
queue, there's no code change needed to take advantage of queues.
Test coverage relies on existing tests; a few tests had to be tweaked
because they relied on `LiveListenerBus.postToAll` being synchronous,
and the change makes that method asynchronous. Other tests were simplified
not to use the asynchronous LiveListenerBus.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#19211 from vanzin/SPARK-18838.
Since ScalaTest 3.0.0, `org.scalatest.concurrent.Timeouts` is deprecated.
This PR replaces the deprecated one with `org.scalatest.concurrent.TimeLimits`.
```scala
-import org.scalatest.concurrent.Timeouts._
+import org.scalatest.concurrent.TimeLimits._
```
Pass the existing test suites.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#19150 from dongjoon-hyun/SPARK-21939.
Change-Id: I1a1b07f1b97e51e2263dfb34b7eaaa099b2ded5e
## What changes were proposed in this pull request?
1.0.0 fixes an issue with import order, explicit type for public methods, line length limitation and comment validation:
```
[error] .../spark/repl/scala-2.11/src/main/scala/org/apache/spark/repl/Main.scala:50:16: Are you sure you want to println? If yes, wrap the code block with
[error] // scalastyle:off println
[error] println(...)
[error] // scalastyle:on println
[error] .../spark/repl/scala-2.11/src/main/scala/org/apache/spark/repl/SparkILoop.scala:49: File line length exceeds 100 characters
[error] .../spark/repl/scala-2.11/src/main/scala/org/apache/spark/repl/SparkILoop.scala:22:21: Are you sure you want to println? If yes, wrap the code block with
[error] // scalastyle:off println
[error] println(...)
[error] // scalastyle:on println
[error] .../spark/streaming/src/test/java/org/apache/spark/streaming/JavaTestUtils.scala:35:6: Public method must have explicit type
[error] .../spark/streaming/src/test/java/org/apache/spark/streaming/JavaTestUtils.scala:51:6: Public method must have explicit type
[error] .../spark/streaming/src/test/java/org/apache/spark/streaming/JavaTestUtils.scala:93:15: Public method must have explicit type
[error] .../spark/streaming/src/test/java/org/apache/spark/streaming/JavaTestUtils.scala:98:15: Public method must have explicit type
[error] .../spark/streaming/src/test/java/org/apache/spark/streaming/JavaTestUtils.scala:47:2: Insert a space after the start of the comment
[error] .../spark/streaming/src/test/java/org/apache/spark/streaming/JavaTestUtils.scala:26:43: JavaDStream should come before JavaDStreamLike.
```
This PR also fixes the workaround added in SPARK-16877 for `org.scalastyle.scalariform.OverrideJavaChecker` feature, added from 0.9.0.
## How was this patch tested?
Manually tested.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#19116 from HyukjinKwon/scalastyle-1.0.0.
…build; fix some things that will be warnings or errors in 2.12; restore Scala 2.12 profile infrastructure
## What changes were proposed in this pull request?
This change adds back the infrastructure for a Scala 2.12 build, but does not enable it in the release or Python test scripts.
In order to make that meaningful, it also resolves compile errors that the code hits in 2.12 only, in a way that still works with 2.11.
It also updates dependencies to the earliest minor release of dependencies whose current version does not yet support Scala 2.12. This is in a sense covered by other JIRAs under the main umbrella, but implemented here. The versions below still work with 2.11, and are the _latest_ maintenance release in the _earliest_ viable minor release.
- Scalatest 2.x -> 3.0.3
- Chill 0.8.0 -> 0.8.4
- Clapper 1.0.x -> 1.1.2
- json4s 3.2.x -> 3.4.2
- Jackson 2.6.x -> 2.7.9 (required by json4s)
This change does _not_ fully enable a Scala 2.12 build:
- It will also require dropping support for Kafka before 0.10. Easy enough, just didn't do it yet here
- It will require recreating `SparkILoop` and `Main` for REPL 2.12, which is SPARK-14650. Possible to do here too.
What it does do is make changes that resolve much of the remaining gap without affecting the current 2.11 build.
## How was this patch tested?
Existing tests and build. Manually tested with `./dev/change-scala-version.sh 2.12` to verify it compiles, modulo the exceptions above.
Author: Sean Owen <sowen@cloudera.com>
Closes#18645 from srowen/SPARK-14280.
This version fixes a few issues in the import order checker; it provides
better error messages, and detects more improper ordering (thus the need
to change a lot of files in this patch). The main fix is that it correctly
complains about the order of packages vs. classes.
As part of the above, I moved some "SparkSession" import in ML examples
inside the "$example on$" blocks; that didn't seem consistent across
different source files to start with, and avoids having to add more on/off blocks
around specific imports.
The new scalastyle also seems to have a better header detector, so a few
license headers had to be updated to match the expected indentation.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#18943 from vanzin/SPARK-21731.
## What changes were proposed in this pull request?
```DStreams
class FileInputDStream
[line 162] protected[streaming] override def clearMetadata(time: Time) {
batchTimeToSelectedFiles.synchronized {
val oldFiles = batchTimeToSelectedFiles.filter(_._1 < (time - rememberDuration))
batchTimeToSelectedFiles --= oldFiles.keys
```
The above code does not remove the old generatedRDDs. "super.clearMetadata(time)" was added to the beginning of clearMetadata to remove the old generatedRDDs.
## How was this patch tested?
At the end of clearMetadata, the testing code (print the number of generatedRDDs) was added to check the old RDDS were removed manually.
Author: shaofei007 <1427357147@qq.com>
Author: Fei Shao <1427357147@qq.com>
Closes#18718 from shaofei007/master.
## What changes were proposed in this pull request?
Address scapegoat warnings for:
- BigDecimal double constructor
- Catching NPE
- Finalizer without super
- List.size is O(n)
- Prefer Seq.empty
- Prefer Set.empty
- reverse.map instead of reverseMap
- Type shadowing
- Unnecessary if condition.
- Use .log1p
- Var could be val
In some instances like Seq.empty, I avoided making the change even where valid in test code to keep the scope of the change smaller. Those issues are concerned with performance and it won't matter for tests.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#18635 from srowen/Scapegoat1.
## What changes were proposed in this pull request?
Reload the `spark.yarn.credentials.file` property when restarting a streaming application from checkpoint.
## How was this patch tested?
Manual tested with 1.6.3 and 2.1.1.
I didn't test this with master because of some compile problems, but I think it will be the same result.
## Notice
This should be merged into maintenance branches too.
jira: [SPARK-21008](https://issues.apache.org/jira/browse/SPARK-21008)
Author: saturday_s <shi.indetail@gmail.com>
Closes#18230 from saturday-shi/SPARK-21008.
## What changes were proposed in this pull request?
This PR proposes to stop `ReceiverTracker` to close `WriteAheadLog` whenever it is and make `WriteAheadLog` and its implementations idempotent.
## How was this patch tested?
Added a test in `WriteAheadLogSuite`. Note that the added test looks passing even if it closes twice (namely even without the changes in `FileBasedWriteAheadLog` and `BatchedWriteAheadLog`. It looks both are already idempotent but this is a rather sanity check.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#18224 from HyukjinKwon/streaming-closing.
## What changes were proposed in this pull request?
This patch adds Coda Hale metrics for instrumenting the `LiveListenerBus` in order to track the number of events received, dropped, and processed. In addition, it adds per-SparkListener-subclass timers to track message processing time. This is useful for identifying when slow third-party SparkListeners cause performance bottlenecks.
See the new `LiveListenerBusMetrics` for a complete description of the new metrics.
## How was this patch tested?
New tests in SparkListenerSuite, including a test to ensure proper counting of dropped listener events.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#18083 from JoshRosen/listener-bus-metrics.
## What changes were proposed in this pull request?
Include documentation of the fact that the updateFunc is sometimes called with no new values. This is documented in the main documentation here: https://spark.apache.org/docs/latest/streaming-programming-guide.html#updatestatebykey-operation however from the docs included with the code it is not clear that this is the case.
## How was this patch tested?
PR only changes comments. Confirmed code still builds.
Author: Wil Selwood <wil.selwood@sa.catapult.org.uk>
Closes#18088 from wselwood/note-edge-case-in-docs.
## What changes were proposed in this pull request?
Add `ThreadUtils.awaitReady` similar to `ThreadUtils.awaitResult` and disallow `Await.ready`.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#17763 from zsxwing/awaitready.
## What changes were proposed in this pull request?
Remove uses of scala.language.reflectiveCalls that are either unnecessary or probably resulting in more complex code. This turned out to be less significant than I thought, but, still worth a touch-up.
## How was this patch tested?
Existing tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#17949 from srowen/SPARK-20554.
## What changes were proposed in this pull request?
Add stripXSS and stripXSSMap to Spark Core's UIUtils. Calling these functions at any point that getParameter is called against a HttpServletRequest.
## How was this patch tested?
Unit tests, IBM Security AppScan Standard no longer showing vulnerabilities, manual verification of WebUI pages.
Author: NICHOLAS T. MARION <nmarion@us.ibm.com>
Closes#17686 from n-marion/xss-fix.
## What changes were proposed in this pull request?
This PR proposes to run Spark unidoc to test Javadoc 8 build as Javadoc 8 is easily re-breakable.
There are several problems with it:
- It introduces little extra bit of time to run the tests. In my case, it took 1.5 mins more (`Elapsed :[94.8746569157]`). How it was tested is described in "How was this patch tested?".
- > One problem that I noticed was that Unidoc appeared to be processing test sources: if we can find a way to exclude those from being processed in the first place then that might significantly speed things up.
(see joshrosen's [comment](https://issues.apache.org/jira/browse/SPARK-18692?focusedCommentId=15947627&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-15947627))
To complete this automated build, It also suggests to fix existing Javadoc breaks / ones introduced by test codes as described above.
There fixes are similar instances that previously fixed. Please refer https://github.com/apache/spark/pull/15999 and https://github.com/apache/spark/pull/16013
Note that this only fixes **errors** not **warnings**. Please see my observation https://github.com/apache/spark/pull/17389#issuecomment-288438704 for spurious errors by warnings.
## How was this patch tested?
Manually via `jekyll build` for building tests. Also, tested via running `./dev/run-tests`.
This was tested via manually adding `time.time()` as below:
```diff
profiles_and_goals = build_profiles + sbt_goals
print("[info] Building Spark unidoc (w/Hive 1.2.1) using SBT with these arguments: ",
" ".join(profiles_and_goals))
+ import time
+ st = time.time()
exec_sbt(profiles_and_goals)
+ print("Elapsed :[%s]" % str(time.time() - st))
```
produces
```
...
========================================================================
Building Unidoc API Documentation
========================================================================
...
[info] Main Java API documentation successful.
...
Elapsed :[94.8746569157]
...
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#17477 from HyukjinKwon/SPARK-18692.
## What changes were proposed in this pull request?
Add Locale.ROOT to internal calls to String `toLowerCase`, `toUpperCase`, to avoid inadvertent locale-sensitive variation in behavior (aka the "Turkish locale problem").
The change looks large but it is just adding `Locale.ROOT` (the locale with no country or language specified) to every call to these methods.
## How was this patch tested?
Existing tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#17527 from srowen/SPARK-20156.
…adoc
## What changes were proposed in this pull request?
Use recommended values for row boundaries in Window's scaladoc, i.e. `Window.unboundedPreceding`, `Window.unboundedFollowing`, and `Window.currentRow` (that were introduced in 2.1.0).
## How was this patch tested?
Local build
Author: Jacek Laskowski <jacek@japila.pl>
Closes#17417 from jaceklaskowski/window-expression-scaladoc.
This change modifies the way block data is encrypted to make the more
common cases faster, while penalizing an edge case. As a side effect
of the change, all data that goes through the block manager is now
encrypted only when needed, including the previous path (broadcast
variables) where that did not happen.
The way the change works is by not encrypting data that is stored in
memory; so if a serialized block is in memory, it will only be encrypted
once it is evicted to disk.
The penalty comes when transferring that encrypted data from disk. If the
data ends up in memory again, it is as efficient as before; but if the
evicted block needs to be transferred directly to a remote executor, then
there's now a performance penalty, since the code now uses a custom
FileRegion implementation to decrypt the data before transferring.
This also means that block data transferred between executors now is
not encrypted (and thus relies on the network library encryption support
for secrecy). Shuffle blocks are still transferred in encrypted form,
since they're handled in a slightly different way by the code. This also
keeps compatibility with existing external shuffle services, which transfer
encrypted shuffle blocks, and avoids having to make the external service
aware of encryption at all.
The serialization and deserialization APIs in the SerializerManager now
do not do encryption automatically; callers need to explicitly wrap their
streams with an appropriate crypto stream before using those.
As a result of these changes, some of the workarounds added in SPARK-19520
are removed here.
Testing: a new trait ("EncryptionFunSuite") was added that provides an easy
way to run a test twice, with encryption on and off; broadcast, block manager
and caching tests were modified to use this new trait so that the existing
tests exercise both encrypted and non-encrypted paths. I also ran some
applications with encryption turned on to verify that they still work,
including streaming tests that failed without the fix for SPARK-19520.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#17295 from vanzin/SPARK-19556.
This commit adds a killTaskAttempt method to SparkContext, to allow users to
kill tasks so that they can be re-scheduled elsewhere.
This also refactors the task kill path to allow specifying a reason for the task kill. The reason is propagated opaquely through events, and will show up in the UI automatically as `(N killed: $reason)` and `TaskKilled: $reason`. Without this change, there is no way to provide the user feedback through the UI.
Currently used reasons are "stage cancelled", "another attempt succeeded", and "killed via SparkContext.killTask". The user can also specify a custom reason through `SparkContext.killTask`.
cc rxin
In the stage overview UI the reasons are summarized:
Within the stage UI you can see individual task kill reasons:
Existing tests, tried killing some stages in the UI and verified the messages are as expected.
Author: Eric Liang <ekl@databricks.com>
Author: Eric Liang <ekl@google.com>
Closes#17166 from ericl/kill-reason.
## What changes were proposed in this pull request?
- SS python example: `TypeError: 'xxx' object is not callable`
- some other doc issue.
## How was this patch tested?
Jenkins.
Author: uncleGen <hustyugm@gmail.com>
Closes#17257 from uncleGen/docs-ss-python.
## What changes were proposed in this pull request?
https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/73800/testReport/
```
sbt.ForkMain$ForkError: org.scalatest.exceptions.TestFailedDueToTimeoutException: The code
passed to eventually never returned normally. Attempted 617 times over 10.003740484 seconds.
Last failure message: 8 did not equal 2.
at org.scalatest.concurrent.Eventually$class.tryTryAgain$1(Eventually.scala:420)
at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:438)
at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:336)
at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
at org.apache.spark.streaming.DStreamCheckpointTester$class.generateOutput(CheckpointSuite
.scala:172)
at org.apache.spark.streaming.CheckpointSuite.generateOutput(CheckpointSuite.scala:211)
```
the check condition is:
```
val checkpointFilesOfLatestTime = Checkpoint.getCheckpointFiles(checkpointDir).filter {
_.toString.contains(clock.getTimeMillis.toString)
}
// Checkpoint files are written twice for every batch interval. So assert that both
// are written to make sure that both of them have been written.
assert(checkpointFilesOfLatestTime.size === 2)
```
the path string may contain the `clock.getTimeMillis.toString`, like `3500` :
```
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-500
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-1000
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-1500
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-2000
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-2500
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-3000
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-3500.bk
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-3500
▲▲▲▲
```
so we should only check the filename, but not the whole path.
## How was this patch tested?
Jenkins.
Author: uncleGen <hustyugm@gmail.com>
Closes#17167 from uncleGen/flaky-CheckpointSuite.
## What changes were proposed in this pull request?
This PR proposes to fix the lint-breaks as below:
```
[ERROR] src/test/java/org/apache/spark/network/TransportResponseHandlerSuite.java:[29,8] (imports) UnusedImports: Unused import - org.apache.spark.network.buffer.ManagedBuffer.
[ERROR] src/main/java/org/apache/spark/unsafe/types/UTF8String.java:[156,10] (modifier) ModifierOrder: 'Nonnull' annotation modifier does not precede non-annotation modifiers.
[ERROR] src/main/java/org/apache/spark/SparkFirehoseListener.java:[122] (sizes) LineLength: Line is longer than 100 characters (found 105).
[ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeExternalSorter.java:[164,78] (coding) OneStatementPerLine: Only one statement per line allowed.
[ERROR] src/test/java/test/org/apache/spark/JavaAPISuite.java:[1157] (sizes) LineLength: Line is longer than 100 characters (found 121).
[ERROR] src/test/java/org/apache/spark/streaming/JavaMapWithStateSuite.java:[149] (sizes) LineLength: Line is longer than 100 characters (found 113).
[ERROR] src/test/java/test/org/apache/spark/streaming/Java8APISuite.java:[146] (sizes) LineLength: Line is longer than 100 characters (found 122).
[ERROR] src/test/java/test/org/apache/spark/streaming/JavaAPISuite.java:[32,8] (imports) UnusedImports: Unused import - org.apache.spark.streaming.Time.
[ERROR] src/test/java/test/org/apache/spark/streaming/JavaAPISuite.java:[611] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/test/java/test/org/apache/spark/streaming/JavaAPISuite.java:[1317] (sizes) LineLength: Line is longer than 100 characters (found 102).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetAggregatorSuite.java:[91] (sizes) LineLength: Line is longer than 100 characters (found 102).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java:[113] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java:[164] (sizes) LineLength: Line is longer than 100 characters (found 110).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java:[212] (sizes) LineLength: Line is longer than 100 characters (found 114).
[ERROR] src/test/java/org/apache/spark/mllib/tree/JavaDecisionTreeSuite.java:[36] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/main/java/org/apache/spark/examples/streaming/JavaKinesisWordCountASL.java:[26,8] (imports) UnusedImports: Unused import - com.amazonaws.regions.RegionUtils.
[ERROR] src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisStreamSuite.java:[20,8] (imports) UnusedImports: Unused import - com.amazonaws.regions.RegionUtils.
[ERROR] src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisStreamSuite.java:[94] (sizes) LineLength: Line is longer than 100 characters (found 103).
[ERROR] src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java:[30,8] (imports) UnusedImports: Unused import - org.apache.spark.sql.api.java.UDF1.
[ERROR] src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java:[72] (sizes) LineLength: Line is longer than 100 characters (found 104).
[ERROR] src/main/java/org/apache/spark/examples/mllib/JavaRankingMetricsExample.java:[121] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:[28,8] (imports) UnusedImports: Unused import - org.apache.spark.api.java.JavaRDD.
[ERROR] src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:[29,8] (imports) UnusedImports: Unused import - org.apache.spark.api.java.JavaSparkContext.
```
## How was this patch tested?
Manually via
```bash
./dev/lint-java
```
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#17072 from HyukjinKwon/java-lint.
The REST API has a security filter that performs auth checks
based on the UI root's security manager. That works fine when
the UI root is the app's UI, but not when it's the history server.
In the SHS case, all users would be allowed to see all applications
through the REST API, even if the UI itself wouldn't be available
to them.
This change adds auth checks for each app access through the API
too, so that only authorized users can see the app's data.
The change also modifies the existing security filter to use
`HttpServletRequest.getRemoteUser()`, which is used in other
places. That is not necessarily the same as the principal's
name; for example, when using Hadoop's SPNEGO auth filter,
the remote user strips the realm information, which then matches
the user name registered as the owner of the application.
I also renamed the UIRootFromServletContext trait to a more generic
name since I'm using it to store more context information now.
Tested manually with an authentication filter enabled.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#16978 from vanzin/SPARK-19652.
## What changes were proposed in this pull request?
Use `BytesWritable.copyBytes`, not `getBytes`, because `getBytes` returns the underlying array, which may be reused when repeated reads don't need a different size, as is the case with binaryRecords APIs
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#16974 from srowen/SPARK-19646.
## What changes were proposed in this pull request?
Convert tests to use Java 8 lambdas, and modest related fixes to surrounding code.
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#16964 from srowen/SPARK-19534.
## What changes were proposed in this pull request?
`askSync` is already added in `RpcEndpointRef` (see SPARK-19347 and https://github.com/apache/spark/pull/16690#issuecomment-276850068) and `askWithRetry` is marked as deprecated.
As mentioned SPARK-18113(https://github.com/apache/spark/pull/16503#event-927953218):
>askWithRetry is basically an unneeded API, and a leftover from the akka days that doesn't make sense anymore. It's prone to cause deadlocks (exactly because it's blocking), it imposes restrictions on the caller (e.g. idempotency) and other things that people generally don't pay that much attention to when using it.
Since `askWithRetry` is just used inside spark and not in user logic. It might make sense to replace all of them with `askSync`.
## How was this patch tested?
This PR doesn't change code logic, existing unit test can cover.
Author: jinxing <jinxing@meituan.com>
Closes#16790 from jinxing64/SPARK-19450.
- Move external/java8-tests tests into core, streaming, sql and remove
- Remove MaxPermGen and related options
- Fix some reflection / TODOs around Java 8+ methods
- Update doc references to 1.7/1.8 differences
- Remove Java 7/8 related build profiles
- Update some plugins for better Java 8 compatibility
- Fix a few Java-related warnings
For the future:
- Update Java 8 examples to fully use Java 8
- Update Java tests to use lambdas for simplicity
- Update Java internal implementations to use lambdas
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#16871 from srowen/SPARK-19493.
Spark's I/O encryption uses an ephemeral key for each driver instance.
So driver B cannot decrypt data written by driver A since it doesn't
have the correct key.
The write ahead log is used for recovery, thus needs to be readable by
a different driver. So it cannot be encrypted by Spark's I/O encryption
code.
The BlockManager APIs used by the WAL code to write the data automatically
encrypt data, so changes are needed so that callers can to opt out of
encryption.
Aside from that, the "putBytes" API in the BlockManager does not do
encryption, so a separate situation arised where the WAL would write
unencrypted data to the BM and, when those blocks were read, decryption
would fail. So the WAL code needs to ask the BM to encrypt that data
when encryption is enabled; this code is not optimal since it results
in a (temporary) second copy of the data block in memory, but should be
OK for now until a more performant solution is added. The non-encryption
case should not be affected.
Tested with new unit tests, and by running streaming apps that do
recovery using the WAL data with I/O encryption turned on.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#16862 from vanzin/SPARK-19520.
## What changes were proposed in this pull request?
`ReceiverSupervisorImpl` on executor side reports block's meta back to `ReceiverTracker` on driver side. In current code, `askWithRetry` is used. However, for `AddBlock`, `ReceiverTracker` is not idempotent, which may result in messages are processed multiple times.
**To reproduce**:
1. Check if it is the first time receiving `AddBlock` in `ReceiverTracker`, if so sleep long enough(say 200 seconds), thus the first RPC call will be timeout in `askWithRetry`, then `AddBlock` will be resent.
2. Rebuild Spark and run following job:
```
def streamProcessing(): Unit = {
val conf = new SparkConf()
.setAppName("StreamingTest")
.setMaster(masterUrl)
val ssc = new StreamingContext(conf, Seconds(200))
val stream = ssc.socketTextStream("localhost", 1234)
stream.print()
ssc.start()
ssc.awaitTermination()
}
```
**To fix**:
It makes sense to provide a blocking version `ask` in RpcEndpointRef, as mentioned in SPARK-18113 (https://github.com/apache/spark/pull/16503#event-927953218). Because Netty RPC layer will not drop messages. `askWithRetry` is a leftover from akka days. It imposes restrictions on the caller(e.g. idempotency) and other things that people generally don't pay that much attention to when using it.
## How was this patch tested?
Test manually. The scenario described above doesn't happen with this patch.
Author: jinxing <jinxing@meituan.com>
Closes#16690 from jinxing64/SPARK-19347.
## What changes were proposed in this pull request?
This PR proposes three things as below:
- Support LaTex inline-formula, `\( ... \)` in Scala API documentation
It seems currently,
```
\( ... \)
```
are rendered as they are, for example,
<img width="345" alt="2017-01-30 10 01 13" src="https://cloud.githubusercontent.com/assets/6477701/22423960/ab37d54a-e737-11e6-9196-4f6229c0189c.png">
It seems mistakenly more backslashes were added.
- Fix warnings Scaladoc/Javadoc generation
This PR fixes t two types of warnings as below:
```
[warn] .../spark/sql/catalyst/src/main/scala/org/apache/spark/sql/Row.scala:335: Could not find any member to link for "UnsupportedOperationException".
[warn] /**
[warn] ^
```
```
[warn] .../spark/sql/core/src/main/scala/org/apache/spark/sql/internal/VariableSubstitution.scala:24: Variable var undefined in comment for class VariableSubstitution in class VariableSubstitution
[warn] * `${var}`, `${system:var}` and `${env:var}`.
[warn] ^
```
- Fix Javadoc8 break
```
[error] .../spark/mllib/target/java/org/apache/spark/ml/PredictionModel.java:7: error: reference not found
[error] * E.g., {link VectorUDT} for vector features.
[error] ^
[error] .../spark/mllib/target/java/org/apache/spark/ml/PredictorParams.java:12: error: reference not found
[error] * E.g., {link VectorUDT} for vector features.
[error] ^
[error] .../spark/mllib/target/java/org/apache/spark/ml/Predictor.java:10: error: reference not found
[error] * E.g., {link VectorUDT} for vector features.
[error] ^
[error] .../spark/sql/hive/target/java/org/apache/spark/sql/hive/HiveAnalysis.java:5: error: reference not found
[error] * Note that, this rule must be run after {link PreprocessTableInsertion}.
[error] ^
```
## How was this patch tested?
Manually via `sbt unidoc` and `jeykil build`.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#16741 from HyukjinKwon/warn-and-break.
## What changes were proposed in this pull request?
When DStreamGraph is generating a job, it will hold a lock and block other APIs. Because StreamingJobProgressListener (numInactiveReceivers, streamName(streamId: Int), streamIds) needs to call DStreamGraph's methods to access some information, the UI may hang if generating a job is very slow (e.g., talking to the slow Kafka cluster to fetch metadata).
It's better to optimize the locks in DStreamGraph and StreamingJobProgressListener to make the UI not block by job generation.
## How was this patch tested?
existing ut
cc zsxwing
Author: uncleGen <hustyugm@gmail.com>
Closes#16601 from uncleGen/SPARK-19182.
## What changes were proposed in this pull request?
the current implementation of Spark streaming considers a batch is completed no matter the results of the jobs (1169db44bc/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala (L203))
Let's consider the following case:
A micro batch contains 2 jobs and they read from two different kafka topics respectively. One of these jobs is failed due to some problem in the user defined logic, after the other one is finished successfully.
1. The main thread in the Spark streaming application will execute the line mentioned above,
2. and another thread (checkpoint writer) will make a checkpoint file immediately after this line is executed.
3. Then due to the current error handling mechanism in Spark Streaming, StreamingContext will be closed (1169db44bc/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala (L214))
the user recovers from the checkpoint file, and because the JobSet containing the failed job has been removed (taken as completed) before the checkpoint is constructed, the data being processed by the failed job would never be reprocessed
This PR fix it by removing jobset from JobScheduler.jobSets only when all jobs in a jobset are successfully finished
## How was this patch tested?
existing tests
Author: CodingCat <zhunansjtu@gmail.com>
Author: Nan Zhu <zhunansjtu@gmail.com>
Closes#16542 from CodingCat/SPARK-18905.
## What changes were proposed in this pull request?
This PR proposes to fix all the test failures identified by testing with AppVeyor.
**Scala - aborted tests**
```
WindowQuerySuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.execution.WindowQuerySuite *** ABORTED *** (156 milliseconds)
org.apache.spark.sql.AnalysisException: LOAD DATA input path does not exist: C:projectssparksqlhive argetscala-2.11 est-classesdatafilespart_tiny.txt;
OrcSourceSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.orc.OrcSourceSuite *** ABORTED *** (62 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
ParquetMetastoreSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetMetastoreSuite *** ABORTED *** (4 seconds, 703 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
ParquetSourceSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetSourceSuite *** ABORTED *** (3 seconds, 907 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-581a6575-454f-4f21-a516-a07f95266143;
KafkaRDDSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaRDDSuite *** ABORTED *** (5 seconds, 212 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-4722304d-213e-4296-b556-951df1a46807
DirectKafkaStreamSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.DirectKafkaStreamSuite *** ABORTED *** (7 seconds, 127 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d0d3eba7-4215-4e10-b40e-bb797e89338e
at org.apache.spark.util.Utils$.deleteRecursively(Utils.scala:1010)
ReliableKafkaStreamSuite
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.ReliableKafkaStreamSuite *** ABORTED *** (5 seconds, 498 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d33e45a0-287e-4bed-acae-ca809a89d888
KafkaStreamSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaStreamSuite *** ABORTED *** (2 seconds, 892 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-59c9d169-5a56-4519-9ef0-cefdbd3f2e6c
KafkaClusterSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaClusterSuite *** ABORTED *** (1 second, 690 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-3ef402b0-8689-4a60-85ae-e41e274f179d
DirectKafkaStreamSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.DirectKafkaStreamSuite *** ABORTED *** (59 seconds, 626 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-426107da-68cf-4d94-b0d6-1f428f1c53f6
KafkaRDDSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.KafkaRDDSuite *** ABORTED *** (2 minutes, 6 seconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-b9ce7929-5dae-46ab-a0c4-9ef6f58fbc2
```
**Java - failed tests**
```
Test org.apache.spark.streaming.kafka.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-1cee32f4-4390-4321-82c9-e8616b3f0fb0, took 9.61 sec
Test org.apache.spark.streaming.kafka.JavaKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-f42695dd-242e-4b07-847c-f299b8e4676e, took 11.797 sec
Test org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-85c0d062-78cf-459c-a2dd-7973572101ce, took 1.581 sec
Test org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-49eb6b5c-8366-47a6-83f2-80c443c48280, took 17.895 sec
org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-898cf826-d636-4b1c-a61a-c12a364c02e7, took 8.858 sec
```
**Scala - failed tests**
```
PartitionProviderCompatibilitySuite:
- insert overwrite partition of new datasource table overwrites just partition *** FAILED *** (828 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-bb6337b9-4f99-45ab-ad2c-a787ab965c09
- SPARK-18635 special chars in partition values - partition management true *** FAILED *** (5 seconds, 360 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- SPARK-18635 special chars in partition values - partition management false *** FAILED *** (141 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```
```
UtilsSuite:
- reading offset bytes of a file (compressed) *** FAILED *** (0 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-ecb2b7d5-db8b-43a7-b268-1bf242b5a491
- reading offset bytes across multiple files (compressed) *** FAILED *** (0 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-25cc47a8-1faa-4da5-8862-cf174df63ce0
```
```
StatisticsSuite:
- MetastoreRelations fallback to HDFS for size estimation *** FAILED *** (110 milliseconds)
org.apache.spark.sql.catalyst.analysis.NoSuchTableException: Table or view 'csv_table' not found in database 'default';
```
```
SQLQuerySuite:
- permanent UDTF *** FAILED *** (125 milliseconds)
org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count_temp'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 24
- describe functions - user defined functions *** FAILED *** (125 milliseconds)
org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 7
- CTAS without serde with location *** FAILED *** (16 milliseconds)
java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-ed673d73-edfc-404e-829e-2e2b9725d94e/c1
- derived from Hive query file: drop_database_removes_partition_dirs.q *** FAILED *** (47 milliseconds)
java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_database_removes_partition_dirs_table
- derived from Hive query file: drop_table_removes_partition_dirs.q *** FAILED *** (0 milliseconds)
java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_table_removes_partition_dirs_table2
- SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH *** FAILED *** (109 milliseconds)
java.nio.file.InvalidPathException: Illegal char <:> at index 2: /C:/projects/spark/sql/hive/projectsspark arget mpspark-1a122f8c-dfb3-46c4-bab1-f30764baee0e/*part-r*
```
```
HiveDDLSuite:
- drop external tables in default database *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- add/drop partitions - external table *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- create/drop database - location without pre-created directory *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- create/drop database - location with pre-created directory *** FAILED *** (32 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- drop database containing tables - CASCADE *** FAILED *** (94 milliseconds)
CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)
- drop an empty database - CASCADE *** FAILED *** (63 milliseconds)
CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)
- drop database containing tables - RESTRICT *** FAILED *** (47 milliseconds)
CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)
- drop an empty database - RESTRICT *** FAILED *** (47 milliseconds)
CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)
- CREATE TABLE LIKE an external data source table *** FAILED *** (140 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-c5eba16d-07ae-4186-95bb-21c5811cf888;
- CREATE TABLE LIKE an external Hive serde table *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- desc table for data source table - no user-defined schema *** FAILED *** (125 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-e8bf5bf5-721a-4cbe-9d6 at scala.collection.immutable.List.foreach(List.scala:381)d-5543a8301c1d;
```
```
MetastoreDataSourcesSuite
- CTAS: persisted bucketed data source table *** FAILED *** (16 milliseconds)
java.lang.IllegalArgumentException: Can not create a Path from an empty string
```
```
ShowCreateTableSuite:
- simple external hive table *** FAILED *** (0 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```
```
PartitionedTablePerfStatsSuite:
- hive table: partitioned pruned table reports only selected files *** FAILED *** (313 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: partitioned pruned table reports only selected files *** FAILED *** (219 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-311f45f8-d064-4023-a4bb-e28235bff64d;
- hive table: lazy partition pruning reads only necessary partition data *** FAILED *** (203 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: lazy partition pruning reads only necessary partition data *** FAILED *** (187 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-fde874ca-66bd-4d0b-a40f-a043b65bf957;
- hive table: lazy partition pruning with file status caching enabled *** FAILED *** (188 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: lazy partition pruning with file status caching enabled *** FAILED *** (187 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-e6d20183-dd68-4145-acbe-4a509849accd;
- hive table: file status caching respects refresh table and refreshByPath *** FAILED *** (172 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: file status caching respects refresh table and refreshByPath *** FAILED *** (203 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-8b2c9651-2adf-4d58-874f-659007e21463;
- hive table: file status cache respects size limit *** FAILED *** (219 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: file status cache respects size limit *** FAILED *** (171 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-7835ab57-cb48-4d2c-bb1d-b46d5a4c47e4;
- datasource table: table setup does not scan filesystem *** FAILED *** (266 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-20598d76-c004-42a7-8061-6c56f0eda5e2;
- hive table: table setup does not scan filesystem *** FAILED *** (266 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- hive table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 281 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 422 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-4cfed321-4d1d-4b48-8d34-5c169afff383;
- hive table: files read and cached when filesource partition management is off *** FAILED *** (234 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: all partition data cached in memory when partition management is off *** FAILED *** (203 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-4bcc0398-15c9-4f6a-811e-12d40f3eec12;
- SPARK-18700: table loaded only once even when resolved concurrently *** FAILED *** (1 second, 266 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```
```
HiveSparkSubmitSuite:
- temporary Hive UDF: define a UDF and use it *** FAILED *** (2 seconds, 94 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- permanent Hive UDF: define a UDF and use it *** FAILED *** (281 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- permanent Hive UDF: use a already defined permanent function *** FAILED *** (718 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-8368: includes jars passed in through --jars *** FAILED *** (3 seconds, 521 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-8020: set sql conf in spark conf *** FAILED *** (0 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-8489: MissingRequirementError during reflection *** FAILED *** (94 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-9757 Persist Parquet relation with decimal column *** FAILED *** (16 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-11009 fix wrong result of Window function in cluster mode *** FAILED *** (16 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-14244 fix window partition size attribute binding failure *** FAILED *** (78 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- set spark.sql.warehouse.dir *** FAILED *** (16 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- set hive.metastore.warehouse.dir *** FAILED *** (15 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-16901: set javax.jdo.option.ConnectionURL *** FAILED *** (16 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-18360: default table path of tables in default database should depend on the location of default database *** FAILED *** (15 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
```
```
UtilsSuite:
- resolveURIs with multiple paths *** FAILED *** (0 milliseconds)
".../jar3,file:/C:/pi.py[%23]py.pi,file:/C:/path%..." did not equal ".../jar3,file:/C:/pi.py[#]py.pi,file:/C:/path%..." (UtilsSuite.scala:468)
```
```
CheckpointSuite:
- recovery with file input stream *** FAILED *** (10 seconds, 205 milliseconds)
The code passed to eventually never returned normally. Attempted 660 times over 10.014272499999999 seconds. Last failure message: Unexpected internal error near index 1
\
^. (CheckpointSuite.scala:680)
```
## How was this patch tested?
Manually via AppVeyor as below:
**Scala - aborted tests**
```
WindowQuerySuite - all passed
OrcSourceSuite:
- SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds)
org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625)
ParquetMetastoreSuite - all passed
ParquetSourceSuite - all passed
KafkaRDDSuite - all passed
DirectKafkaStreamSuite - all passed
ReliableKafkaStreamSuite - all passed
KafkaStreamSuite - all passed
KafkaClusterSuite - all passed
DirectKafkaStreamSuite - all passed
KafkaRDDSuite - all passed
```
**Java - failed tests**
```
org.apache.spark.streaming.kafka.JavaKafkaRDDSuite - all passed
org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka.JavaKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite - all passed
```
**Scala - failed tests**
```
PartitionProviderCompatibilitySuite:
- insert overwrite partition of new datasource table overwrites just partition (1 second, 953 milliseconds)
- SPARK-18635 special chars in partition values - partition management true (6 seconds, 31 milliseconds)
- SPARK-18635 special chars in partition values - partition management false (4 seconds, 578 milliseconds)
```
```
UtilsSuite:
- reading offset bytes of a file (compressed) (203 milliseconds)
- reading offset bytes across multiple files (compressed) (0 milliseconds)
```
```
StatisticsSuite:
- MetastoreRelations fallback to HDFS for size estimation (94 milliseconds)
```
```
SQLQuerySuite:
- permanent UDTF (407 milliseconds)
- describe functions - user defined functions (441 milliseconds)
- CTAS without serde with location (2 seconds, 831 milliseconds)
- derived from Hive query file: drop_database_removes_partition_dirs.q (734 milliseconds)
- derived from Hive query file: drop_table_removes_partition_dirs.q (563 milliseconds)
- SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH (453 milliseconds)
```
```
HiveDDLSuite:
- drop external tables in default database (3 seconds, 5 milliseconds)
- add/drop partitions - external table (2 seconds, 750 milliseconds)
- create/drop database - location without pre-created directory (500 milliseconds)
- create/drop database - location with pre-created directory (407 milliseconds)
- drop database containing tables - CASCADE (453 milliseconds)
- drop an empty database - CASCADE (375 milliseconds)
- drop database containing tables - RESTRICT (328 milliseconds)
- drop an empty database - RESTRICT (391 milliseconds)
- CREATE TABLE LIKE an external data source table (953 milliseconds)
- CREATE TABLE LIKE an external Hive serde table (3 seconds, 782 milliseconds)
- desc table for data source table - no user-defined schema (1 second, 150 milliseconds)
```
```
MetastoreDataSourcesSuite
- CTAS: persisted bucketed data source table (875 milliseconds)
```
```
ShowCreateTableSuite:
- simple external hive table (78 milliseconds)
```
```
PartitionedTablePerfStatsSuite:
- hive table: partitioned pruned table reports only selected files (1 second, 109 milliseconds)
- datasource table: partitioned pruned table reports only selected files (860 milliseconds)
- hive table: lazy partition pruning reads only necessary partition data (859 milliseconds)
- datasource table: lazy partition pruning reads only necessary partition data (1 second, 219 milliseconds)
- hive table: lazy partition pruning with file status caching enabled (875 milliseconds)
- datasource table: lazy partition pruning with file status caching enabled (890 milliseconds)
- hive table: file status caching respects refresh table and refreshByPath (922 milliseconds)
- datasource table: file status caching respects refresh table and refreshByPath (640 milliseconds)
- hive table: file status cache respects size limit (469 milliseconds)
- datasource table: file status cache respects size limit (453 milliseconds)
- datasource table: table setup does not scan filesystem (328 milliseconds)
- hive table: table setup does not scan filesystem (313 milliseconds)
- hive table: num hive client calls does not scale with partition count (5 seconds, 431 milliseconds)
- datasource table: num hive client calls does not scale with partition count (4 seconds, 79 milliseconds)
- hive table: files read and cached when filesource partition management is off (656 milliseconds)
- datasource table: all partition data cached in memory when partition management is off (484 milliseconds)
- SPARK-18700: table loaded only once even when resolved concurrently (2 seconds, 578 milliseconds)
```
```
HiveSparkSubmitSuite:
- temporary Hive UDF: define a UDF and use it (1 second, 745 milliseconds)
- permanent Hive UDF: define a UDF and use it (406 milliseconds)
- permanent Hive UDF: use a already defined permanent function (375 milliseconds)
- SPARK-8368: includes jars passed in through --jars (391 milliseconds)
- SPARK-8020: set sql conf in spark conf (156 milliseconds)
- SPARK-8489: MissingRequirementError during reflection (187 milliseconds)
- SPARK-9757 Persist Parquet relation with decimal column (157 milliseconds)
- SPARK-11009 fix wrong result of Window function in cluster mode (156 milliseconds)
- SPARK-14244 fix window partition size attribute binding failure (156 milliseconds)
- set spark.sql.warehouse.dir (172 milliseconds)
- set hive.metastore.warehouse.dir (156 milliseconds)
- SPARK-16901: set javax.jdo.option.ConnectionURL (157 milliseconds)
- SPARK-18360: default table path of tables in default database should depend on the location of default database (172 milliseconds)
```
```
UtilsSuite:
- resolveURIs with multiple paths (0 milliseconds)
```
```
CheckpointSuite:
- recovery with file input stream (4 seconds, 452 milliseconds)
```
Note: after resolving the aborted tests, there is a test failure identified as below:
```
OrcSourceSuite:
- SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds)
org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625)
```
This does not look due to this problem so this PR does not fix it here.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#16451 from HyukjinKwon/all-path-resource-fixes.
## What changes were proposed in this pull request?
There are many locations in the Spark repo where the same word occurs consecutively. Sometimes they are appropriately placed, but many times they are not. This PR removes the inappropriately duplicated words.
## How was this patch tested?
N/A since only docs or comments were updated.
Author: Niranjan Padmanabhan <niranjan.padmanabhan@gmail.com>
Closes#16455 from neurons/np.structure_streaming_doc.
## What changes were proposed in this pull request?
This PR is an inheritance from #16000, and is a completion of #15904.
**Description**
- Augment the `org.apache.spark.status.api.v1` package for serving streaming information.
- Retrieve the streaming information through StreamingJobProgressListener.
> this api should cover exceptly the same amount of information as you can get from the web interface
> the implementation is base on the current REST implementation of spark-core
> and will be available for running applications only
>
> https://issues.apache.org/jira/browse/SPARK-18537
## How was this patch tested?
Local test.
Author: saturday_s <shi.indetail@gmail.com>
Author: Chan Chor Pang <ChorPang.Chan@access-company.com>
Author: peterCPChan <universknight@gmail.com>
Closes#16253 from saturday-shi/SPARK-18537.
Remove spark-tag's compile-scope dependency (and, indirectly, spark-core's compile-scope transitive-dependency) on scalatest by splitting test-oriented tags into spark-tags' test JAR.
Alternative to #16303.
Author: Ryan Williams <ryan.blake.williams@gmail.com>
Closes#16311 from ryan-williams/tt.
## What changes were proposed in this pull request?
The issue in this test is the cleanup of RDDs may not be able to finish before stopping StreamingContext. This PR basically just puts the assertions into `eventually` and runs it before stopping StreamingContext.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16362 from zsxwing/SPARK-18954.
## What changes were proposed in this pull request?
The failure is because in `test("basic functionality")`, it doesn't block until `ExecutorAllocationManager.manageAllocation` is called. This PR just adds StreamManualClock to allow the tests to block on expected wait time to make the test deterministic.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16321 from zsxwing/SPARK-18031.
## What changes were proposed in this pull request?
This patch bumps master branch version to 2.2.0-SNAPSHOT.
## How was this patch tested?
N/A
Author: Reynold Xin <rxin@databricks.com>
Closes#16126 from rxin/SPARK-18695.
## What changes were proposed in this pull request?
Avoid to create multiple threads to stop StreamingContext. Otherwise, the latch added in #16091 can be passed too early.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16105 from zsxwing/SPARK-18617-2.
## What changes were proposed in this pull request?
Fixed the potential SparkContext leak in `StreamingContextSuite.SPARK-18560 Receiver data should be deserialized properly` which was added in #16052. I also removed FakeByteArrayReceiver and used TestReceiver directly.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16091 from zsxwing/SPARK-18617-follow-up.
## What changes were proposed in this pull request?
#15992 provided a solution to fix the bug, i.e. **receiver data can not be deserialized properly**. As zsxwing said, it is a critical bug, but we should not break APIs between maintenance releases. It may be a rational choice to close auto pick kryo serializer for Spark Streaming in the first step. I will continue #15992 to optimize the solution.
## How was this patch tested?
existing ut
Author: uncleGen <hustyugm@gmail.com>
Closes#16052 from uncleGen/SPARK-18617.
## What changes were proposed in this pull request?
This PR make `sbt unidoc` complete with Java 8.
This PR roughly includes several fixes as below:
- Fix unrecognisable class and method links in javadoc by changing it from `[[..]]` to `` `...` ``
```diff
- * A column that will be computed based on the data in a [[DataFrame]].
+ * A column that will be computed based on the data in a `DataFrame`.
```
- Fix throws annotations so that they are recognisable in javadoc
- Fix URL links to `<a href="http..."></a>`.
```diff
- * [[http://en.wikipedia.org/wiki/Decision_tree_learning Decision tree]] model for regression.
+ * <a href="http://en.wikipedia.org/wiki/Decision_tree_learning">
+ * Decision tree (Wikipedia)</a> model for regression.
```
```diff
- * see http://en.wikipedia.org/wiki/Receiver_operating_characteristic
+ * see <a href="http://en.wikipedia.org/wiki/Receiver_operating_characteristic">
+ * Receiver operating characteristic (Wikipedia)</a>
```
- Fix < to > to
- `greater than`/`greater than or equal to` or `less than`/`less than or equal to` where applicable.
- Wrap it with `{{{...}}}` to print them in javadoc or use `{code ...}` or `{literal ..}`. Please refer https://github.com/apache/spark/pull/16013#discussion_r89665558
- Fix `</p>` complaint
## How was this patch tested?
Manually tested by `jekyll build` with Java 7 and 8
```
java version "1.7.0_80"
Java(TM) SE Runtime Environment (build 1.7.0_80-b15)
Java HotSpot(TM) 64-Bit Server VM (build 24.80-b11, mixed mode)
```
```
java version "1.8.0_45"
Java(TM) SE Runtime Environment (build 1.8.0_45-b14)
Java HotSpot(TM) 64-Bit Server VM (build 25.45-b02, mixed mode)
```
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#16013 from HyukjinKwon/SPARK-3359-errors-more.
Added RDD batch time as an input parameter to the update function in updateStateByKey.
Author: Aaditya Ramesh <aramesh@conviva.com>
Closes#11122 from aramesh117/SPARK-13027.
## What changes were proposed in this pull request?
This is a follow-up work of #15618.
Close file source;
For any newly created streaming context outside the withContext, explicitly close the context.
## How was this patch tested?
Existing unit tests.
Author: wm624@hotmail.com <wm624@hotmail.com>
Closes#15818 from wangmiao1981/rtest.
## What changes were proposed in this pull request?
This PR port RDD API to use commit protocol, the changes made here:
1. Add new internal helper class that saves an RDD using a Hadoop OutputFormat named `SparkNewHadoopWriter`, it's similar with `SparkHadoopWriter` but uses commit protocol. This class supports the newer `mapreduce` API, instead of the old `mapred` API which is supported by `SparkHadoopWriter`;
2. Rewrite `PairRDDFunctions.saveAsNewAPIHadoopDataset` function, so it uses commit protocol now.
## How was this patch tested?
Exsiting test cases.
Author: jiangxingbo <jiangxb1987@gmail.com>
Closes#15769 from jiangxb1987/rdd-commit.
## What changes were proposed in this pull request?
Close `FileStreams`, `ZipFiles` etc to release the resources after using. Not closing the resources will cause IO Exception to be raised while deleting temp files.
## How was this patch tested?
Existing tests
Author: U-FAREAST\tl <tl@microsoft.com>
Author: hyukjinkwon <gurwls223@gmail.com>
Author: Tao LI <tl@microsoft.com>
Closes#15618 from HyukjinKwon/SPARK-14914-1.
## What changes were proposed in this pull request?
Fix `Locale.US` for all usages of `DateFormat`, `NumberFormat`
## How was this patch tested?
Existing tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#15610 from srowen/SPARK-18076.
## What changes were proposed in this pull request?
Removing `appUIAddress` attribute since it is no longer in use.
## How was this patch tested?
Local build
Author: Jacek Laskowski <jacek@japila.pl>
Closes#15603 from jaceklaskowski/sparkui-fixes.
## What changes were proposed in this pull request?
When the Python process is dead, the JVM StreamingContext is still running. Hence we will see a lot of Py4jException before the JVM process exits. It's better to stop the JVM StreamingContext to avoid those annoying logs.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#15201 from zsxwing/stop-jvm-ssc.
## What changes were proposed in this pull request?
We are killing multiple executors together instead of iterating over expensive RPC calls to kill single executor.
## How was this patch tested?
Executed sample spark job to observe executors being killed/removed with dynamic allocation enabled.
Author: Dhruve Ashar <dashar@yahoo-inc.com>
Author: Dhruve Ashar <dhruveashar@gmail.com>
Closes#15152 from dhruve/impr/SPARK-17365.
The goal of this feature is to allow the Spark driver to run in an
isolated environment, such as a docker container, and be able to use
the host's port forwarding mechanism to be able to accept connections
from the outside world.
The change is restricted to the driver: there is no support for achieving
the same thing on executors (or the YARN AM for that matter). Those still
need full access to the outside world so that, for example, connections
can be made to an executor's block manager.
The core of the change is simple: add a new configuration that tells what's
the address the driver should bind to, which can be different than the address
it advertises to executors (spark.driver.host). Everything else is plumbing
the new configuration where it's needed.
To use the feature, the host starting the container needs to set up the
driver's port range to fall into a range that is being forwarded; this
required the block manager port to need a special configuration just for
the driver, which falls back to the existing spark.blockManager.port when
not set. This way, users can modify the driver settings without affecting
the executors; it would theoretically be nice to also have different
retry counts for driver and executors, but given that docker (at least)
allows forwarding port ranges, we can probably live without that for now.
Because of the nature of the feature it's kinda hard to add unit tests;
I just added a simple one to make sure the configuration works.
This was tested with a docker image running spark-shell with the following
command:
docker blah blah blah \
-p 38000-38100:38000-38100 \
[image] \
spark-shell \
--num-executors 3 \
--conf spark.shuffle.service.enabled=false \
--conf spark.dynamicAllocation.enabled=false \
--conf spark.driver.host=[host's address] \
--conf spark.driver.port=38000 \
--conf spark.driver.blockManager.port=38020 \
--conf spark.ui.port=38040
Running on YARN; verified the driver works, executors start up and listen
on ephemeral ports (instead of using the driver's config), and that caching
and shuffling (without the shuffle service) works. Clicked through the UI
to make sure all pages (including executor thread dumps) worked. Also tested
apps without docker, and ran unit tests.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#15120 from vanzin/SPARK-4563.
## What changes were proposed in this pull request?
We should generally use `ArrayBuffer.+=(A)` rather than `ArrayBuffer.append(A)`, because `append(A)` would involve extra boxing / unboxing.
## How was this patch tested?
N/A
Author: Liwei Lin <lwlin7@gmail.com>
Closes#14914 from lw-lin/append_to_plus_eq_v2.
## What changes were proposed in this pull request?
This patch fixes a `java.io.StreamCorruptedException` error affecting remote reads of cached values when certain data types are used. The problem stems from #11801 / SPARK-13990, a patch to have Spark automatically pick the "best" serializer when caching RDDs. If PySpark cached a PythonRDD, then this would be cached as an `RDD[Array[Byte]]` and the automatic serializer selection would pick KryoSerializer for replication and block transfer. However, the `getRemoteValues()` / `getRemoteBytes()` code path did not pass proper class tags in order to enable the same serializer to be used during deserialization, causing Java to be inappropriately used instead of Kryo, leading to the StreamCorruptedException.
We already fixed a similar bug in #14311, which dealt with similar issues in block replication. Prior to that patch, it seems that we had no tests to ensure that block replication actually succeeded. Similarly, prior to this bug fix patch it looks like we had no tests to perform remote reads of cached data, which is why this bug was able to remain latent for so long.
This patch addresses the bug by modifying `BlockManager`'s `get()` and `getRemoteValues()` methods to accept ClassTags, allowing the proper class tag to be threaded in the `getOrElseUpdate` code path (which is used by `rdd.iterator`)
## How was this patch tested?
Extended the caching tests in `DistributedSuite` to exercise the `getRemoteValues` path, plus manual testing to verify that the PySpark bug reproduction in SPARK-17110 is fixed.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#14952 from JoshRosen/SPARK-17110.
## What changes were proposed in this pull request?
Improved the code quality of spark by replacing all pattern match on boolean value by if/else block.
## How was this patch tested?
By running the tests
Author: Shivansh <shiv4nsh@gmail.com>
Closes#14873 from shiv4nsh/SPARK-17308.
https://issues.apache.org/jira/browse/SPARK-17038
## What changes were proposed in this pull request?
StreamingSource's lastReceivedBatch_submissionTime, lastReceivedBatch_processingTimeStart, and lastReceivedBatch_processingTimeEnd all use data from lastCompletedBatch instead of lastReceivedBatch.
In particular, this makes it impossible to match lastReceivedBatch_records with a batchID/submission time.
This is apparent when looking at StreamingSource.scala, lines 89-94.
## How was this patch tested?
Manually running unit tests on local laptop
Author: Xin Ren <iamshrek@126.com>
Closes#14681 from keypointt/SPARK-17038.
A review of the code, working back from Hadoop's `FileSystem.exists()` and `FileSystem.isDirectory()` code, then removing uses of the calls when superfluous.
1. delete is harmless if called on a nonexistent path, so don't do any checks before deletes
1. any `FileSystem.exists()` check before `getFileStatus()` or `open()` is superfluous as the operation itself does the check. Instead the `FileNotFoundException` is caught and triggers the downgraded path. When a `FileNotFoundException` was thrown before, the code still creates a new FNFE with the error messages. Though now the inner exceptions are nested, for easier diagnostics.
Initially, relying on Jenkins test runs.
One troublespot here is that some of the codepaths are clearly error situations; it's not clear that they have coverage anyway. Trying to create the failure conditions in tests would be ideal, but it will also be hard.
Author: Steve Loughran <stevel@apache.org>
Closes#14371 from steveloughran/cloud/SPARK-16736-superfluous-fs-calls.
## What changes were proposed in this pull request?
Avoid using postfix operation for command execution in SQLQuerySuite where it wasn't whitelisted and audit existing whitelistings removing postfix operators from most places. Some notable places where postfix operation remains is in the XML parsing & time units (seconds, millis, etc.) where it arguably can improve readability.
## How was this patch tested?
Existing tests.
Author: Holden Karau <holden@us.ibm.com>
Closes#14407 from holdenk/SPARK-16779.
## What changes were proposed in this pull request?
Moved `asScala` to a `map` to avoid NPE.
## How was this patch tested?
Existing unit tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#14443 from zsxwing/SPARK-15869.
## 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?
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?
This PR moves `ssc.stop()` into `finally` for `StreamingContextSuite.createValidCheckpoint` to avoid leaking a StreamingContext since leaking a StreamingContext will fail a lot of tests and make us hard to find the real failure one.
## How was this patch tested?
Jenkins unit tests
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#14354 from zsxwing/ssc-leak.
## 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?
In `JobGenerator`, the code reads like that some batches might not get marked as fully processed. In the following flowchart, the batch should get marked fully processed before endpoint C however it is not. Currently, this does not actually cause an issue, as the condition `(time - zeroTime) is multiple of checkpoint duration?` always evaluates to `true` as the `checkpoint duration` is always set to be equal to the `batch duration`.
This PR fixes this issue so as to improve code readability and to avoid any potential issue in case there is any future change making checkpoint duration to be set different from batch duration.
Author: Ahmed Mahran <ahmed.mahran@mashin.io>
Closes#14145 from ahmed-mahran/b-mark-batch-fully-processed.
## What changes were proposed in this pull request?
Begin failing if checkpoint writes will likely keep up with storage's ability to write them, to fail fast instead of slowly filling memory
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#14152 from srowen/SPARK-16395.
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?
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?
Replace use of `commons-lang` in favor of `commons-lang3` and forbid the former via scalastyle; remove `NotImplementedException` from `comons-lang` in favor of JDK `UnsupportedOperationException`
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#13843 from srowen/SPARK-16129.
## What changes were proposed in this pull request?
In `ReceiverSuite.scala`, in the test case "write ahead log - generating and cleaning", the inner method `getCurrentLogFiles` uses external variable `logDirectory1` instead of the passed parameter `logDirectory`. This PR fixes this by using the passed method argument instead of variable from the outer scope.
## How was this patch tested?
The unit test was re-run and the output logs were checked for the correct paths used.
tdas
Author: Ahmed Mahran <ahmed.mahran@mashin.io>
Closes#13825 from ahmed-mahran/b-receiver-suite-wal-gen-cln.
## What changes were proposed in this pull request?
- Deprecate old Java accumulator API; should use Scala now
- Update Java tests and examples
- Don't bother testing old accumulator API in Java 8 (too)
- (fix a misspelling too)
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#13606 from srowen/SPARK-15086.
