Tobias noted today on the mailing list:
========
I am trying to use Spark Streaming with Kafka, which works like a
charm – except for shutdown. When I run my program with "sbt
run-main", sbt will never exit, because there are two non-daemon
threads left that don't die.
I created a minimal example at
<https://gist.github.com/tgpfeiffer/b1e765064e983449c6b6#file-kafkadoesntshutdown-scala>.
It starts a StreamingContext and does nothing more than connecting to
a Kafka server and printing what it receives. Using the `future
Unknown macro: { ... }
` construct, I shut down the StreamingContext after some seconds and
then print the difference between the threads at start time and at end
time. The output can be found at
<https://gist.github.com/tgpfeiffer/b1e765064e983449c6b6#file-output1>.
There are a number of threads remaining that will prevent sbt from
exiting.
When I replace `KafkaUtils.createStream(...)` with a call that does
exactly the same, except that it calls `consumerConnector.shutdown()`
in `KafkaReceiver.onStop()` (which it should, IMO), the output is as
shown at <https://gist.github.com/tgpfeiffer/b1e765064e983449c6b6#file-output2>.
Does anyone have any idea what is going on here and why the program
doesn't shut down properly? The behavior is the same with both kafka
0.8.0 and 0.8.1.1, by the way.
========
Something similar was noted last year:
http://mail-archives.apache.org/mod_mbox/spark-dev/201309.mbox/%3C1380220041.2428.YahooMailNeo@web160804.mail.bf1.yahoo.com%3E
KafkaInputDStream doesn't close `ConsumerConnector` in `onStop()`, and does not close the `Executor` it creates. The latter leaves non-daemon threads and can prevent the JVM from shutting down even if streaming is closed properly.
Author: Sean Owen <sowen@cloudera.com>
Closes#980 from srowen/SPARK-2034 and squashes the following commits:
9f31a8d [Sean Owen] Restore ClassTag to private class because MIMA flags it; is the shadowing intended?
2d579a8 [Sean Owen] Close ConsumerConnector in onStop; shutdown() the local Executor that is created so that its threads stop when done; close the Zookeeper client even on exception; fix a few typos; log exceptions that otherwise vanish
Author: Takuya UESHIN <ueshin@happy-camper.st>
Closes#974 from ueshin/issues/SPARK-2029 and squashes the following commits:
e19e8f4 [Takuya UESHIN] Bump version number to 1.1.0-SNAPSHOT.
This is a few changes based on the original patch by @scrapcodes.
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes#785 from pwendell/package-docs and squashes the following commits:
c32b731 [Patrick Wendell] Changes based on Prashant's patch
c0463d3 [Prashant Sharma] added eof new line
ce8bf73 [Prashant Sharma] Added eof new line to all files.
4c35f2e [Prashant Sharma] SPARK-1563 Add package-info.java and package.scala files for all packages that appear in docs
Three issues related to temp files that tests generate – these should be touched up for hygiene but are not urgent.
Modules have a log4j.properties which directs the unit-test.log output file to a directory like `[module]/target/unit-test.log`. But this ends up creating `[module]/[module]/target/unit-test.log` instead of former.
The `work/` directory is not deleted by "mvn clean", in the parent and in modules. Neither is the `checkpoint/` directory created under the various external modules.
Many tests create a temp directory, which is not usually deleted. This can be largely resolved by calling `deleteOnExit()` at creation and trying to call `Utils.deleteRecursively` consistently to clean up, sometimes in an `@After` method.
_If anyone seconds the motion, I can create a more significant change that introduces a new test trait along the lines of `LocalSparkContext`, which provides management of temp directories for subclasses to take advantage of._
Author: Sean Owen <sowen@cloudera.com>
Closes#732 from srowen/SPARK-1798 and squashes the following commits:
5af578e [Sean Owen] Try to consistently delete test temp dirs and files, and set deleteOnExit() for each
b21b356 [Sean Owen] Remove work/ and checkpoint/ dirs with mvn clean
bdd0f41 [Sean Owen] Remove duplicate module dir in log4j.properties output path for tests
The current Network Receiver API makes it slightly complicated to right a new receiver as one needs to create an instance of BlockGenerator as shown in SocketReceiver
https://github.com/apache/spark/blob/master/streaming/src/main/scala/org/apache/spark/streaming/dstream/SocketInputDStream.scala#L51
Exposing the BlockGenerator interface has made it harder to improve the receiving process. The API of NetworkReceiver (which was not a very stable API anyways) needs to be change if we are to ensure future stability.
Additionally, the functions like streamingContext.socketStream that create input streams, return DStream objects. That makes it hard to expose functionality (say, rate limits) unique to input dstreams. They should return InputDStream or NetworkInputDStream. This is still not yet implemented.
This PR is blocked on the graceful shutdown PR #247
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#300 from tdas/network-receiver-api and squashes the following commits:
ea27b38 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into network-receiver-api
3a4777c [Tathagata Das] Renamed NetworkInputDStream to ReceiverInputDStream, and ActorReceiver related stuff.
838dd39 [Tathagata Das] Added more events to the StreamingListener to report errors and stopped receivers.
a75c7a6 [Tathagata Das] Address some PR comments and fixed other issues.
91bfa72 [Tathagata Das] Fixed bugs.
8533094 [Tathagata Das] Scala style fixes.
028bde6 [Tathagata Das] Further refactored receiver to allow restarting of a receiver.
43f5290 [Tathagata Das] Made functions that create input streams return InputDStream and NetworkInputDStream, for both Scala and Java.
2c94579 [Tathagata Das] Fixed graceful shutdown by removing interrupts on receiving thread.
9e37a0b [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into network-receiver-api
3223e95 [Tathagata Das] Refactored the code that runs the NetworkReceiver into further classes and traits to make them more testable.
a36cc48 [Tathagata Das] Refactored the NetworkReceiver API for future stability.
Author: Sandy Ryza <sandy@cloudera.com>
Closes#91 from sryza/sandy-spark-1193 and squashes the following commits:
a878124 [Sandy Ryza] SPARK-1193. Fix indentation in pom.xmls
This lets us explicitly include Avro based on a profile for 0.23.X
builds. It makes me sad how convoluted it is to express this logic
in Maven. @tgraves and @sryza curious if this works for you.
I'm also considering just reverting to how it was before. The only
real problem was that Spark advertised a dependency on Avro
even though it only really depends transitively on Avro through
other deps.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#49 from pwendell/avro-build-fix and squashes the following commits:
8d6ee92 [Patrick Wendell] SPARK-1121: Add avro to yarn-alpha profile
This removes some loose ends not caught by the other (incubating -> tlp) patches. @markhamstra this updates the version as you mentioned earlier.
Author: Patrick Wendell <pwendell@gmail.com>
Closes#51 from pwendell/tlp and squashes the following commits:
d553b1b [Patrick Wendell] Remove remaining references to incubation
Prompted by a recent thread on the mailing list, I tried and failed to see if Spark can be made independent of log4j. There are a few cases where control of the underlying logging is pretty useful, and to do that, you have to bind to a specific logger.
Instead I propose some tidying that leaves Spark's use of log4j, but gets rid of warnings and should still enable downstream users to switch. The idea is to pipe everything (except log4j) through SLF4J, and have Spark use SLF4J directly when logging, and where Spark needs to output info (REPL and tests), bind from SLF4J to log4j.
This leaves the same behavior in Spark. It means that downstream users who want to use something except log4j should:
- Exclude dependencies on log4j, slf4j-log4j12 from Spark
- Include dependency on log4j-over-slf4j
- Include dependency on another logger X, and another slf4j-X
- Recreate any log config that Spark does, that is needed, in the other logger's config
That sounds about right.
Here are the key changes:
- Include the jcl-over-slf4j shim everywhere by depending on it in core.
- Exclude dependencies on commons-logging from third-party libraries.
- Include the jul-to-slf4j shim everywhere by depending on it in core.
- Exclude slf4j-* dependencies from third-party libraries to prevent collision or warnings
- Added missing slf4j-log4j12 binding to GraphX, Bagel module tests
And minor/incidental changes:
- Update to SLF4J 1.7.5, which happily matches Hadoop 2’s version and is a recommended update over 1.7.2
- (Remove a duplicate HBase dependency declaration in SparkBuild.scala)
- (Remove a duplicate mockito dependency declaration that was causing warnings and bugging me)
Author: Sean Owen <sowen@cloudera.com>
Closes#570 from srowen/SPARK-1071 and squashes the following commits:
52eac9f [Sean Owen] Add slf4j-over-log4j12 dependency to core (non-test) and remove it from things that depend on core.
77a7fa9 [Sean Owen] SPARK-1071: Tidy logging strategy and use of log4j
Version number to 1.0.0-SNAPSHOT
Since 0.9.0-incubating is done and out the door, we shouldn't be building 0.9.0-incubating-SNAPSHOT anymore.
@pwendell
Author: Mark Hamstra <markhamstra@gmail.com>
== Merge branch commits ==
commit 1b00a8a7c1a7f251b4bb3774b84b9e64758eaa71
Author: Mark Hamstra <markhamstra@gmail.com>
Date: Wed Feb 5 09:30:32 2014 -0800
Version number to 1.0.0-SNAPSHOT
