One more point to add.
I disabled checkpoints (by commenting out code that calls
enableCheckpointing()) and re-ran the job this time with plenty of memory
to the job manager
~/flink-1.3.2/bin/yarn-session.sh -n 4 -jm 24576 -tm 24576 -s 2 -d
At the Jobmanager, I am still hitting:
2017-09-25 06:46:44,066 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner - Starting
YARN ApplicationMaster / ResourceManager / JobManager (Version: 1.3.2,
Rev:0399bee, Date:03.08.2017 @ 10:23:11 UTC)
2017-09-25 06:46:44,066 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner - Current
user: flink
2017-09-25 06:46:44,066 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner - JVM:
OpenJDK 64-Bit Server VM - Oracle Corporation - 1.8/25.131-b11
2017-09-25 06:46:44,066 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner - Maximum
heap size: 16384 MiBytes
2017-09-25 06:46:44,066 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner - JAVA_HOME:
/usr/lib/jvm/java-8-openjdk-amd64
2017-09-25 06:46:44,067 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner - Hadoop
version: 2.7.2
2017-09-25 06:46:44,067 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner - JVM
Options:
2017-09-25 06:46:44,067 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner -
-Xmx18432m
2017-09-25 06:46:44,067 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner -
-Dlog.file=/var/log/hadoop-yarn/userlogs/application_1506317793012_0001/container_1506317793012_0001_01_000001/jobmanager.log
2017-09-25 06:46:44,067 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner -
-Dlogback.configurationFile=file:logback.xml
2017-09-25 06:46:44,067 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner -
-Dlog4j.configuration=file:log4j.properties
2017-09-25 06:46:44,067 INFO
org.apache.flink.yarn.YarnApplicationMasterRunner - Program
Arguments: (none)
.
.
2017-09-25 06:50:51,925 INFO
org.apache.flink.runtime.executiongraph.ExecutionGraph - Source:
Custom Source -> (Filter -> Map -> Map, Filter -> Map -> Map, Filter -> Map
-> Map, Map -> (Filter, Filter)) (2/2) (e27860984c858738f044931e4b6a86a6)
switched from DEPLOYING to RUNNING.
2017-09-25 13:38:54,175 INFO
org.apache.flink.runtime.blob.BlobCache - Created
BLOB cache storage directory
/tmp/blobStore-3e0b96a1-904b-4acb-b0d3-9d88f2073e97
2017-09-25 13:38:54,187 INFO
org.apache.flink.runtime.blob.BlobCache - Downloading
49efe0ad58b727ba145b86df6088111c9a90ddd6 from localhost/127.0.0.1:55550
2017-09-25 16:30:39,974 INFO
org.apache.flink.runtime.executiongraph.ExecutionGraph -
KeyedCEPPatternOperator -> Map (2/2) (e464ec796cd239a7b7fa225aaf86309a)
switched from RUNNING to CANCELED.
2017-09-25 16:30:39,975 INFO
org.apache.flink.runtime.executiongraph.ExecutionGraph - Source:
Custom Source -> (Filter -> Map -> Map, Filter -> Map -> Map, Filter -> Map
-> Map, Map -> (Filter, Filter)) (2/2) (e27860984c858738f044931e4b6a86a6)
switched from RUNNING to FAILED.
java.lang.OutOfMemoryError: GC overhead limit exceeded
at sun.reflect.GeneratedConstructorAccessor10.newInstance(Unknown
Source)
at
sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at
com.twitter.chill.Instantiators$$anonfun$normalJava$1.apply(KryoBase.scala:160)
at
com.twitter.chill.Instantiators$$anon$1.newInstance(KryoBase.scala:123)
at com.esotericsoftware.kryo.Kryo.newInstance(Kryo.java:1061)
at
com.esotericsoftware.kryo.serializers.FieldSerializer.createCopy(FieldSerializer.java:620)
at
com.esotericsoftware.kryo.serializers.FieldSerializer.copy(FieldSerializer.java:624)
at com.esotericsoftware.kryo.Kryo.copy(Kryo.java:862)
at
org.apache.flink.api.java.typeutils.runtime.kryo.KryoSerializer.copy(KryoSerializer.java:176)
at
org.apache.flink.api.java.typeutils.runtime.PojoSerializer.copy(PojoSerializer.java:239)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:526)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:503)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:483)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$BroadcastingOutputCollector.collect(OperatorChain.java:575)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$BroadcastingOutputCollector.collect(OperatorChain.java:536)
at
org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:891)
at
org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:869)
at
org.apache.flink.streaming.api.operators.StreamMap.processElement(StreamMap.java:41)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:528)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:503)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:483)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$BroadcastingOutputCollector.collect(OperatorChain.java:575)
at
org.apache.flink.streaming.runtime.tasks.OperatorChain$BroadcastingOutputCollector.collect(OperatorChain.java:536)
at
org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:891)
On Wed, Sep 27, 2017 at 8:34 AM, Sridhar Chellappa <flinken...@gmail.com>
wrote:
> Here is the snippet :
>
> public interface Rule {
> DataStream<Alert> run();
> }
>
> public class Rule1 implements Rule {
>
> private static final String RULE_ID = "Rule1"
>
> @Override
> public DataStream<Alert> run() {
>
>
> Pattern<MyMessage1, ?> MyMessage1Pattern =
> Pattern.<MyMessage1>begin("first").
> subtype(MyMessage1.class).
> next("second").
> subtype(MyMessage1.class).
> within(Time.minutes(15);
>
> PatternStream<MyMessage1> MyMessage1PatternStream =
> CEP.pattern(
> MyMessage1DataStream.keyBy("field1", "field2"),
> MyMessage1Pattern
> );
>
> return (MyMessage1PatternStream.select(
> new PatternSelectFunction<MyMessage1, Alert>() {
> @Override
> public Alert select(Map<String, List<MyMessage1>>
> pattern) throws Exception {
>
> String alertMessage = String.format("Cep Alert.
> Rule ID : %s" RULE_ID);
>
> return new CEPAlert(alertMessage);
> }
> }
> )
> );
>
> }
>
>
>
> private static List<Rule> getStream1RulesToExecute(DataStream<MyMessage1>
> MyMessage1DataStream) {
> List<Rule> rules = new ArrayList<Rule>();
>
> rules.add(new Rule1(MyMessage1DataStream));
>
> return rules;
> }
>
>
> private static List<Rule> getStream2RulesToExecute(DataStream<MyMessage1>
> MyMessage1DataStream) {
> List<Rule> rules = new ArrayList<Rule>();
>
> rules.add(new Rule2(MyMessage1DataStream));
> return rules;
> }
>
>
> public RichParallelSourceFunction<MyMessage1>
> getStreamSource1(StreamExecutionEnvironment
> env, ParameterTool parameterTool) {
>
>
> env.enableCheckpointing(parameterTool.getInt(CHECKPOINT_INTERVAL,
> DEFAULT_CHECKPOINT_INTERVAL));
> env.getCheckpointConfig().setCheckpointingMode(
> CheckpointingMode.EXACTLY_ONCE);
> env.getCheckpointConfig().setMinPauseBetweenCheckpoints(
> DEFAULT_MIN_PAUSE_BETWEEN_CHECKPOINTS);
> env.getCheckpointConfig().setCheckpointTimeout(
> CheckpointConfig.DEFAULT_TIMEOUT);
> env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);
>
>
> KafkaDataSource<T> flinkCepConsumer =
> new KafkaDataSource<MyMessage1>(parameterTool, new
> MyMessage1SerDeSchema());
>
> return flinkCepConsumer;
> }
>
>
> public RichParallelSourceFunction<MyMessage2>
> getStreamSource2(StreamExecutionEnvironment
> env, ParameterTool parameterTool) {
>
>
> env.enableCheckpointing(parameterTool.getInt(CHECKPOINT_INTERVAL,
> DEFAULT_CHECKPOINT_INTERVAL));
> env.getCheckpointConfig().setCheckpointingMode(
> CheckpointingMode.EXACTLY_ONCE);
> env.getCheckpointConfig().setMinPauseBetweenCheckpoints(
> DEFAULT_MIN_PAUSE_BETWEEN_CHECKPOINTS);
> env.getCheckpointConfig().setCheckpointTimeout(
> CheckpointConfig.DEFAULT_TIMEOUT);
> env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);
>
>
> KafkaDataSource<T> flinkCepConsumer =
> new KafkaDataSource<MyMessage1>(parameterTool, new
> MyMessage2SerDeSchema());
>
> return flinkCepConsumer;
> }
>
>
> public static void main(String[] args) throws Exception {
> ParameterTool parameterTool = ParameterTool.
> fromPropertiesFile(args[PROPS_FILE_ARG_INDEX]);
>
> StreamExecutionEnvironment env = StreamExecutionEnvironment.
> getExecutionEnvironment();
>
> env.getConfig().setGlobalJobParameters(parameterTool);
>
> DataStream<MyMessage1> message1Stream = env.addSource(
> getStreamSource1(env, parameterTool);
> );
>
>
> DataStream<MyMessge2> message2Stream = env.addSource(
> getStreamSource2(env, parameterTool);
> );
>
>
> getStream1RulesToExecute(message1Stream).forEach(rule ->
> rule.run().print());
> getStream2RulesToExecute(message2tream).forEach(rule ->
> rule.run().print());
> env.execute(STREAMING_JOB_NAME);
> }
>
>
>
>
>
>
> On Mon, Sep 25, 2017 at 3:13 PM, Tzu-Li (Gordon) Tai <tzuli...@apache.org>
> wrote:
>
>> I talked a bit with Kostas on what may be happening here.
>>
>> It could be that your patterns are not closing, which depends on the
>> pattern construction of your CEP job.
>> Could you perhaps provide an overview / code snippet of what your CEP job
>> is doing?
>>
>> Looping Kostas (in CC) also to this thread as he may have a better idea
>> what is happening here.
>>
>> Cheers,
>> Gordon
>>
>> On 22 September 2017 at 4:09:07 PM, Sridhar Chellappa (
>> flinken...@gmail.com) wrote:
>>
>> Thanks for the reply. Well, tracing back to the root cause, I see the
>> following:
>>
>> 1. At the Job manager, the Checkpoint times are getting worse :
>>
>> Jobmanager :
>>
>> Checkpoint times are getting worse progressively.
>>
>> 2017-09-16 05:05:50,813 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Triggering checkpoint 1 @ 1505538350809
>> 2017-09-16 05:05:51,396 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Completed checkpoint 1 (11101233 bytes
>> in 586 ms).
>> 2017-09-16 05:07:30,809 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Triggering checkpoint 2 @ 1505538450809
>> 2017-09-16 05:07:31,657 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Completed checkpoint 2 (18070955 bytes
>> in 583 ms).
>>
>> .
>> .
>> .
>> .
>> .
>> .
>> .
>> .
>> .
>> .
>> .
>> .
>> .
>> 2017-09-16 07:32:58,117 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Completed checkpoint 89 (246125113
>> bytes in 27194 ms).
>> 2017-09-16 07:34:10,809 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Triggering checkpoint 90 @
>> 1505547250809
>> 2017-09-16 07:34:44,932 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Completed checkpoint 90 (248272325
>> bytes in 34012 ms).
>> 2017-09-16 07:35:50,809 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Triggering checkpoint 91 @
>> 1505547350809
>> 2017-09-16 07:36:37,058 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Completed checkpoint 91 (250348812
>> bytes in 46136 ms).
>> 2017-09-16 07:37:30,809 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Triggering checkpoint 92 @
>> 1505547450809
>> 2017-09-16 07:38:18,076 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Completed checkpoint 92 (252399724
>> bytes in 47152 ms).
>> 2017-09-16 07:39:10,809 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Triggering checkpoint 93 @
>> 1505547550809
>> 2017-09-16 07:40:13,494 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Completed checkpoint 93 (254374636
>> bytes in 62573 ms).
>> 2017-09-16 07:40:50,809 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Triggering checkpoint 94 @
>> 1505547650809
>> 2017-09-16 07:42:42,850 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Completed checkpoint 94 (256386533
>> bytes in 111898 ms).
>> 2017-09-16 07:42:42,850 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Triggering checkpoint 95 @
>> 1505547762850
>> 2017-09-16 07:46:06,241 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Completed checkpoint 95 (258441766
>> bytes in 203268 ms).
>> 2017-09-16 07:46:06,241 INFO org.apache.flink.runtime.check
>> point.CheckpointCoordinator - Triggering checkpoint 96 @
>> 1505547966241
>> 2017-09-16 07:48:42,069 INFO org.apache.flink.runtime.execu
>> tiongraph.ExecutionGraph - KeyedCEPPatternOperator -> Map (1/4)
>> (ff835faa9eb9182ed2f2230a1e5cc56d) switched from RUNNING to FAILED.
>> AsynchronousException{java.lang.Exception: Could not materialize
>> checkpoint 96 for operator KeyedCEPPatternOperator -> Map (1/4).}
>> at org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncChe
>> ckpointRunnable.run(StreamTask.java:970)
>> at java.util.concurrent.Executors$RunnableAdapter.call(
>> Executors.java:511)
>> at java.util.concurrent.FutureTask.run(FutureTask.java:266)
>> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPool
>> Executor.java:1142)
>> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoo
>> lExecutor.java:617)
>> at java.lang.Thread.run(Thread.java:748)
>> Caused by: java.lang.Exception: Could not materialize checkpoint 96 for
>> operator KeyedCEPPatternOperator -> Map (1/4).
>> ... 6 more
>> Caused by: java.util.concurrent.ExecutionException:
>> java.lang.OutOfMemoryError: GC overhead limit exceeded
>> at java.util.concurrent.FutureTask.report(FutureTask.java:122)
>> at java.util.concurrent.FutureTask.get(FutureTask.java:192)
>> at org.apache.flink.util.FutureUtil.runIfNotDoneAndGet(FutureUt
>> il.java:43)
>> at org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncChe
>> ckpointRunnable.run(StreamTask.java:897)
>> ... 5 more
>>
>>
>> So, it looks like the Job Manager ran out of memory, thanks to the
>> "Progressively Getting Worse" checkpoints. Any ideas on how to make sure
>> the checkpoints faster?
>>
>>
>>
>>
>>
>>
>> On Thu, Sep 21, 2017 at 7:29 PM, Tzu-Li (Gordon) Tai <tzuli...@apache.org
>> > wrote:
>>
>>> Hi Sridhar,
>>>
>>> Sorry that this didn't get a response earlier.
>>>
>>> According to the trace, it seems like the job failed during the process,
>>> and
>>> when trying to automatically restore from a checkpoint, deserialization
>>> of a
>>> CEP `IterativeCondition` object failed. As far as I can tell, CEP
>>> operators
>>> are just using Java serialization on CEP `IterativeCondition` objects, so
>>> should not be related to the protobuf serializer that you are using.
>>>
>>> Is this still constantly happening for you?
>>>
>>> Cheers,
>>> Gordon
>>>
>>>
>>>
>>> --
>>> Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nab
>>> ble.com/
>>>
>>
>>
>
