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From "Zhijiang(wangzhijiang999)" <wangzhijiang...@aliyun.com>
Subject 回复:Kryo Serialization Issue
Date Tue, 28 Aug 2018 10:01:37 GMT
Hi,

How do you reduce the speed to avoid this issue? Do you mean reducing the parallelism of source
or downstream tasks? 
As I know, data buffering is managed by flink internal buffer pool and memory manager, so
it will not cause OOM issue.
I just wonder the OOM may be caused by temporary byte buffers in record serializers. If the
record size is large and the downstream parallelism is large, it may cause OOM issue in serialization.
Could you show the stack of OOM part? If it is this case,  the following [1] can solve it
and it is working in progress.

Zhijiang

[1] https://issues.apache.org/jira/browse/FLINK-9913
------------------------------------------------------------------
发件人:Darshan Singh <darshan.meel@gmail.com>
发送时间:2018年8月28日(星期二) 00:16
收件人:walterddr <walterddr@gmail.com>
抄 送:user <user@flink.apache.org>
主 题:Re: Kryo Serialization Issue

Thanks,  We ran into differnet errors and then realized it was OOM issue which was causing
different parts to be failed. 
Flink was buffering too much data as we were reading too fast from source. Reducing the speed
fixed the issue.

However, I am curious how to achieve the same with S3 apart from limiting the number of files
to read at same time.

Thanks

On Sun, Aug 26, 2018 at 5:32 PM Rong Rong <walterddr@gmail.com> wrote:
This seems to be irrelevant to the issue for KyroSerializer in recent discussions [1]. which
has been fixed in 1.4.3, 1.5.0 and 1.6.0.
On a quick glance, this might have been a corrupted message in your decoding, for example
a malformed JSON string.

--
Rong

[1] https://issues.apache.org/jira/browse/FLINK-8836

On Wed, Aug 22, 2018 at 8:41 AM Darshan Singh <darshan.meel@gmail.com> wrote:
Hi,

I am using a map function on a data stream which has 1 column i.e. a json string. Map function
simply uses Jackson mapper and convert the String to ObjectNode and also assign key based
on one of the value in Object node.

The code seems to work fine for 2-3 minutes as expected and then suddenly it fails with below
error. I looked at the mailing list and most of the issues mentioned that it was fixed in
1.5.0 and I am using 1.6.0 so not sure what needs to do.

Just wanted to know if we will need to write our own Serializer for ObjectNode to fix this
issue or there is some setting we are missing.

Thanks

ava.lang.IndexOutOfBoundsException: Index: 49, Size: 0
 at java.util.ArrayList.rangeCheck(ArrayList.java:657)
 at java.util.ArrayList.get(ArrayList.java:433)
 at com.esotericsoftware.kryo.util.MapReferenceResolver.getReadObject(MapReferenceResolver.java:42)
 at com.esotericsoftware.kryo.Kryo.readReferenceOrNull(Kryo.java:805)
 at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:759)
 at org.apache.flink.api.java.typeutils.runtime.kryo.KryoSerializer.deserialize(KryoSerializer.java:315)
 at org.apache.flink.api.java.typeutils.runtime.TupleSerializer.deserialize(TupleSerializer.java:136)
 at org.apache.flink.api.java.typeutils.runtime.TupleSerializer.deserialize(TupleSerializer.java:30)
 at org.apache.flink.streaming.runtime.streamrecord.StreamElementSerializer.deserialize(StreamElementSerializer.java:207)
 at org.apache.flink.streaming.runtime.streamrecord.StreamElementSerializer.deserialize(StreamElementSerializer.java:49)
 at org.apache.flink.runtime.plugable.NonReusingDeserializationDelegate.read(NonReusingDeserializationDelegate.java:55)
 at org.apache.flink.runtime.io.network.api.serialization.SpillingAdaptiveSpanningRecordDeserializer.getNextRecord(SpillingAdaptiveSpanningRecordDeserializer.java:140)
 at org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:172)
 at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:105)
 at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:300)
 at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711)
 at java.lang.Thread.run(Thread.java:748)



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