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Posted to user@flink.apache.org by Yun Gao <yu...@aliyun.com> on 2020/05/22 06:05:56 UTC
回复：Performance issue when writing to HDFS
Hi Kong,
Sorry that I'm not expert of Hadoop, but from the logs and Google, It seems more likely to be a problem of HDFS side [1] ? Like long-time GC in DataNode.
Also I have found a similar issue from the history mails [2], and the conclusion should be similar.
Best,
Yun
[1] https://community.cloudera.com/t5/Support-Questions/Solution-for-quot-slow-readprocessor-quot-warnings/td-p/122046
[2] http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/quot-Slow-ReadProcessor-quot-warnings-when-using-BucketSink-td9427.html
------------------原始邮件 ------------------
发件人:Mu Kong <ko...@gmail.com>
发送时间:Fri May 22 11:16:32 2020
收件人:user <us...@flink.apache.org>
主题:Performance issue when writing to HDFS
Hi all,
I have Flink application consuming from Kafka and writing the data to HDFS bucketed by event time with BucketingSink.
Sometimes, the the traffic gets high and from the prometheus metrics, it shows the writing is not stable.
(getting from flink_taskmanager_job_task_operator_numRecordsOutPerSecond)
The output data on HDFS is also getting delayed. (The records for a certain hour bucket are written to HDFS 50 minutes after that hour)
I looked into the log, and find warning regarding the datanode ack, which might be related:
DFSClient exception:2020-05-21 10:43:10,432 INFO org.apache.hadoop.hdfs.DFSClient - Exception in createBlockOutputStream
java.io.IOException: Got error, status message , ack with firstBadLink as <IP address here>:1004
at org.apache.hadoop.hdfs.protocol.datatransfer.DataTransferProtoUtil.checkBlockOpStatus(DataTransferProtoUtil.java:140)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.createBlockOutputStream(DFSOutputStream.java:1478)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1380)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:558)
Slow ReadProcessor read fields warning:2020-05-21 10:42:30,509 WARN org.apache.hadoop.hdfs.DFSClient - Slow ReadProcessor read fields took 30230ms (threshold=30000ms); ack: seqno: 126 reply: SUCCESS reply: SUCCESS reply: SUCCESS downstreamAckTimeNanos: 372753456 flag: 0 flag: 0 flag: 0, targets: [DatanodeInfoWithStorage[<IP address here>:1004,DS-833b175e-9848-453d-a222-abf5c05d643e,DISK], DatanodeInfoWithStorage[<IP address here>:1004,DS-f998208a-df7b-4c63-9dde-26453ba69559,DISK], DatanodeInfoWithStorage[<IP address here>:1004,DS-4baa6ba6-3951-46f7-a843-62a13e3a62f7,DISK]]
We haven't done any tuning for the Flink job regarding writing to HDFS. Is there any config or optimization we can try to avoid delay and these warnings?
Thanks in advance!!
Best regards,
Mu
Re: Performance issue when writing to HDFS
Posted by Mu Kong <ko...@gmail.com>.
Hi Gao,
Thanks for helping out.
It turns out to be a networking issue of our HDFS datanode.
But I was hoping to find out a way to weaken the impact of such issue.
Things I considered was to shorten the waiting time for a file to close
when there is no incoming data, so that there will be fewer open files on
hdfs.
But I'm not sure if that would work.
Regards,
Mu
On Fri, May 22, 2020 at 3:06 PM Yun Gao <yu...@aliyun.com> wrote:
> Hi Kong,
>
> Sorry that I'm not expert of Hadoop, but from the logs and Google, It
> seems more likely to be a problem of HDFS side [1] ? Like long-time GC in
> DataNode.
>
> Also I have found a similar issue from the history mails [2], and the
> conclusion should be similar.
>
> Best,
> Yun
>
>
> [1]
> https://community.cloudera.com/t5/Support-Questions/Solution-for-quot-slow-readprocessor-quot-warnings/td-p/122046
> [2]
> http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/quot-Slow-ReadProcessor-quot-warnings-when-using-BucketSink-td9427.html
>
>
> ------------------原始邮件 ------------------
> *发件人:*Mu Kong <ko...@gmail.com>
> *发送时间:*Fri May 22 11:16:32 2020
> *收件人:*user <us...@flink.apache.org>
> *主题:*Performance issue when writing to HDFS
>
>> Hi all,
>>
>> I have Flink application consuming from Kafka and writing the data to
>> HDFS bucketed by event time with BucketingSink.
>> Sometimes, the the traffic gets high and from the prometheus metrics, it
>> shows the writing is not stable.
>> [image: image.png]
>> (getting from flink_taskmanager_job_task_operator_numRecordsOutPerSecond)
>>
>> The output data on HDFS is also getting delayed. (The records for a
>> certain hour bucket are written to HDFS 50 minutes after that hour)
>>
>> I looked into the log, and find warning regarding the datanode ack, which
>> might be related:
>>
>> *DFSClient exception:*
>>
>>> 2020-05-21 10:43:10,432 INFO org.apache.hadoop.hdfs.DFSClient
>>> - Exception in createBlockOutputStream
>>> java.io.IOException: Got error, status message , ack with firstBadLink
>>> as <IP address here>:1004
>>> at
>>> org.apache.hadoop.hdfs.protocol.datatransfer.DataTransferProtoUtil.checkBlockOpStatus(DataTransferProtoUtil.java:140)
>>> at
>>> org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.createBlockOutputStream(DFSOutputStream.java:1478)
>>> at
>>> org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1380)
>>> at
>>> org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:558)
>>>
>>
>> * Slow ReadProcessor read fields warning:*
>>
>>> 2020-05-21 10:42:30,509 WARN org.apache.hadoop.hdfs.DFSClient
>>> - Slow ReadProcessor read fields took 30230ms
>>> (threshold=30000ms); ack: seqno: 126 reply: SUCCESS reply: SUCCESS reply:
>>> SUCCESS downstreamAckTimeNanos: 372753456 flag: 0 flag: 0 flag: 0, targets:
>>> [DatanodeInfoWithStorage[<IP address
>>> here>:1004,DS-833b175e-9848-453d-a222-abf5c05d643e,DISK],
>>> DatanodeInfoWithStorage[<IP address
>>> here>:1004,DS-f998208a-df7b-4c63-9dde-26453ba69559,DISK],
>>> DatanodeInfoWithStorage[<IP address
>>> here>:1004,DS-4baa6ba6-3951-46f7-a843-62a13e3a62f7,DISK]]
>>
>>
>>
>> We haven't done any tuning for the Flink job regarding writing to HDFS.
>> Is there any config or optimization we can try to avoid delay and these
>> warnings?
>>
>> Thanks in advance!!
>>
>> Best regards,
>> Mu
>>
>