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Posted to issues@ozone.apache.org by "Shashikant Banerjee (Jira)" <ji...@apache.org> on 2020/03/11 17:02:00 UTC
[jira] [Comment Edited] (HDDS-3155) Improved ozone flush
implementation to make it faster.
[ https://issues.apache.org/jira/browse/HDDS-3155?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17057213#comment-17057213 ]
Shashikant Banerjee edited comment on HDDS-3155 at 3/11/20, 5:01 PM:
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{code:java}
Currently, each flush operation in ozone generates a new chunk file in real time on the disk. This approach is not very efficient at the moment.
{code}
This is not true. We never do a sync write to disk during flush/close. It does not create a chunk file either during flush/close.
A chunk file is created when a new chunk is getting written (for 4MB data by default).
was (Author: shashikant):
{code:java}
Currently, each flush operation in ozone generates a new chunk file in real time on the disk. This approach is not very efficient at the moment.
{code}
This is not true. We never do a sync write to disk during flush/close. It does not create a chunk file either during flush/close.
> Improved ozone flush implementation to make it faster.
> ------------------------------------------------------
>
> Key: HDDS-3155
> URL: https://issues.apache.org/jira/browse/HDDS-3155
> Project: Hadoop Distributed Data Store
> Issue Type: Improvement
> Reporter: mingchao zhao
> Priority: Major
> Attachments: amlog, stdout
>
>
> Background:
> When we execute mapreduce in the ozone, we find that the task will be stuck for a long time after the completion of Map and Reduce. The log is as follows:
> {code:java}
> //Refer to the attachment: stdout
> 20/03/05 14:43:30 INFO mapreduce.Job: map 100% reduce 33%
> 20/03/05 14:43:33 INFO mapreduce.Job: map 100% reduce 100%
> 20/03/05 15:29:52 INFO mapreduce.Job: Job job_1583385253878_0002 completed successfully{code}
> By looking at AM's log(Refer to the amlog for details), we found that the time of over 40 minutes is AM writing a task log into ozone.
> At present, after MR execution, the Task information is recorded into the log on HDFS or ozone by AM. Moreover, the task information is flush to HDFS or ozone one by one ([details|https://github.com/apache/hadoop/blob/a55d6bba71c81c1c4e9d8cd11f55c78f10a548b0/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app/src/main/java/org/apache/hadoop/mapreduce/jobhistory/JobHistoryEventHandler.java#L1640]). The problem occurs when the number of task maps is large.
> Currently, each flush operation in ozone generates a new chunk file in real time on the disk. This approach is not very efficient at the moment. For this we can refer to the implementation of HDFS flush. Instead of writing to disk each time flush writes the contents of the buffer to the datanode's OS buffer. In the first place, we need to ensure that this content can be read by other datanodes.
>
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