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https://issues.apache.org/jira/browse/HADOOP-19874?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18076534#comment-18076534
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ASF GitHub Bot commented on HADOOP-19874:
-----------------------------------------
pan3793 commented on code in PR #8461:
URL: https://github.com/apache/hadoop/pull/8461#discussion_r3146376526
##########
hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/io/compress/zstd/ZStandardCompressor.java:
##########
@@ -209,7 +229,16 @@ public int compress(byte[] b, int off, int len) throws
IOException {
compressedDirectBuf.position(0);
compressedDirectBuf.limit(directBufferSize);
- EndDirective endOp = shouldEnd ? EndDirective.END : EndDirective.FLUSH;
+ // CONTINUE should be used for non-end case, to support multi-threaded:
+ // 1. CONTINUE + workers ≥ 1: non-blocking. The call copies as much input
+ // as it can into a job, dispatches to workers, drains whatever output
+ // is ready, and returns. Multiple jobs can be in flight in parallel.
+ // 2. FLUSH + workers ≥ 1: multi-threaded compression will block to flush
+ // as much output as possible. The call won't return until every
queued
+ // job has finished and its output has been drained to the dst buffer.
+ // 3. END + workers ≥ 1: same as FLUSH but also closes the frame. Same
+ // blocking behavior.
+ EndDirective endOp = shouldEnd ? EndDirective.END : EndDirective.CONTINUE;
Review Comment:
my spark integration test shows it has no effect when using `FLUSH` -
setting workers to 4 has the same cpu usage and wall-clock time as the default
workers 0. while after the change to `CONTINUE`, the cpu average usage takes
~3.5x, wall-clock time cost has also decreased significantly
> ZStandardCodec supports multi-threaded compression
> --------------------------------------------------
>
> Key: HADOOP-19874
> URL: https://issues.apache.org/jira/browse/HADOOP-19874
> Project: Hadoop Common
> Issue Type: Improvement
> Reporter: Cheng Pan
> Priority: Major
> Labels: pull-request-available
>
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