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From "ASF GitHub Bot (Jira)" <j...@apache.org>
Subject [jira] [Work logged] (HADOOP-17292) Using lz4-java in Lz4Codec
Date Thu, 15 Oct 2020 16:47:00 GMT

     [ https://issues.apache.org/jira/browse/HADOOP-17292?focusedWorklogId=501163&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-501163

ASF GitHub Bot logged work on HADOOP-17292:

                Author: ASF GitHub Bot
            Created on: 15/Oct/20 16:46
            Start Date: 15/Oct/20 16:46
    Worklog Time Spent: 10m 
      Work Description: sunchao commented on a change in pull request #2350:
URL: https://github.com/apache/hadoop/pull/2350#discussion_r505690346

File path: hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/io/compress/lz4/Lz4Compressor.java
@@ -302,11 +303,20 @@ public synchronized long getBytesWritten() {
   public synchronized void end() {
-  private native static void initIDs();
-  private native int compressBytesDirect();
-  private native int compressBytesDirectHC();
-  public native static String getLibraryName();
+  private int compressDirectBuf() {
+    if (uncompressedDirectBufLen == 0) {
+      return 0;
+    } else {
+      // Set the position and limit of `uncompressedDirectBuf` for reading
+      uncompressedDirectBuf.limit(uncompressedDirectBufLen).position(0);
+      compressedDirectBuf.clear();

Review comment:
       Okay makes sense.

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Issue Time Tracking

    Worklog Id:     (was: 501163)
    Time Spent: 5h 50m  (was: 5h 40m)

> Using lz4-java in Lz4Codec
> --------------------------
>                 Key: HADOOP-17292
>                 URL: https://issues.apache.org/jira/browse/HADOOP-17292
>             Project: Hadoop Common
>          Issue Type: New Feature
>          Components: common
>    Affects Versions: 3.3.0
>            Reporter: L. C. Hsieh
>            Priority: Major
>              Labels: pull-request-available
>          Time Spent: 5h 50m
>  Remaining Estimate: 0h
> In Hadoop, we use native libs for lz4 codec which has several disadvantages:
> It requires native libhadoop to be installed in system LD_LIBRARY_PATH, and they have
to be installed separately on each node of the clusters, container images, or local test environments
which adds huge complexities from deployment point of view. In some environments, it requires
compiling the natives from sources which is non-trivial. Also, this approach is platform dependent;
the binary may not work in different platform, so it requires recompilation.
> It requires extra configuration of java.library.path to load the natives, and it results
higher application deployment and maintenance cost for users.
> Projects such as Spark use [lz4-java|https://github.com/lz4/lz4-java] which is JNI-based
implementation. It contains native binaries in jar file, and it can automatically load the
native binaries into JVM from jar without any setup. If a native implementation can not be
found for a platform, it can fallback to pure-java implementation of lz4.

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