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From "ASF GitHub Bot (Jira)" <j...@apache.org>
Subject [jira] [Work logged] (HADOOP-17125) Using snappy-java in SnappyCodec
Date Wed, 09 Sep 2020 06:23:00 GMT

     [ https://issues.apache.org/jira/browse/HADOOP-17125?focusedWorklogId=480616&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-480616
]

ASF GitHub Bot logged work on HADOOP-17125:
-------------------------------------------

                Author: ASF GitHub Bot
            Created on: 09/Sep/20 06:22
            Start Date: 09/Sep/20 06:22
    Worklog Time Spent: 10m 
      Work Description: dbtsai commented on a change in pull request #2201:
URL: https://github.com/apache/hadoop/pull/2201#discussion_r485364827



##########
File path: hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/io/compress/snappy/SnappyDecompressor.java
##########
@@ -276,13 +258,27 @@ public void end() {
     // do nothing
   }
 
-  private native static void initIDs();
+  private int decompressBytesDirect() throws IOException {
+    if (compressedDirectBufLen == 0) {
+      return 0;
+    } else {
+      // Set the position and limit of `compressedDirectBuf` for reading
+      compressedDirectBuf.position(0).limit(compressedDirectBufLen);
+      // There is compressed input, decompress it now.
+      int size = Snappy.uncompressedLength((ByteBuffer) compressedDirectBuf);
+      if (size > uncompressedDirectBuf.capacity()) {

Review comment:
       Before calling `decompressBytesDirect`, we always reset `uncompressedDirectBuf`. So
both method returns the same result. But you are right, I think .remaining is better. 




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Issue Time Tracking
-------------------

    Worklog Id:     (was: 480616)
    Time Spent: 1h  (was: 50m)

> Using snappy-java in SnappyCodec
> --------------------------------
>
>                 Key: HADOOP-17125
>                 URL: https://issues.apache.org/jira/browse/HADOOP-17125
>             Project: Hadoop Common
>          Issue Type: New Feature
>          Components: common
>    Affects Versions: 3.3.0
>            Reporter: DB Tsai
>            Priority: Major
>              Labels: pull-request-available
>          Time Spent: 1h
>  Remaining Estimate: 0h
>
> In Hadoop, we use native libs for snappy codec which has several disadvantages:
>  * It requires native *libhadoop* and *libsnappy* 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* and *Parquet* use [snappy-java|[https://github.com/xerial/snappy-java]]
which is JNI-based implementation. It contains native binaries for Linux, Mac, and IBM 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 snappy based on [aircompressor|[https://github.com/airlift/aircompressor/tree/master/src/main/java/io/airlift/compress/snappy]].



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