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https://issues.apache.org/jira/browse/HADOOP-17125?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Steve Loughran resolved HADOOP-17125.
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Fix Version/s: 3.3.1
Resolution: Fixed
> 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
> Assignee: DB Tsai
> Priority: Major
> Labels: pull-request-available
> Fix For: 3.3.1
>
> Time Spent: 24h 40m
> 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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