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https://issues.apache.org/jira/browse/HADOOP-17292?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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L. C. Hsieh updated HADOOP-17292:
---------------------------------
Description:
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.
was:
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 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 lz4.
> 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
>
> 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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