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https://issues.apache.org/jira/browse/SPARK-8449?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14592398#comment-14592398
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Alexander Ulanov commented on SPARK-8449:
-----------------------------------------
It seems that using the official HDF5 reader is not a viable choice for Spark
due to platform dependent binaries. We need to look for pure Java
implementation. Apparently, there is one called netCDF:
http://www.unidata.ucar.edu/blogs/news/entry/netcdf_java_library_version_44. It
might be tricky to use it because the license is not Apache. However it worth a
look.
> HDF5 read/write support for Spark MLlib
> ---------------------------------------
>
> Key: SPARK-8449
> URL: https://issues.apache.org/jira/browse/SPARK-8449
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.4.0
> Reporter: Alexander Ulanov
> Fix For: 1.4.1
>
> Original Estimate: 96h
> Remaining Estimate: 96h
>
> Add support for reading and writing HDF5 file format to/from LabeledPoint.
> HDFS and local file system have to be supported. Other Spark formats to be
> discussed.
> Interface proposal:
> /* path - directory path in any Hadoop-supported file system URI */
> MLUtils.saveAsHDF5(sc: SparkContext, path: String, RDD[LabeledPoint]): Unit
> /* path - file or directory path in any Hadoop-supported file system URI */
> MLUtils.loadHDF5(sc: SparkContext, path: String): RDD[LabeledPoint]
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