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Posted to issues@spark.apache.org by "Alexander Ulanov (JIRA)" <ji...@apache.org> on 2015/06/18 21:54:01 UTC
[jira] [Comment Edited] (SPARK-8449) HDF5 read/write support for
Spark MLlib
[ https://issues.apache.org/jira/browse/SPARK-8449?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14592398#comment-14592398 ]
Alexander Ulanov edited comment on SPARK-8449 at 6/18/15 7:53 PM:
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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 worths a look.
was (Author: avulanov):
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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