GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2378
[SPARK-3491] [WIP] [MLlib] [PySpark] use pickle to serialize data in MLlib
Currently, we serialize the data between JVM and Python case by case
manually, this cannot scale to support so many APIs in MLlib.
This patch will try to address this problem by serialize the data using
pickle protocol, using Pyrolite library to serialize/deserialize in JVM. Pickle
protocol can be easily extended to support customized class.
In the first step, it can support Double, DenseVector, SparseVector,
DenseMatrix, LabeledPoint, Rating, Tuple2 now, the recommendation module had
been refactor to use this new protocol.
Later, I will refactor all others to use this protocol.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/davies/spark pickle_mllib
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/2378.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #2378
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commit b30ef35ec7830cee08b4f8d692da26d98cac70e8
Author: Davies Liu <[email protected]>
Date: 2014-09-13T07:18:33Z
use pickle to serialize data for mllib/recommendation
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