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    ce95bd8e
    [SPARK-4531] [MLlib] cache serialized java object · ce95bd8e
    Davies Liu authored
    The Pyrolite is pretty slow (comparing to the adhoc serializer in 1.1), it cause much performance regression in 1.2, because we cache the serialized Python object in JVM, deserialize them into Java object in each step.
    
    This PR change to cache the deserialized JavaRDD instead of PythonRDD to avoid the deserialization of Pyrolite. It should have similar memory usage as before, but much faster.
    
    Author: Davies Liu <davies@databricks.com>
    
    Closes #3397 from davies/cache and squashes the following commits:
    
    7f6e6ce [Davies Liu] Update -> Updater
    4b52edd [Davies Liu] using named argument
    63b984e [Davies Liu] fix
    7da0332 [Davies Liu] add unpersist()
    dff33e1 [Davies Liu] address comments
    c2bdfc2 [Davies Liu] refactor
    d572f00 [Davies Liu] Merge branch 'master' into cache
    f1063e1 [Davies Liu] cache serialized java object
    ce95bd8e
    History
    [SPARK-4531] [MLlib] cache serialized java object
    Davies Liu authored
    The Pyrolite is pretty slow (comparing to the adhoc serializer in 1.1), it cause much performance regression in 1.2, because we cache the serialized Python object in JVM, deserialize them into Java object in each step.
    
    This PR change to cache the deserialized JavaRDD instead of PythonRDD to avoid the deserialization of Pyrolite. It should have similar memory usage as before, but much faster.
    
    Author: Davies Liu <davies@databricks.com>
    
    Closes #3397 from davies/cache and squashes the following commits:
    
    7f6e6ce [Davies Liu] Update -> Updater
    4b52edd [Davies Liu] using named argument
    63b984e [Davies Liu] fix
    7da0332 [Davies Liu] add unpersist()
    dff33e1 [Davies Liu] address comments
    c2bdfc2 [Davies Liu] refactor
    d572f00 [Davies Liu] Merge branch 'master' into cache
    f1063e1 [Davies Liu] cache serialized java object
common.py 4.10 KiB
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

import py4j.protocol
from py4j.protocol import Py4JJavaError
from py4j.java_gateway import JavaObject
from py4j.java_collections import MapConverter, ListConverter, JavaArray, JavaList

from pyspark import RDD, SparkContext
from pyspark.serializers import PickleSerializer, AutoBatchedSerializer


# Hack for support float('inf') in Py4j
_old_smart_decode = py4j.protocol.smart_decode

_float_str_mapping = {
    'nan': 'NaN',
    'inf': 'Infinity',
    '-inf': '-Infinity',
}


def _new_smart_decode(obj):
    if isinstance(obj, float):
        s = unicode(obj)
        return _float_str_mapping.get(s, s)
    return _old_smart_decode(obj)

py4j.protocol.smart_decode = _new_smart_decode


_picklable_classes = [
    'LinkedList',
    'SparseVector',
    'DenseVector',
    'DenseMatrix',
    'Rating',
    'LabeledPoint',
]


# this will call the MLlib version of pythonToJava()
def _to_java_object_rdd(rdd):
    """ Return an JavaRDD of Object by unpickling

    It will convert each Python object into Java object by Pyrolite, whenever the
    RDD is serialized in batch or not.
    """
    rdd = rdd._reserialize(AutoBatchedSerializer(PickleSerializer()))
    return rdd.ctx._jvm.SerDe.pythonToJava(rdd._jrdd, True)


def _py2java(sc, obj):
    """ Convert Python object into Java """
    if isinstance(obj, RDD):
        obj = _to_java_object_rdd(obj)
    elif isinstance(obj, SparkContext):
        obj = obj._jsc
    elif isinstance(obj, dict):
        obj = MapConverter().convert(obj, sc._gateway._gateway_client)
    elif isinstance(obj, (list, tuple)):
        obj = ListConverter().convert(obj, sc._gateway._gateway_client)
    elif isinstance(obj, JavaObject):
        pass
    elif isinstance(obj, (int, long, float, bool, basestring)):
        pass
    else:
        bytes = bytearray(PickleSerializer().dumps(obj))
        obj = sc._jvm.SerDe.loads(bytes)
    return obj


def _java2py(sc, r):
    if isinstance(r, JavaObject):
        clsName = r.getClass().getSimpleName()
        # convert RDD into JavaRDD
        if clsName != 'JavaRDD' and clsName.endswith("RDD"):
            r = r.toJavaRDD()
            clsName = 'JavaRDD'

        if clsName == 'JavaRDD':
            jrdd = sc._jvm.SerDe.javaToPython(r)
            return RDD(jrdd, sc)

        if clsName in _picklable_classes:
            r = sc._jvm.SerDe.dumps(r)
        elif isinstance(r, (JavaArray, JavaList)):
            try:
                r = sc._jvm.SerDe.dumps(r)
            except Py4JJavaError:
                pass  # not pickable

    if isinstance(r, bytearray):
        r = PickleSerializer().loads(str(r))
    return r


def callJavaFunc(sc, func, *args):
    """ Call Java Function """
    args = [_py2java(sc, a) for a in args]
    return _java2py(sc, func(*args))


def callMLlibFunc(name, *args):
    """ Call API in PythonMLLibAPI """
    sc = SparkContext._active_spark_context
    api = getattr(sc._jvm.PythonMLLibAPI(), name)
    return callJavaFunc(sc, api, *args)


class JavaModelWrapper(object):
    """
    Wrapper for the model in JVM
    """
    def __init__(self, java_model):
        self._sc = SparkContext._active_spark_context
        self._java_model = java_model

    def __del__(self):
        self._sc._gateway.detach(self._java_model)

    def call(self, name, *a):
        """Call method of java_model"""
        return callJavaFunc(self._sc, getattr(self._java_model, name), *a)