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Davies Liu authored
This patch will bring support for broadcasting objects larger than 2G. pickle, zlib, FrameSerializer and Array[Byte] all can not support objects larger than 2G, so this patch introduce LargeObjectSerializer to serialize broadcast objects, the object will be serialized and compressed into small chunks, it also change the type of Broadcast[Array[Byte]]] into Broadcast[Array[Array[Byte]]]]. Testing for support broadcast objects larger than 2G is slow and memory hungry, so this is tested manually, could be added into SparkPerf. Author: Davies Liu <davies@databricks.com> Author: Davies Liu <davies.liu@gmail.com> Closes #2659 from davies/huge and squashes the following commits: 7b57a14 [Davies Liu] add more tests for broadcast 28acff9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge a2f6a02 [Davies Liu] bug fix 4820613 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 5875c73 [Davies Liu] address comments 10a349b [Davies Liu] address comments 0c33016 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 6182c8f [Davies Liu] Merge branch 'master' into huge d94b68f [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 2514848 [Davies Liu] address comments fda395b [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 1c2d928 [Davies Liu] fix scala style 091b107 [Davies Liu] broadcast objects larger than 2G
Davies Liu authoredThis patch will bring support for broadcasting objects larger than 2G. pickle, zlib, FrameSerializer and Array[Byte] all can not support objects larger than 2G, so this patch introduce LargeObjectSerializer to serialize broadcast objects, the object will be serialized and compressed into small chunks, it also change the type of Broadcast[Array[Byte]]] into Broadcast[Array[Array[Byte]]]]. Testing for support broadcast objects larger than 2G is slow and memory hungry, so this is tested manually, could be added into SparkPerf. Author: Davies Liu <davies@databricks.com> Author: Davies Liu <davies.liu@gmail.com> Closes #2659 from davies/huge and squashes the following commits: 7b57a14 [Davies Liu] add more tests for broadcast 28acff9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge a2f6a02 [Davies Liu] bug fix 4820613 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 5875c73 [Davies Liu] address comments 10a349b [Davies Liu] address comments 0c33016 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 6182c8f [Davies Liu] Merge branch 'master' into huge d94b68f [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 2514848 [Davies Liu] address comments fda395b [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 1c2d928 [Davies Liu] fix scala style 091b107 [Davies Liu] broadcast objects larger than 2G
worker.py 5.38 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.
#
"""
Worker that receives input from Piped RDD.
"""
import os
import sys
import time
import socket
import traceback
import cProfile
import pstats
from pyspark.accumulators import _accumulatorRegistry
from pyspark.broadcast import Broadcast, _broadcastRegistry
from pyspark.files import SparkFiles
from pyspark.serializers import write_with_length, write_int, read_long, \
write_long, read_int, SpecialLengths, UTF8Deserializer, PickleSerializer, \
SizeLimitedStream, LargeObjectSerializer
from pyspark import shuffle
pickleSer = PickleSerializer()
utf8_deserializer = UTF8Deserializer()
def report_times(outfile, boot, init, finish):
write_int(SpecialLengths.TIMING_DATA, outfile)
write_long(1000 * boot, outfile)
write_long(1000 * init, outfile)
write_long(1000 * finish, outfile)
def add_path(path):
# worker can be used, so donot add path multiple times
if path not in sys.path:
# overwrite system packages
sys.path.insert(1, path)
def main(infile, outfile):
try:
boot_time = time.time()
split_index = read_int(infile)
if split_index == -1: # for unit tests
exit(-1)
# initialize global state
shuffle.MemoryBytesSpilled = 0
shuffle.DiskBytesSpilled = 0
_accumulatorRegistry.clear()
# fetch name of workdir
spark_files_dir = utf8_deserializer.loads(infile)
SparkFiles._root_directory = spark_files_dir
SparkFiles._is_running_on_worker = True
# fetch names of includes (*.zip and *.egg files) and construct PYTHONPATH
add_path(spark_files_dir) # *.py files that were added will be copied here
num_python_includes = read_int(infile)
for _ in range(num_python_includes):
filename = utf8_deserializer.loads(infile)
add_path(os.path.join(spark_files_dir, filename))
# fetch names and values of broadcast variables
num_broadcast_variables = read_int(infile)
bser = LargeObjectSerializer()
for _ in range(num_broadcast_variables):
bid = read_long(infile)
if bid >= 0:
size = read_long(infile)
s = SizeLimitedStream(infile, size)
value = list((bser.load_stream(s)))[0] # read out all the bytes
_broadcastRegistry[bid] = Broadcast(bid, value)
else:
bid = - bid - 1
_broadcastRegistry.pop(bid)
_accumulatorRegistry.clear()
command = pickleSer._read_with_length(infile)
if isinstance(command, Broadcast):
command = pickleSer.loads(command.value)
(func, stats, deserializer, serializer) = command
init_time = time.time()
def process():
iterator = deserializer.load_stream(infile)
serializer.dump_stream(func(split_index, iterator), outfile)
if stats:
p = cProfile.Profile()
p.runcall(process)
st = pstats.Stats(p)
st.stream = None # make it picklable
stats.add(st.strip_dirs())
else:
process()
except Exception:
try:
write_int(SpecialLengths.PYTHON_EXCEPTION_THROWN, outfile)
write_with_length(traceback.format_exc(), outfile)
except IOError:
# JVM close the socket
pass
except Exception:
# Write the error to stderr if it happened while serializing
print >> sys.stderr, "PySpark worker failed with exception:"
print >> sys.stderr, traceback.format_exc()
exit(-1)
finish_time = time.time()
report_times(outfile, boot_time, init_time, finish_time)
write_long(shuffle.MemoryBytesSpilled, outfile)
write_long(shuffle.DiskBytesSpilled, outfile)
# Mark the beginning of the accumulators section of the output
write_int(SpecialLengths.END_OF_DATA_SECTION, outfile)
write_int(len(_accumulatorRegistry), outfile)
for (aid, accum) in _accumulatorRegistry.items():
pickleSer._write_with_length((aid, accum._value), outfile)
# check end of stream
if read_int(infile) == SpecialLengths.END_OF_STREAM:
write_int(SpecialLengths.END_OF_STREAM, outfile)
else:
# write a different value to tell JVM to not reuse this worker
write_int(SpecialLengths.END_OF_DATA_SECTION, outfile)
exit(-1)
if __name__ == '__main__':
# Read a local port to connect to from stdin
java_port = int(sys.stdin.readline())
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.connect(("127.0.0.1", java_port))
sock_file = sock.makefile("a+", 65536)
main(sock_file, sock_file)