python/pyspark/worker.py - spark - Git at Google

 #
 # 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.
 """
 from __future__ import print_function
 import os
 import sys
 import time
 import socket
 import traceback

 from pyspark.accumulators import _accumulatorRegistry
 from pyspark.broadcast import Broadcast, _broadcastRegistry
 from pyspark.java_gateway import do_server_auth
 from pyspark.files import SparkFiles
 from pyspark.serializers import write_with_length, write_int, read_long, \
     write_long, read_int, SpecialLengths, UTF8Deserializer, PickleSerializer, BatchedSerializer
 from pyspark import shuffle

 pickleSer = PickleSerializer()
 utf8_deserializer = UTF8Deserializer()


 def report_times(outfile, boot, init, finish):
     write_int(SpecialLengths.TIMING_DATA, outfile)
     write_long(int(1000 * boot), outfile)
     write_long(int(1000 * init), outfile)
     write_long(int(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 read_command(serializer, file):
     command = serializer._read_with_length(file)
     if isinstance(command, Broadcast):
         command = serializer.loads(command.value)
     return command


 def chain(f, g):
     """chain two function together """
     return lambda *a: g(f(*a))


 def wrap_udf(f, return_type):
     if return_type.needConversion():
         toInternal = return_type.toInternal
         return lambda *a: toInternal(f(*a))
     else:
         return lambda *a: f(*a)


 def read_single_udf(pickleSer, infile):
     num_arg = read_int(infile)
     arg_offsets = [read_int(infile) for i in range(num_arg)]
     row_func = None
     for i in range(read_int(infile)):
         f, return_type = read_command(pickleSer, infile)
         if row_func is None:
             row_func = f
         else:
             row_func = chain(row_func, f)
     # the last returnType will be the return type of UDF
     return arg_offsets, wrap_udf(row_func, return_type)


 def read_udfs(pickleSer, infile):
     num_udfs = read_int(infile)
     udfs = {}
     call_udf = []
     for i in range(num_udfs):
         arg_offsets, udf = read_single_udf(pickleSer, infile)
         udfs['f%d' % i] = udf
         args = ["a[%d]" % o for o in arg_offsets]
         call_udf.append("f%d(%s)" % (i, ", ".join(args)))
     # Create function like this:
     #   lambda a: (f0(a0), f1(a1, a2), f2(a3))
     # In the special case of a single UDF this will return a single result rather
     # than a tuple of results; this is the format that the JVM side expects.
     mapper_str = "lambda a: (%s)" % (", ".join(call_udf))
     mapper = eval(mapper_str, udfs)

     func = lambda _, it: map(mapper, it)
     ser = BatchedSerializer(PickleSerializer(), 100)
     # profiling is not supported for UDF
     return func, None, ser, ser


 def main(infile, outfile):
     try:
         boot_time = time.time()
         split_index = read_int(infile)
         if split_index == -1:  # for unit tests
             exit(-1)

         version = utf8_deserializer.loads(infile)
         if version != "%d.%d" % sys.version_info[:2]:
             raise Exception(("Python in worker has different version %s than that in " +
                              "driver %s, PySpark cannot run with different minor versions." +
                              "Please check environment variables PYSPARK_PYTHON and " +
                              "PYSPARK_DRIVER_PYTHON are correctly set.") %
                             ("%d.%d" % sys.version_info[:2], version))

         # 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))
         if sys.version > '3':
             import importlib
             importlib.invalidate_caches()

         # fetch names and values of broadcast variables
         num_broadcast_variables = read_int(infile)
         for _ in range(num_broadcast_variables):
             bid = read_long(infile)
             if bid >= 0:
                 path = utf8_deserializer.loads(infile)
                 _broadcastRegistry[bid] = Broadcast(path=path)
             else:
                 bid = - bid - 1
                 _broadcastRegistry.pop(bid)

         _accumulatorRegistry.clear()
         is_sql_udf = read_int(infile)
         if is_sql_udf:
             func, profiler, deserializer, serializer = read_udfs(pickleSer, infile)
         else:
             func, profiler, deserializer, serializer = read_command(pickleSer, infile)

         init_time = time.time()

         def process():
             iterator = deserializer.load_stream(infile)
             serializer.dump_stream(func(split_index, iterator), outfile)

         if profiler:
             profiler.profile(process)
         else:
             process()
     except Exception:
         try:
             write_int(SpecialLengths.PYTHON_EXCEPTION_THROWN, outfile)
             write_with_length(traceback.format_exc().encode("utf-8"), outfile)
         except IOError:
             # JVM close the socket
             pass
         except Exception:
             # Write the error to stderr if it happened while serializing
             print("PySpark worker failed with exception:", file=sys.stderr)
             print(traceback.format_exc(), file=sys.stderr)
         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 information about how to connect back to the JVM from the environment.
     java_port = int(os.environ["PYTHON_WORKER_FACTORY_PORT"])
     auth_secret = os.environ["PYTHON_WORKER_FACTORY_SECRET"]
     sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
     sock.connect(("127.0.0.1", java_port))
     sock_file = sock.makefile("rwb", 65536)
     do_server_auth(sock_file, auth_secret)
     main(sock_file, sock_file)
	#
	# 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.
	"""
	from __future__ import print_function
	import os
	import sys
	import time
	import socket
	import traceback

	from pyspark.accumulators import _accumulatorRegistry
	from pyspark.broadcast import Broadcast, _broadcastRegistry
	from pyspark.java_gateway import do_server_auth
	from pyspark.files import SparkFiles
	from pyspark.serializers import write_with_length, write_int, read_long, \
	write_long, read_int, SpecialLengths, UTF8Deserializer, PickleSerializer, BatchedSerializer
	from pyspark import shuffle

	pickleSer = PickleSerializer()
	utf8_deserializer = UTF8Deserializer()


	def report_times(outfile, boot, init, finish):
	write_int(SpecialLengths.TIMING_DATA, outfile)
	write_long(int(1000 * boot), outfile)
	write_long(int(1000 * init), outfile)
	write_long(int(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 read_command(serializer, file):
	command = serializer._read_with_length(file)
	if isinstance(command, Broadcast):
	command = serializer.loads(command.value)
	return command


	def chain(f, g):
	"""chain two function together """
	return lambda a: g(f(a))


	def wrap_udf(f, return_type):
	if return_type.needConversion():
	toInternal = return_type.toInternal
	return lambda a: toInternal(f(a))
	else:
	return lambda a: f(a)


	def read_single_udf(pickleSer, infile):
	num_arg = read_int(infile)
	arg_offsets = [read_int(infile) for i in range(num_arg)]
	row_func = None
	for i in range(read_int(infile)):
	f, return_type = read_command(pickleSer, infile)
	if row_func is None:
	row_func = f
	else:
	row_func = chain(row_func, f)
	# the last returnType will be the return type of UDF
	return arg_offsets, wrap_udf(row_func, return_type)


	def read_udfs(pickleSer, infile):
	num_udfs = read_int(infile)
	udfs = {}
	call_udf = []
	for i in range(num_udfs):
	arg_offsets, udf = read_single_udf(pickleSer, infile)
	udfs['f%d' % i] = udf
	args = ["a[%d]" % o for o in arg_offsets]
	call_udf.append("f%d(%s)" % (i, ", ".join(args)))
	# Create function like this:
	# lambda a: (f0(a0), f1(a1, a2), f2(a3))
	# In the special case of a single UDF this will return a single result rather
	# than a tuple of results; this is the format that the JVM side expects.
	mapper_str = "lambda a: (%s)" % (", ".join(call_udf))
	mapper = eval(mapper_str, udfs)

	func = lambda _, it: map(mapper, it)
	ser = BatchedSerializer(PickleSerializer(), 100)
	# profiling is not supported for UDF
	return func, None, ser, ser


	def main(infile, outfile):
	try:
	boot_time = time.time()
	split_index = read_int(infile)
	if split_index == -1: # for unit tests
	exit(-1)

	version = utf8_deserializer.loads(infile)
	if version != "%d.%d" % sys.version_info[:2]:
	raise Exception(("Python in worker has different version %s than that in " +
	"driver %s, PySpark cannot run with different minor versions." +
	"Please check environment variables PYSPARK_PYTHON and " +
	"PYSPARK_DRIVER_PYTHON are correctly set.") %
	("%d.%d" % sys.version_info[:2], version))

	# 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))
	if sys.version > '3':
	import importlib
	importlib.invalidate_caches()

	# fetch names and values of broadcast variables
	num_broadcast_variables = read_int(infile)
	for _ in range(num_broadcast_variables):
	bid = read_long(infile)
	if bid >= 0:
	path = utf8_deserializer.loads(infile)
	_broadcastRegistry[bid] = Broadcast(path=path)
	else:
	bid = - bid - 1
	_broadcastRegistry.pop(bid)

	_accumulatorRegistry.clear()
	is_sql_udf = read_int(infile)
	if is_sql_udf:
	func, profiler, deserializer, serializer = read_udfs(pickleSer, infile)
	else:
	func, profiler, deserializer, serializer = read_command(pickleSer, infile)

	init_time = time.time()

	def process():
	iterator = deserializer.load_stream(infile)
	serializer.dump_stream(func(split_index, iterator), outfile)

	if profiler:
	profiler.profile(process)
	else:
	process()
	except Exception:
	try:
	write_int(SpecialLengths.PYTHON_EXCEPTION_THROWN, outfile)
	write_with_length(traceback.format_exc().encode("utf-8"), outfile)
	except IOError:
	# JVM close the socket
	pass
	except Exception:
	# Write the error to stderr if it happened while serializing
	print("PySpark worker failed with exception:", file=sys.stderr)
	print(traceback.format_exc(), file=sys.stderr)
	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 information about how to connect back to the JVM from the environment.
	java_port = int(os.environ["PYTHON_WORKER_FACTORY_PORT"])
	auth_secret = os.environ["PYTHON_WORKER_FACTORY_SECRET"]
	sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
	sock.connect(("127.0.0.1", java_port))
	sock_file = sock.makefile("rwb", 65536)
	do_server_auth(sock_file, auth_secret)
	main(sock_file, sock_file)