# # 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.taskcontext import TaskContext 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) if num_udfs == 1: # fast path for single UDF _, udf = read_single_udf(pickleSer, infile) mapper = lambda a: udf(*a) else: 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)) 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 taskContext = TaskContext._getOrCreate() taskContext._stageId = read_int(infile) taskContext._partitionId = read_int(infile) taskContext._attemptNumber = read_int(infile) taskContext._taskAttemptId = read_long(infile) 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 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("rwb", 65536) main(sock_file, sock_file)