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Python serializers.write_with_length函数代码示例

原作者: [db:作者] 来自: [db:来源] 收藏 邀请

本文整理汇总了Python中pyspark.serializers.write_with_length函数的典型用法代码示例。如果您正苦于以下问题:Python write_with_length函数的具体用法?Python write_with_length怎么用?Python write_with_length使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。



在下文中一共展示了write_with_length函数的14个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: main

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

        # 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
        sys.path.append(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)
            sys.path.append(os.path.join(spark_files_dir, filename))

        # fetch names and values of broadcast variables
        num_broadcast_variables = read_int(infile)
        ser = CompressedSerializer(pickleSer)
        for _ in range(num_broadcast_variables):
            bid = read_long(infile)
            if bid >= 0:
                value = ser._read_with_length(infile)
                _broadcastRegistry[bid] = Broadcast(bid, value)
            else:
                bid = - bid - 1
                _broadcastRegistry.remove(bid)

        _accumulatorRegistry.clear()
        command = pickleSer._read_with_length(infile)
        (func, deserializer, serializer) = command
        init_time = time.time()
        iterator = deserializer.load_stream(infile)
        serializer.dump_stream(func(split_index, iterator), outfile)
    except Exception:
        try:
            write_int(SpecialLengths.PYTHON_EXCEPTION_THROWN, outfile)
            write_with_length(traceback.format_exc(), outfile)
            outfile.flush()
        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)
    # 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)
开发者ID:xuqingshen,项目名称:spark,代码行数:57,代码来源:worker.py


示例2: do_server_auth

def do_server_auth(conn, auth_secret):
    """
    Performs the authentication protocol defined by the SocketAuthHelper class on the given
    file-like object 'conn'.
    """
    write_with_length(auth_secret.encode("utf-8"), conn)
    conn.flush()
    reply = UTF8Deserializer().loads(conn)
    if reply != "ok":
        conn.close()
        raise Exception("Unexpected reply from iterator server.")
开发者ID:WeichenXu123,项目名称:spark,代码行数:11,代码来源:java_gateway.py


示例3: main

def main():
    split_index = read_int(sys.stdin)
    num_broadcast_variables = read_int(sys.stdin)
    for _ in range(num_broadcast_variables):
        bid = read_long(sys.stdin)
        value = read_with_length(sys.stdin)
        _broadcastRegistry[bid] = Broadcast(bid, load_pickle(value))
    func = load_obj()
    bypassSerializer = load_obj()
    if bypassSerializer:
        dumps = lambda x: x
    else:
        dumps = dump_pickle
    iterator = read_from_pickle_file(sys.stdin)
    for obj in func(split_index, iterator):
        write_with_length(dumps(obj), old_stdout)
开发者ID:fernand,项目名称:spark,代码行数:16,代码来源:worker.py


示例4: parallelize

 def parallelize(self, c, numSlices=None):
     """
     Distribute a local Python collection to form an RDD.
     """
     numSlices = numSlices or self.defaultParallelism
     # Calling the Java parallelize() method with an ArrayList is too slow,
     # because it sends O(n) Py4J commands.  As an alternative, serialized
     # objects are written to a file and loaded through textFile().
     tempFile = NamedTemporaryFile(delete=False)
     atexit.register(lambda: os.unlink(tempFile.name))
     if self.batchSize != 1:
         c = batched(c, self.batchSize)
     for x in c:
         write_with_length(dump_pickle(x), tempFile)
     tempFile.close()
     jrdd = self._readRDDFromPickleFile(self._jsc, tempFile.name, numSlices)
     return RDD(jrdd, self)
开发者ID:fernand,项目名称:spark,代码行数:17,代码来源:context.py


示例5: main

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

    # fetch name of workdir
    spark_files_dir = mutf8_deserializer.loads(infile)
    SparkFiles._root_directory = spark_files_dir
    SparkFiles._is_running_on_worker = True

    # fetch names and values of broadcast variables
    num_broadcast_variables = read_int(infile)
    for _ in range(num_broadcast_variables):
        bid = read_long(infile)
        value = pickleSer._read_with_length(infile)
        _broadcastRegistry[bid] = Broadcast(bid, value)

    # fetch names of includes (*.zip and *.egg files) and construct PYTHONPATH
    sys.path.append(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 = mutf8_deserializer.loads(infile)
        sys.path.append(os.path.join(spark_files_dir, filename))

    command = pickleSer._read_with_length(infile)
    (func, deserializer, serializer) = command
    init_time = time.time()
    try:
        iterator = deserializer.load_stream(infile)
        serializer.dump_stream(func(split_index, iterator), outfile)
    except Exception as e:
        write_int(SpecialLengths.PYTHON_EXCEPTION_THROWN, outfile)
        write_with_length(traceback.format_exc(), outfile)
        sys.exit(-1)
    finish_time = time.time()
    report_times(outfile, boot_time, init_time, finish_time)
    # 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)
开发者ID:CadillacBupt,项目名称:incubator-spark,代码行数:42,代码来源:worker.py


示例6: main

def main():
    split_index = read_int(sys.stdin)
    spark_files_dir = load_pickle(read_with_length(sys.stdin))
    SparkFiles._root_directory = spark_files_dir
    SparkFiles._is_running_on_worker = True
    sys.path.append(spark_files_dir)
    num_broadcast_variables = read_int(sys.stdin)
    for _ in range(num_broadcast_variables):
        bid = read_long(sys.stdin)
        value = read_with_length(sys.stdin)
        _broadcastRegistry[bid] = Broadcast(bid, load_pickle(value))
    func = load_obj()
    bypassSerializer = load_obj()
    if bypassSerializer:
        dumps = lambda x: x
    else:
        dumps = dump_pickle
    iterator = read_from_pickle_file(sys.stdin)
    try:
        for obj in func(split_index, iterator):
           write_with_length(dumps(obj), old_stdout)
    except Exception as e:
        write_int(-2, old_stdout)
        write_with_length(traceback.format_exc(), old_stdout)
        sys.exit(-1)
    # Mark the beginning of the accumulators section of the output
    write_int(-1, old_stdout)
    for aid, accum in _accumulatorRegistry.items():
        write_with_length(dump_pickle((aid, accum._value)), old_stdout)
开发者ID:Alienfeel,项目名称:spark,代码行数:29,代码来源:worker.py


示例7: worker

def worker(sock, authenticated):
    """
    Called by a worker process after the fork().
    """
    signal.signal(SIGHUP, SIG_DFL)
    signal.signal(SIGCHLD, SIG_DFL)
    signal.signal(SIGTERM, SIG_DFL)
    # restore the handler for SIGINT,
    # it's useful for debugging (show the stacktrace before exit)
    signal.signal(SIGINT, signal.default_int_handler)

    # Read the socket using fdopen instead of socket.makefile() because the latter
    # seems to be very slow; note that we need to dup() the file descriptor because
    # otherwise writes also cause a seek that makes us miss data on the read side.
    infile = os.fdopen(os.dup(sock.fileno()), "rb", 65536)
    outfile = os.fdopen(os.dup(sock.fileno()), "wb", 65536)

    if not authenticated:
        client_secret = UTF8Deserializer().loads(infile)
        if os.environ["PYTHON_WORKER_FACTORY_SECRET"] == client_secret:
            write_with_length("ok".encode("utf-8"), outfile)
            outfile.flush()
        else:
            write_with_length("err".encode("utf-8"), outfile)
            outfile.flush()
            sock.close()
            return 1

    exit_code = 0
    try:
        worker_main(infile, outfile)
    except SystemExit as exc:
        exit_code = compute_real_exit_code(exc.code)
    finally:
        try:
            outfile.flush()
        except Exception:
            pass
    return exit_code
开发者ID:BaiBenny,项目名称:spark,代码行数:39,代码来源:daemon.py


示例8: parallelize

    def parallelize(self, c, numSlices=None):
        """
        Distribute a local Python collection to form an RDD.

        >>> sc.parallelize(range(5), 5).glom().collect()
        [[0], [1], [2], [3], [4]]
        """
        numSlices = numSlices or self.defaultParallelism
        # Calling the Java parallelize() method with an ArrayList is too slow,
        # because it sends O(n) Py4J commands.  As an alternative, serialized
        # objects are written to a file and loaded through textFile().
        tempFile = NamedTemporaryFile(delete=False, dir=self._temp_dir)
        # Make sure we distribute data evenly if it's smaller than self.batchSize
        if "__len__" not in dir(c):
            c = list(c)    # Make it a list so we can compute its length
        batchSize = min(len(c) // numSlices, self.batchSize)
        if batchSize > 1:
            c = batched(c, batchSize)
        for x in c:
            write_with_length(dump_pickle(x), tempFile)
        tempFile.close()
        readRDDFromPickleFile = self._jvm.PythonRDD.readRDDFromPickleFile
        jrdd = readRDDFromPickleFile(self._jsc, tempFile.name, numSlices)
        return RDD(jrdd, self)
开发者ID:AustinBGibbons,项目名称:incubator-spark,代码行数:24,代码来源:context.py


示例9: main

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

    # fetch name of workdir
    spark_files_dir = load_pickle(read_with_length(infile))
    SparkFiles._root_directory = spark_files_dir
    SparkFiles._is_running_on_worker = True

    # fetch names and values of broadcast variables
    num_broadcast_variables = read_int(infile)
    for _ in range(num_broadcast_variables):
        bid = read_long(infile)
        value = read_with_length(infile)
        _broadcastRegistry[bid] = Broadcast(bid, load_pickle(value))

    # fetch names of includes (*.zip and *.egg files) and construct PYTHONPATH
    sys.path.append(spark_files_dir) # *.py files that were added will be copied here
    num_python_includes =  read_int(infile)
    for _ in range(num_python_includes):
        sys.path.append(os.path.join(spark_files_dir, load_pickle(read_with_length(infile))))

    # now load function
    func = load_obj(infile)
    bypassSerializer = load_obj(infile)
    if bypassSerializer:
        dumps = lambda x: x
    else:
        dumps = dump_pickle
    init_time = time.time()
    iterator = read_from_pickle_file(infile)
    try:
        for obj in func(split_index, iterator):
            write_with_length(dumps(obj), outfile)
    except Exception as e:
        write_int(-2, outfile)
        write_with_length(traceback.format_exc(), outfile)
        sys.exit(-1)
    finish_time = time.time()
    report_times(outfile, boot_time, init_time, finish_time)
    # Mark the beginning of the accumulators section of the output
    write_int(-1, outfile)
    for aid, accum in _accumulatorRegistry.items():
        write_with_length(dump_pickle((aid, accum._value)), outfile)
    write_int(-1, outfile)
开发者ID:AtScaleInc,项目名称:incubator-spark,代码行数:47,代码来源:worker.py


示例10: main

def main(infile, outfile):
    boot_time = time.time()
    split_index = read_int(infile)
    if split_index == -1:  # for unit tests
        return
    spark_files_dir = load_pickle(read_with_length(infile))
    SparkFiles._root_directory = spark_files_dir
    SparkFiles._is_running_on_worker = True
    sys.path.append(spark_files_dir)
    num_broadcast_variables = read_int(infile)
    for _ in range(num_broadcast_variables):
        bid = read_long(infile)
        value = read_with_length(infile)
        _broadcastRegistry[bid] = Broadcast(bid, load_pickle(value))
    func = load_obj(infile)
    bypassSerializer = load_obj(infile)
    if bypassSerializer:
        dumps = lambda x: x
    else:
        dumps = dump_pickle
    init_time = time.time()
    iterator = read_from_pickle_file(infile)
    try:
        for obj in func(split_index, iterator):
            write_with_length(dumps(obj), outfile)
    except Exception as e:
        write_int(-2, outfile)
        write_with_length(traceback.format_exc(), outfile)
        sys.exit(-1)
    finish_time = time.time()
    report_times(outfile, boot_time, init_time, finish_time)
    # Mark the beginning of the accumulators section of the output
    write_int(-1, outfile)
    for aid, accum in _accumulatorRegistry.items():
        write_with_length(dump_pickle((aid, accum._value)), outfile)
    write_int(-1, outfile)
开发者ID:knightelvis,项目名称:spark,代码行数:36,代码来源:worker.py


示例11: main


#.........这里部分代码省略.........
        for i in range(read_int(infile)):
            k = utf8_deserializer.loads(infile)
            v = utf8_deserializer.loads(infile)
            taskContext._localProperties[k] = v

        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
        needs_broadcast_decryption_server = read_bool(infile)
        num_broadcast_variables = read_int(infile)
        if needs_broadcast_decryption_server:
            # read the decrypted data from a server in the jvm
            port = read_int(infile)
            auth_secret = utf8_deserializer.loads(infile)
            (broadcast_sock_file, _) = local_connect_and_auth(port, auth_secret)

        for _ in range(num_broadcast_variables):
            bid = read_long(infile)
            if bid >= 0:
                if needs_broadcast_decryption_server:
                    read_bid = read_long(broadcast_sock_file)
                    assert(read_bid == bid)
                    _broadcastRegistry[bid] = \
                        Broadcast(sock_file=broadcast_sock_file)
                else:
                    path = utf8_deserializer.loads(infile)
                    _broadcastRegistry[bid] = Broadcast(path=path)

            else:
                bid = - bid - 1
                _broadcastRegistry.pop(bid)

        if needs_broadcast_decryption_server:
            broadcast_sock_file.write(b'1')
            broadcast_sock_file.close()

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

        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)
        sys.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)
        sys.exit(-1)
开发者ID:Brett-A,项目名称:spark,代码行数:101,代码来源:worker.py


示例12: main

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))
        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()
        command = pickleSer._read_with_length(infile)
        if isinstance(command, Broadcast):
            command = pickleSer.loads(command.value)
        (func, profiler, deserializer, serializer), version = command
        if version != 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") %
                            (sys.version_info[:2], version))
        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)
开发者ID:1ambda,项目名称:spark,代码行数:87,代码来源:worker.py


示例13: main

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)
开发者ID:0asa,项目名称:spark,代码行数:87,代码来源:worker.py


示例14: main

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

        # read inputs only for a barrier task
        isBarrier = read_bool(infile)
        boundPort = read_int(infile)
        secret = UTF8Deserializer().loads(infile)
        # initialize global state
        taskContext = None
        if isBarrier:
            taskContext = BarrierTaskContext._getOrCreate()
            BarrierTaskContext._initialize(boundPort, secret)
        else:
            taskContext = TaskContext._getOrCreate()
        # read inputs for TaskContext info
        taskContext._stageId = read_int(infile)
        taskContext._partitionId = read_int(infile)
        taskContext._attemptNumber = read_int(infile)
        taskContext._taskAttemptId = read_long(infile)
        taskContext._localProperties = dict()
        for i in range(read_int(infile)):
            k = utf8_deserializer.loads(infile)
            v = utf8_deserializer.loads(infile)
            taskContext._localProperties[k] = v

        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()
        eval_type = read_int(infile)
        if eval_type == PythonEvalType.NON_UDF:
            func, profiler, deserializer, serializer = read_command(pickleSer, infile)
        else:
            func, profiler, deserializer, serializer = read_udfs(pickleSer, infile, eval_type)

        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)
        sys.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)
#.........这里部分代码省略.........
开发者ID:lshoo,项目名称:spark,代码行数:101,代码来源:worker.py



注:本文中的pyspark.serializers.write_with_length函数示例由纯净天空整理自Github/MSDocs等源码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。


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