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 RuntimeError((
"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)
# set up memory limits
memory_limit_mb = int(
os.environ.get('PYSPARK_EXECUTOR_MEMORY_MB', "-1"))
if memory_limit_mb > 0 and has_resource_module:
total_memory = resource.RLIMIT_AS
try:
(soft_limit, hard_limit) = resource.getrlimit(total_memory)
msg = "Current mem limits: {0} of max {1}\n".format(
soft_limit, hard_limit)
print(msg, file=sys.stderr)
# convert to bytes
new_limit = memory_limit_mb * 1024 * 1024
if soft_limit == resource.RLIM_INFINITY or new_limit < soft_limit:
msg = "Setting mem limits to {0} of max {1}\n".format(
new_limit, new_limit)
print(msg, file=sys.stderr)
resource.setrlimit(total_memory, (new_limit, new_limit))
except (resource.error, OSError, ValueError) as e:
# not all systems support resource limits, so warn instead of failing
lineno = getframeinfo(currentframe(
)).lineno + 1 if currentframe() is not None else 0
print(warnings.formatwarning(
"Failed to set memory limit: {0}".format(e),
ResourceWarning, __file__, lineno),
file=sys.stderr)
# initialize global state
taskContext = None
if isBarrier:
taskContext = BarrierTaskContext._getOrCreate()
BarrierTaskContext._initialize(boundPort, secret)
# Set the task context instance here, so we can get it by TaskContext.get for
# both TaskContext and BarrierTaskContext
TaskContext._setTaskContext(taskContext)
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._resources = {}
for r in range(read_int(infile)):
key = utf8_deserializer.loads(infile)
name = utf8_deserializer.loads(infile)
addresses = []
taskContext._resources = {}
for a in range(read_int(infile)):
addresses.append(utf8_deserializer.loads(infile))
taskContext._resources[key] = ResourceInformation(name, addresses)
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))
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)
out_iter = func(split_index, iterator)
try:
serializer.dump_stream(out_iter, outfile)
finally:
if hasattr(out_iter, 'close'):
out_iter.close()
if profiler:
profiler.profile(process)
else:
process()
# Reset task context to None. This is a guard code to avoid residual context when worker
# reuse.
TaskContext._setTaskContext(None)
BarrierTaskContext._setTaskContext(None)
except BaseException as e:
try:
exc_info = None
if os.environ.get("SPARK_SIMPLIFIED_TRACEBACK", False):
tb = try_simplify_traceback(sys.exc_info()[-1])
if tb is not None:
e.__cause__ = None
exc_info = "".join(
traceback.format_exception(type(e), e, tb))
if exc_info is None:
exc_info = traceback.format_exc()
write_int(SpecialLengths.PYTHON_EXCEPTION_THROWN, outfile)
write_with_length(exc_info.encode("utf-8"), outfile)
except IOError:
# JVM close the socket
pass
except BaseException:
# 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)
# http://spark.apache.org/docs/latest/api/python/pyspark.resource.html
# New in version 3.0.0.
from pyspark import SparkContext
from pyspark.resource import ResourceInformation
r = ResourceInformation("name", [])
sc = SparkContext(jsc=None)
# SparkContext使用Py4J启动JVM并创建JavaSparkContext。
# 由jsc传入的
# jsc: The JavaSparkContext instance (optional).
# SparkContext(jsc=xx)
"""
源码
Create the Java SparkContext through Py4J
self._jsc = jsc or self._initialize_context(self._conf._jconf)
"""
print(sc.resources)