/
util.py
332 lines (275 loc) · 11.4 KB
/
util.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
# -*- coding: utf-8 -*-
#
# 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.
#
import itertools
import os
import platform
import re
import sys
import threading
import traceback
import types
from py4j.clientserver import ClientServer
__all__ = [] # type: ignore
def print_exec(stream):
ei = sys.exc_info()
traceback.print_exception(ei[0], ei[1], ei[2], None, stream)
class VersionUtils(object):
"""
Provides utility method to determine Spark versions with given input string.
"""
@staticmethod
def majorMinorVersion(sparkVersion):
"""
Given a Spark version string, return the (major version number, minor version number).
E.g., for 2.0.1-SNAPSHOT, return (2, 0).
Examples
--------
>>> sparkVersion = "2.4.0"
>>> VersionUtils.majorMinorVersion(sparkVersion)
(2, 4)
>>> sparkVersion = "2.3.0-SNAPSHOT"
>>> VersionUtils.majorMinorVersion(sparkVersion)
(2, 3)
"""
m = re.search(r'^(\d+)\.(\d+)(\..*)?$', sparkVersion)
if m is not None:
return (int(m.group(1)), int(m.group(2)))
else:
raise ValueError("Spark tried to parse '%s' as a Spark" % sparkVersion +
" version string, but it could not find the major and minor" +
" version numbers.")
def fail_on_stopiteration(f):
"""
Wraps the input function to fail on 'StopIteration' by raising a 'RuntimeError'
prevents silent loss of data when 'f' is used in a for loop in Spark code
"""
def wrapper(*args, **kwargs):
try:
return f(*args, **kwargs)
except StopIteration as exc:
raise RuntimeError(
"Caught StopIteration thrown from user's code; failing the task",
exc
)
return wrapper
def walk_tb(tb):
while tb is not None:
yield tb
tb = tb.tb_next
def try_simplify_traceback(tb):
"""
Simplify the traceback. It removes the tracebacks in the current package, and only
shows the traceback that is related to the thirdparty and user-specified codes.
Returns
-------
TracebackType or None
Simplified traceback instance. It returns None if it fails to simplify.
Notes
-----
This keeps the tracebacks once it sees they are from a different file even
though the following tracebacks are from the current package.
Examples
--------
>>> import importlib
>>> import sys
>>> import traceback
>>> import tempfile
>>> with tempfile.TemporaryDirectory() as tmp_dir:
... with open("%s/dummy_module.py" % tmp_dir, "w") as f:
... _ = f.write(
... 'def raise_stop_iteration():\\n'
... ' raise StopIteration()\\n\\n'
... 'def simple_wrapper(f):\\n'
... ' def wrapper(*a, **k):\\n'
... ' return f(*a, **k)\\n'
... ' return wrapper\\n')
... f.flush()
... spec = importlib.util.spec_from_file_location(
... "dummy_module", "%s/dummy_module.py" % tmp_dir)
... dummy_module = importlib.util.module_from_spec(spec)
... spec.loader.exec_module(dummy_module)
>>> def skip_doctest_traceback(tb):
... import pyspark
... root = os.path.dirname(pyspark.__file__)
... pairs = zip(walk_tb(tb), traceback.extract_tb(tb))
... for cur_tb, cur_frame in pairs:
... if cur_frame.filename.startswith(root):
... return cur_tb
Regular exceptions should show the file name of the current package as below.
>>> exc_info = None
>>> try:
... fail_on_stopiteration(dummy_module.raise_stop_iteration)()
... except Exception as e:
... tb = sys.exc_info()[-1]
... e.__cause__ = None
... exc_info = "".join(
... traceback.format_exception(type(e), e, tb))
>>> print(exc_info) # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
Traceback (most recent call last):
File ...
...
File "/.../pyspark/util.py", line ...
...
RuntimeError: ...
>>> "pyspark/util.py" in exc_info
True
If the traceback is simplified with this method, it hides the current package file name:
>>> exc_info = None
>>> try:
... fail_on_stopiteration(dummy_module.raise_stop_iteration)()
... except Exception as e:
... tb = try_simplify_traceback(sys.exc_info()[-1])
... e.__cause__ = None
... exc_info = "".join(
... traceback.format_exception(
... type(e), e, try_simplify_traceback(skip_doctest_traceback(tb))))
>>> print(exc_info) # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
RuntimeError: ...
>>> "pyspark/util.py" in exc_info
False
In the case below, the traceback contains the current package in the middle.
In this case, it just hides the top occurrence only.
>>> exc_info = None
>>> try:
... fail_on_stopiteration(dummy_module.simple_wrapper(
... fail_on_stopiteration(dummy_module.raise_stop_iteration)))()
... except Exception as e:
... tb = sys.exc_info()[-1]
... e.__cause__ = None
... exc_info_a = "".join(
... traceback.format_exception(type(e), e, tb))
... exc_info_b = "".join(
... traceback.format_exception(
... type(e), e, try_simplify_traceback(skip_doctest_traceback(tb))))
>>> exc_info_a.count("pyspark/util.py")
2
>>> exc_info_b.count("pyspark/util.py")
1
"""
if "pypy" in platform.python_implementation().lower():
# Traceback modification is not supported with PyPy in PySpark.
return None
if sys.version_info[:2] < (3, 7):
# Traceback creation is not supported Python < 3.7.
# See https://bugs.python.org/issue30579.
return None
import pyspark
root = os.path.dirname(pyspark.__file__)
tb_next = None
new_tb = None
pairs = zip(walk_tb(tb), traceback.extract_tb(tb))
last_seen = []
for cur_tb, cur_frame in pairs:
if not cur_frame.filename.startswith(root):
# Filter the stacktrace from the PySpark source itself.
last_seen = [(cur_tb, cur_frame)]
break
for cur_tb, cur_frame in reversed(list(itertools.chain(last_seen, pairs))):
# Once we have seen the file names outside, don't skip.
new_tb = types.TracebackType(
tb_next=tb_next,
tb_frame=cur_tb.tb_frame,
tb_lasti=cur_tb.tb_frame.f_lasti,
tb_lineno=cur_tb.tb_frame.f_lineno)
tb_next = new_tb
return new_tb
def _print_missing_jar(lib_name, pkg_name, jar_name, spark_version):
print("""
________________________________________________________________________________________________
Spark %(lib_name)s libraries not found in class path. Try one of the following.
1. Include the %(lib_name)s library and its dependencies with in the
spark-submit command as
$ bin/spark-submit --packages org.apache.spark:spark-%(pkg_name)s:%(spark_version)s ...
2. Download the JAR of the artifact from Maven Central http://search.maven.org/,
Group Id = org.apache.spark, Artifact Id = spark-%(jar_name)s, Version = %(spark_version)s.
Then, include the jar in the spark-submit command as
$ bin/spark-submit --jars <spark-%(jar_name)s.jar> ...
________________________________________________________________________________________________
""" % {
"lib_name": lib_name,
"pkg_name": pkg_name,
"jar_name": jar_name,
"spark_version": spark_version
})
def _parse_memory(s):
"""
Parse a memory string in the format supported by Java (e.g. 1g, 200m) and
return the value in MiB
Examples
--------
>>> _parse_memory("256m")
256
>>> _parse_memory("2g")
2048
"""
units = {'g': 1024, 'm': 1, 't': 1 << 20, 'k': 1.0 / 1024}
if s[-1].lower() not in units:
raise ValueError("invalid format: " + s)
return int(float(s[:-1]) * units[s[-1].lower()])
class InheritableThread(threading.Thread):
"""
Thread that is recommended to be used in PySpark instead of :class:`threading.Thread`
when the pinned thread mode is enabled. The usage of this class is exactly same as
:class:`threading.Thread` but correctly inherits the inheritable properties specific
to JVM thread such as ``InheritableThreadLocal``.
Also, note that pinned thread mode does not close the connection from Python
to JVM when the thread is finished in the Python side. With this class, Python
garbage-collects the Python thread instance and also closes the connection
which finishes JVM thread correctly.
When the pinned thread mode is off, this works as :class:`threading.Thread`.
.. versionadded:: 3.1.0
Notes
-----
This API is experimental.
"""
def __init__(self, target, *args, **kwargs):
from pyspark import SparkContext
sc = SparkContext._active_spark_context
if isinstance(sc._gateway, ClientServer):
# Here's when the pinned-thread mode (PYSPARK_PIN_THREAD) is on.
properties = sc._jsc.sc().getLocalProperties().clone()
self._sc = sc
def copy_local_properties(*a, **k):
sc._jsc.sc().setLocalProperties(properties)
return target(*a, **k)
super(InheritableThread, self).__init__(
target=copy_local_properties, *args, **kwargs)
else:
super(InheritableThread, self).__init__(target=target, *args, **kwargs)
def __del__(self):
from pyspark import SparkContext
if isinstance(SparkContext._gateway, ClientServer):
thread_connection = self._sc._jvm._gateway_client.thread_connection.connection()
if thread_connection is not None:
connections = self._sc._jvm._gateway_client.deque
# Reuse the lock for Py4J in PySpark
with SparkContext._lock:
for i in range(len(connections)):
if connections[i] is thread_connection:
connections[i].close()
del connections[i]
break
else:
# Just in case the connection was not closed but removed from the queue.
thread_connection.close()
if __name__ == "__main__":
import doctest
if "pypy" not in platform.python_implementation().lower() and sys.version_info[:2] >= (3, 7):
(failure_count, test_count) = doctest.testmod()
if failure_count:
sys.exit(-1)