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author | Davies Liu <davies@databricks.com> | 2015-04-16 16:20:57 -0700 |
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committer | Josh Rosen <joshrosen@databricks.com> | 2015-04-16 16:20:57 -0700 |
commit | 04e44b37cc04f62fbf9e08c7076349e0a4d12ea8 (patch) | |
tree | b6429253955210445ddc37faa4d5166ea25a91e2 /python/pyspark/streaming/dstream.py | |
parent | 55f553a979db925aa0c3559f7e80b99d2bf3feb4 (diff) | |
download | spark-04e44b37cc04f62fbf9e08c7076349e0a4d12ea8.tar.gz spark-04e44b37cc04f62fbf9e08c7076349e0a4d12ea8.tar.bz2 spark-04e44b37cc04f62fbf9e08c7076349e0a4d12ea8.zip |
[SPARK-4897] [PySpark] Python 3 support
This PR update PySpark to support Python 3 (tested with 3.4).
Known issue: unpickle array from Pyrolite is broken in Python 3, those tests are skipped.
TODO: ec2/spark-ec2.py is not fully tested with python3.
Author: Davies Liu <davies@databricks.com>
Author: twneale <twneale@gmail.com>
Author: Josh Rosen <joshrosen@databricks.com>
Closes #5173 from davies/python3 and squashes the following commits:
d7d6323 [Davies Liu] fix tests
6c52a98 [Davies Liu] fix mllib test
99e334f [Davies Liu] update timeout
b716610 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
cafd5ec [Davies Liu] adddress comments from @mengxr
bf225d7 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
179fc8d [Davies Liu] tuning flaky tests
8c8b957 [Davies Liu] fix ResourceWarning in Python 3
5c57c95 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
4006829 [Davies Liu] fix test
2fc0066 [Davies Liu] add python3 path
71535e9 [Davies Liu] fix xrange and divide
5a55ab4 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
125f12c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ed498c8 [Davies Liu] fix compatibility with python 3
820e649 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
e8ce8c9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ad7c374 [Davies Liu] fix mllib test and warning
ef1fc2f [Davies Liu] fix tests
4eee14a [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
20112ff [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
59bb492 [Davies Liu] fix tests
1da268c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ca0fdd3 [Davies Liu] fix code style
9563a15 [Davies Liu] add imap back for python 2
0b1ec04 [Davies Liu] make python examples work with Python 3
d2fd566 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
a716d34 [Davies Liu] test with python 3.4
f1700e8 [Davies Liu] fix test in python3
671b1db [Davies Liu] fix test in python3
692ff47 [Davies Liu] fix flaky test
7b9699f [Davies Liu] invalidate import cache for Python 3.3+
9c58497 [Davies Liu] fix kill worker
309bfbf [Davies Liu] keep compatibility
5707476 [Davies Liu] cleanup, fix hash of string in 3.3+
8662d5b [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
f53e1f0 [Davies Liu] fix tests
70b6b73 [Davies Liu] compile ec2/spark_ec2.py in python 3
a39167e [Davies Liu] support customize class in __main__
814c77b [Davies Liu] run unittests with python 3
7f4476e [Davies Liu] mllib tests passed
d737924 [Davies Liu] pass ml tests
375ea17 [Davies Liu] SQL tests pass
6cc42a9 [Davies Liu] rename
431a8de [Davies Liu] streaming tests pass
78901a7 [Davies Liu] fix hash of serializer in Python 3
24b2f2e [Davies Liu] pass all RDD tests
35f48fe [Davies Liu] run future again
1eebac2 [Davies Liu] fix conflict in ec2/spark_ec2.py
6e3c21d [Davies Liu] make cloudpickle work with Python3
2fb2db3 [Josh Rosen] Guard more changes behind sys.version; still doesn't run
1aa5e8f [twneale] Turned out `pickle.DictionaryType is dict` == True, so swapped it out
7354371 [twneale] buffer --> memoryview I'm not super sure if this a valid change, but the 2.7 docs recommend using memoryview over buffer where possible, so hoping it'll work.
b69ccdf [twneale] Uses the pure python pickle._Pickler instead of c-extension _pickle.Pickler. It appears pyspark 2.7 uses the pure python pickler as well, so this shouldn't degrade pickling performance (?).
f40d925 [twneale] xrange --> range
e104215 [twneale] Replaces 2.7 types.InstsanceType with 3.4 `object`....could be horribly wrong depending on how types.InstanceType is used elsewhere in the package--see http://bugs.python.org/issue8206
79de9d0 [twneale] Replaces python2.7 `file` with 3.4 _io.TextIOWrapper
2adb42d [Josh Rosen] Fix up some import differences between Python 2 and 3
854be27 [Josh Rosen] Run `futurize` on Python code:
7c5b4ce [Josh Rosen] Remove Python 3 check in shell.py.
Diffstat (limited to 'python/pyspark/streaming/dstream.py')
-rw-r--r-- | python/pyspark/streaming/dstream.py | 51 |
1 files changed, 28 insertions, 23 deletions
diff --git a/python/pyspark/streaming/dstream.py b/python/pyspark/streaming/dstream.py index 3fa4244423..ff097985fa 100644 --- a/python/pyspark/streaming/dstream.py +++ b/python/pyspark/streaming/dstream.py @@ -15,11 +15,15 @@ # limitations under the License. # -from itertools import chain, ifilter, imap +import sys import operator import time +from itertools import chain from datetime import datetime +if sys.version < "3": + from itertools import imap as map, ifilter as filter + from py4j.protocol import Py4JJavaError from pyspark import RDD @@ -76,7 +80,7 @@ class DStream(object): Return a new DStream containing only the elements that satisfy predicate. """ def func(iterator): - return ifilter(f, iterator) + return filter(f, iterator) return self.mapPartitions(func, True) def flatMap(self, f, preservesPartitioning=False): @@ -85,7 +89,7 @@ class DStream(object): this DStream, and then flattening the results """ def func(s, iterator): - return chain.from_iterable(imap(f, iterator)) + return chain.from_iterable(map(f, iterator)) return self.mapPartitionsWithIndex(func, preservesPartitioning) def map(self, f, preservesPartitioning=False): @@ -93,7 +97,7 @@ class DStream(object): Return a new DStream by applying a function to each element of DStream. """ def func(iterator): - return imap(f, iterator) + return map(f, iterator) return self.mapPartitions(func, preservesPartitioning) def mapPartitions(self, f, preservesPartitioning=False): @@ -150,7 +154,7 @@ class DStream(object): """ Apply a function to each RDD in this DStream. """ - if func.func_code.co_argcount == 1: + if func.__code__.co_argcount == 1: old_func = func func = lambda t, rdd: old_func(rdd) jfunc = TransformFunction(self._sc, func, self._jrdd_deserializer) @@ -165,14 +169,14 @@ class DStream(object): """ def takeAndPrint(time, rdd): taken = rdd.take(num + 1) - print "-------------------------------------------" - print "Time: %s" % time - print "-------------------------------------------" + print("-------------------------------------------") + print("Time: %s" % time) + print("-------------------------------------------") for record in taken[:num]: - print record + print(record) if len(taken) > num: - print "..." - print + print("...") + print() self.foreachRDD(takeAndPrint) @@ -181,7 +185,7 @@ class DStream(object): Return a new DStream by applying a map function to the value of each key-value pairs in this DStream without changing the key. """ - map_values_fn = lambda (k, v): (k, f(v)) + map_values_fn = lambda kv: (kv[0], f(kv[1])) return self.map(map_values_fn, preservesPartitioning=True) def flatMapValues(self, f): @@ -189,7 +193,7 @@ class DStream(object): Return a new DStream by applying a flatmap function to the value of each key-value pairs in this DStream without changing the key. """ - flat_map_fn = lambda (k, v): ((k, x) for x in f(v)) + flat_map_fn = lambda kv: ((kv[0], x) for x in f(kv[1])) return self.flatMap(flat_map_fn, preservesPartitioning=True) def glom(self): @@ -286,10 +290,10 @@ class DStream(object): `func` can have one argument of `rdd`, or have two arguments of (`time`, `rdd`) """ - if func.func_code.co_argcount == 1: + if func.__code__.co_argcount == 1: oldfunc = func func = lambda t, rdd: oldfunc(rdd) - assert func.func_code.co_argcount == 2, "func should take one or two arguments" + assert func.__code__.co_argcount == 2, "func should take one or two arguments" return TransformedDStream(self, func) def transformWith(self, func, other, keepSerializer=False): @@ -300,10 +304,10 @@ class DStream(object): `func` can have two arguments of (`rdd_a`, `rdd_b`) or have three arguments of (`time`, `rdd_a`, `rdd_b`) """ - if func.func_code.co_argcount == 2: + if func.__code__.co_argcount == 2: oldfunc = func func = lambda t, a, b: oldfunc(a, b) - assert func.func_code.co_argcount == 3, "func should take two or three arguments" + assert func.__code__.co_argcount == 3, "func should take two or three arguments" jfunc = TransformFunction(self._sc, func, self._jrdd_deserializer, other._jrdd_deserializer) dstream = self._sc._jvm.PythonTransformed2DStream(self._jdstream.dstream(), other._jdstream.dstream(), jfunc) @@ -460,7 +464,7 @@ class DStream(object): keyed = self.map(lambda x: (1, x)) reduced = keyed.reduceByKeyAndWindow(reduceFunc, invReduceFunc, windowDuration, slideDuration, 1) - return reduced.map(lambda (k, v): v) + return reduced.map(lambda kv: kv[1]) def countByWindow(self, windowDuration, slideDuration): """ @@ -489,7 +493,7 @@ class DStream(object): keyed = self.map(lambda x: (x, 1)) counted = keyed.reduceByKeyAndWindow(operator.add, operator.sub, windowDuration, slideDuration, numPartitions) - return counted.filter(lambda (k, v): v > 0).count() + return counted.filter(lambda kv: kv[1] > 0).count() def groupByKeyAndWindow(self, windowDuration, slideDuration, numPartitions=None): """ @@ -548,7 +552,8 @@ class DStream(object): def invReduceFunc(t, a, b): b = b.reduceByKey(func, numPartitions) joined = a.leftOuterJoin(b, numPartitions) - return joined.mapValues(lambda (v1, v2): invFunc(v1, v2) if v2 is not None else v1) + return joined.mapValues(lambda kv: invFunc(kv[0], kv[1]) + if kv[1] is not None else kv[0]) jreduceFunc = TransformFunction(self._sc, reduceFunc, reduced._jrdd_deserializer) if invReduceFunc: @@ -579,9 +584,9 @@ class DStream(object): g = b.groupByKey(numPartitions).mapValues(lambda vs: (list(vs), None)) else: g = a.cogroup(b.partitionBy(numPartitions), numPartitions) - g = g.mapValues(lambda (va, vb): (list(vb), list(va)[0] if len(va) else None)) - state = g.mapValues(lambda (vs, s): updateFunc(vs, s)) - return state.filter(lambda (k, v): v is not None) + g = g.mapValues(lambda ab: (list(ab[1]), list(ab[0])[0] if len(ab[0]) else None)) + state = g.mapValues(lambda vs_s: updateFunc(vs_s[0], vs_s[1])) + return state.filter(lambda k_v: k_v[1] is not None) jreduceFunc = TransformFunction(self._sc, reduceFunc, self._sc.serializer, self._jrdd_deserializer) |