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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/ml/feature.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/ml/feature.py')
-rw-r--r-- | python/pyspark/ml/feature.py | 22 |
1 files changed, 12 insertions, 10 deletions
diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py index 263fe2a5bc..4e4614b859 100644 --- a/python/pyspark/ml/feature.py +++ b/python/pyspark/ml/feature.py @@ -15,6 +15,7 @@ # limitations under the License. # +from pyspark.rdd import ignore_unicode_prefix from pyspark.ml.param.shared import HasInputCol, HasOutputCol, HasNumFeatures from pyspark.ml.util import keyword_only from pyspark.ml.wrapper import JavaTransformer @@ -24,6 +25,7 @@ __all__ = ['Tokenizer', 'HashingTF'] @inherit_doc +@ignore_unicode_prefix class Tokenizer(JavaTransformer, HasInputCol, HasOutputCol): """ A tokenizer that converts the input string to lowercase and then @@ -32,15 +34,15 @@ class Tokenizer(JavaTransformer, HasInputCol, HasOutputCol): >>> from pyspark.sql import Row >>> df = sc.parallelize([Row(text="a b c")]).toDF() >>> tokenizer = Tokenizer(inputCol="text", outputCol="words") - >>> print tokenizer.transform(df).head() + >>> tokenizer.transform(df).head() Row(text=u'a b c', words=[u'a', u'b', u'c']) >>> # Change a parameter. - >>> print tokenizer.setParams(outputCol="tokens").transform(df).head() + >>> tokenizer.setParams(outputCol="tokens").transform(df).head() Row(text=u'a b c', tokens=[u'a', u'b', u'c']) >>> # Temporarily modify a parameter. - >>> print tokenizer.transform(df, {tokenizer.outputCol: "words"}).head() + >>> tokenizer.transform(df, {tokenizer.outputCol: "words"}).head() Row(text=u'a b c', words=[u'a', u'b', u'c']) - >>> print tokenizer.transform(df).head() + >>> tokenizer.transform(df).head() Row(text=u'a b c', tokens=[u'a', u'b', u'c']) >>> # Must use keyword arguments to specify params. >>> tokenizer.setParams("text") @@ -79,13 +81,13 @@ class HashingTF(JavaTransformer, HasInputCol, HasOutputCol, HasNumFeatures): >>> from pyspark.sql import Row >>> df = sc.parallelize([Row(words=["a", "b", "c"])]).toDF() >>> hashingTF = HashingTF(numFeatures=10, inputCol="words", outputCol="features") - >>> print hashingTF.transform(df).head().features - (10,[7,8,9],[1.0,1.0,1.0]) - >>> print hashingTF.setParams(outputCol="freqs").transform(df).head().freqs - (10,[7,8,9],[1.0,1.0,1.0]) + >>> hashingTF.transform(df).head().features + SparseVector(10, {7: 1.0, 8: 1.0, 9: 1.0}) + >>> hashingTF.setParams(outputCol="freqs").transform(df).head().freqs + SparseVector(10, {7: 1.0, 8: 1.0, 9: 1.0}) >>> params = {hashingTF.numFeatures: 5, hashingTF.outputCol: "vector"} - >>> print hashingTF.transform(df, params).head().vector - (5,[2,3,4],[1.0,1.0,1.0]) + >>> hashingTF.transform(df, params).head().vector + SparseVector(5, {2: 1.0, 3: 1.0, 4: 1.0}) """ _java_class = "org.apache.spark.ml.feature.HashingTF" |