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author | felixcheung <felixcheung_m@hotmail.com> | 2016-04-19 17:29:28 -0700 |
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committer | Davies Liu <davies.liu@gmail.com> | 2016-04-19 17:29:28 -0700 |
commit | 3664142350afb6bf40a8bcb3508b56670603dae4 (patch) | |
tree | 31d89a8d4f7ec6e57b61c404cafc3d34319428f5 /python/pyspark | |
parent | a685e65a4ca0b300b12103fccbda29cb08221f5d (diff) | |
download | spark-3664142350afb6bf40a8bcb3508b56670603dae4.tar.gz spark-3664142350afb6bf40a8bcb3508b56670603dae4.tar.bz2 spark-3664142350afb6bf40a8bcb3508b56670603dae4.zip |
[SPARK-14717] [PYTHON] Scala, Python APIs for Dataset.unpersist differ in default blocking value
## What changes were proposed in this pull request?
Change unpersist blocking parameter default value to match Scala
## How was this patch tested?
unit tests, manual tests
jkbradley davies
Author: felixcheung <felixcheung_m@hotmail.com>
Closes #12507 from felixcheung/pyunpersist.
Diffstat (limited to 'python/pyspark')
-rw-r--r-- | python/pyspark/sql/dataframe.py | 4 | ||||
-rw-r--r-- | python/pyspark/sql/tests.py | 2 |
2 files changed, 4 insertions, 2 deletions
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py index b4fa836893..328bda6601 100644 --- a/python/pyspark/sql/dataframe.py +++ b/python/pyspark/sql/dataframe.py @@ -326,9 +326,11 @@ class DataFrame(object): return self @since(1.3) - def unpersist(self, blocking=True): + def unpersist(self, blocking=False): """Marks the :class:`DataFrame` as non-persistent, and remove all blocks for it from memory and disk. + + .. note:: `blocking` default has changed to False to match Scala in 2.0. """ self.is_cached = False self._jdf.unpersist(blocking) diff --git a/python/pyspark/sql/tests.py b/python/pyspark/sql/tests.py index e4f79c911c..d4c221d712 100644 --- a/python/pyspark/sql/tests.py +++ b/python/pyspark/sql/tests.py @@ -362,7 +362,7 @@ class SQLTests(ReusedPySparkTestCase): # cache and checkpoint self.assertFalse(df.is_cached) df.persist() - df.unpersist() + df.unpersist(True) df.cache() self.assertTrue(df.is_cached) self.assertEqual(2, df.count()) |