diff --git a/python/pyspark/context.py b/python/pyspark/context.py index 529d16b480399a6d5f21740abce5d6f704667ec1..cb15b4b91f9132ea682f2d8e421cbfaec360d06d 100644 --- a/python/pyspark/context.py +++ b/python/pyspark/context.py @@ -428,15 +428,19 @@ class SparkContext(object): # because it sends O(n) Py4J commands. As an alternative, serialized # objects are written to a file and loaded through textFile(). tempFile = NamedTemporaryFile(delete=False, dir=self._temp_dir) - # Make sure we distribute data evenly if it's smaller than self.batchSize - if "__len__" not in dir(c): - c = list(c) # Make it a list so we can compute its length - batchSize = max(1, min(len(c) // numSlices, self._batchSize or 1024)) - serializer = BatchedSerializer(self._unbatched_serializer, batchSize) - serializer.dump_stream(c, tempFile) - tempFile.close() - readRDDFromFile = self._jvm.PythonRDD.readRDDFromFile - jrdd = readRDDFromFile(self._jsc, tempFile.name, numSlices) + try: + # Make sure we distribute data evenly if it's smaller than self.batchSize + if "__len__" not in dir(c): + c = list(c) # Make it a list so we can compute its length + batchSize = max(1, min(len(c) // numSlices, self._batchSize or 1024)) + serializer = BatchedSerializer(self._unbatched_serializer, batchSize) + serializer.dump_stream(c, tempFile) + tempFile.close() + readRDDFromFile = self._jvm.PythonRDD.readRDDFromFile + jrdd = readRDDFromFile(self._jsc, tempFile.name, numSlices) + finally: + # readRDDFromFile eagerily reads the file so we can delete right after. + os.unlink(tempFile.name) return RDD(jrdd, self, serializer) def pickleFile(self, name, minPartitions=None): diff --git a/python/pyspark/tests.py b/python/pyspark/tests.py index 15c87e22f98b00ece735e4d094439d6ef23dfa35..97ea39dde05fa7e1e0ae9f69dc3446de93311ff7 100644 --- a/python/pyspark/tests.py +++ b/python/pyspark/tests.py @@ -1914,6 +1914,13 @@ class ContextTests(unittest.TestCase): with SparkContext.getOrCreate() as sc: self.assertTrue(SparkContext.getOrCreate() is sc) + def test_parallelize_eager_cleanup(self): + with SparkContext() as sc: + temp_files = os.listdir(sc._temp_dir) + rdd = sc.parallelize([0, 1, 2]) + post_parallalize_temp_files = os.listdir(sc._temp_dir) + self.assertEqual(temp_files, post_parallalize_temp_files) + def test_stop(self): sc = SparkContext() self.assertNotEqual(SparkContext._active_spark_context, None)