diff options
| -rw-r--r-- | python/pyspark/context.py | 11 |
1 files changed, 9 insertions, 2 deletions
diff --git a/python/pyspark/context.py b/python/pyspark/context.py index 2f741cb345..c2b49ff37a 100644 --- a/python/pyspark/context.py +++ b/python/pyspark/context.py @@ -141,14 +141,21 @@ class SparkContext(object): def parallelize(self, c, numSlices=None): """ Distribute a local Python collection to form an RDD. + + >>> sc.parallelize(range(5), 5).glom().collect() + [[0], [1], [2], [3], [4]] """ numSlices = numSlices or self.defaultParallelism # Calling the Java parallelize() method with an ArrayList is too slow, # 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) - if self.batchSize != 1: - c = batched(c, self.batchSize) + # 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 = min(len(c) // numSlices, self.batchSize) + if batchSize > 1: + c = batched(c, batchSize) for x in c: write_with_length(dump_pickle(x), tempFile) tempFile.close() |