diff options
Diffstat (limited to 'python/pyspark/context.py')
-rw-r--r-- | python/pyspark/context.py | 29 |
1 files changed, 22 insertions, 7 deletions
diff --git a/python/pyspark/context.py b/python/pyspark/context.py index 2f741cb345..8fbf296509 100644 --- a/python/pyspark/context.py +++ b/python/pyspark/context.py @@ -46,6 +46,7 @@ class SparkContext(object): _next_accum_id = 0 _active_spark_context = None _lock = Lock() + _python_includes = None # zip and egg files that need to be added to PYTHONPATH def __init__(self, master, jobName, sparkHome=None, pyFiles=None, environment=None, batchSize=1024): @@ -103,16 +104,19 @@ class SparkContext(object): # send. self._pickled_broadcast_vars = set() + SparkFiles._sc = self + root_dir = SparkFiles.getRootDirectory() + sys.path.append(root_dir) + # Deploy any code dependencies specified in the constructor + self._python_includes = list() for path in (pyFiles or []): self.addPyFile(path) - SparkFiles._sc = self - sys.path.append(SparkFiles.getRootDirectory()) # Create a temporary directory inside spark.local.dir: - local_dir = self._jvm.spark.Utils.getLocalDir() + local_dir = self._jvm.org.apache.spark.util.Utils.getLocalDir() self._temp_dir = \ - self._jvm.spark.Utils.createTempDir(local_dir).getAbsolutePath() + self._jvm.org.apache.spark.util.Utils.createTempDir(local_dir).getAbsolutePath() @property def defaultParallelism(self): @@ -141,14 +145,21 @@ 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() @@ -250,7 +261,11 @@ class SparkContext(object): HTTP, HTTPS or FTP URI. """ self.addFile(path) - filename = path.split("/")[-1] + (dirname, filename) = os.path.split(path) # dirname may be directory or HDFS/S3 prefix + + if filename.endswith('.zip') or filename.endswith('.ZIP') or filename.endswith('.egg'): + self._python_includes.append(filename) + sys.path.append(os.path.join(SparkFiles.getRootDirectory(), filename)) # for tests in local mode def setCheckpointDir(self, dirName, useExisting=False): """ |