Github user gliptak commented on a diff in the pull request:
https://github.com/apache/spark/pull/9263#discussion_r43250312
--- Diff: python/pyspark/mllib/tests.py ---
@@ -76,7 +76,8 @@
pass
ser = PickleSerializer()
-sc = SparkContext('local[4]', "MLlib tests")
+conf = SparkConf().set("spark.driver.allowMultipleContexts", "true")
--- End diff --
Reviewing the tests.py-s
https://github.com/apache/spark/blob/master/python/pyspark/streaming/tests.py
initiates SparkContext differently:
```
@classmethod
def setUpClass(cls):
class_name = cls.__name__
conf = SparkConf().set("spark.default.parallelism", 1)
cls.sc = SparkContext(appName=class_name, conf=conf)
cls.sc.setCheckpointDir("/tmp")
@classmethod
def tearDownClass(cls):
cls.sc.stop()
# Clean up in the JVM just in case there has been some issues in
Python API
try:
jSparkContextOption = SparkContext._jvm.SparkContext.get()
if jSparkContextOption.nonEmpty():
jSparkContextOption.get().stop()
except:
pass
```
Could this approach be retrofitted into
https://github.com/apache/spark/blob/master/python/pyspark/mllib/tests.py to
allow for concurrency?
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