[SPARK-10710] Remove ability to disable spilling in core and SQL

It does not make much sense to set `spark.shuffle.spill` or `spark.sql.planner.externalSort` to false: I believe that these configurations were initially added as "escape hatches" to guard against bugs in the external operators, but these operators are now mature and well-tested. In addition, these configurations are not handled in a consistent way anymore: SQL's Tungsten codepath ignores these configurations and will continue to use spilling operators. Similarly, Spark Core's `tungsten-sort` shuffle manager does not respect `spark.shuffle.spill=false`.

This pull request removes these configurations, adds warnings at the appropriate places, and deletes a large amount of code which was only used in code paths that did not support spilling.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #8831 from JoshRosen/remove-ability-to-disable-spilling.

1 files changed, 1 insertions, 12 deletions

diff --git a/python/pyspark/tests.py b/python/pyspark/tests.py
index 647504c32f..f11aaf001c 100644
--- a/python/pyspark/tests.py
+++ b/python/pyspark/tests.py
@@ -62,7 +62,7 @@ from pyspark.serializers import read_int, BatchedSerializer, MarshalSerializer,
     CloudPickleSerializer, CompressedSerializer, UTF8Deserializer, NoOpSerializer, \
     PairDeserializer, CartesianDeserializer, AutoBatchedSerializer, AutoSerializer, \
     FlattenedValuesSerializer
-from pyspark.shuffle import Aggregator, InMemoryMerger, ExternalMerger, ExternalSorter
+from pyspark.shuffle import Aggregator, ExternalMerger, ExternalSorter
 from pyspark import shuffle
 from pyspark.profiler import BasicProfiler
 
@@ -95,17 +95,6 @@ class MergerTests(unittest.TestCase):
                               lambda x, y: x.append(y) or x,
                               lambda x, y: x.extend(y) or x)
 
-    def test_in_memory(self):
-        m = InMemoryMerger(self.agg)
-        m.mergeValues(self.data)
-        self.assertEqual(sum(sum(v) for k, v in m.items()),
-                         sum(xrange(self.N)))
-
-        m = InMemoryMerger(self.agg)
-        m.mergeCombiners(map(lambda x_y: (x_y[0], [x_y[1]]), self.data))
-        self.assertEqual(sum(sum(v) for k, v in m.items()),
-                         sum(xrange(self.N)))
-
     def test_small_dataset(self):
         m = ExternalMerger(self.agg, 1000)
         m.mergeValues(self.data)