diff --git a/python/pyspark/rdd.py b/python/pyspark/rdd.py
index d3148de6f41a3..e57d9c767e43a 100644
--- a/python/pyspark/rdd.py
+++ b/python/pyspark/rdd.py
@@ -577,7 +577,7 @@ def sortPartition(iterator):
         maxSampleSize = numPartitions * 20.0  # constant from Spark's RangePartitioner
         fraction = min(maxSampleSize / max(rddSize, 1), 1.0)
         samples = self.sample(False, fraction, 1).map(lambda (k, v): k).collect()
-        samples = sorted(samples, reverse=(not ascending), key=keyfunc)
+        samples = sorted(samples, key=keyfunc)
 
         # we have numPartitions many parts but one of the them has
         # an implicit boundary
diff --git a/python/pyspark/tests.py b/python/pyspark/tests.py
index 06ba2b461d53e..39e277fdbb934 100644
--- a/python/pyspark/tests.py
+++ b/python/pyspark/tests.py
@@ -782,6 +782,17 @@ def test_narrow_dependency_in_join(self):
         jobId = tracker.getJobIdsForGroup("test4")[0]
         self.assertEqual(3, len(tracker.getJobInfo(jobId).stageIds))
 
+    def test_sortByKey_uses_all_partitions_not_only_first_and_last(self):
+        # Regression test for SPARK-5969
+        seq = [(i * 59 % 101, i) for i in range(101)]  # unsorted sequence
+        rdd = self.sc.parallelize(seq)
+        for ascending in [True, False]:
+            sort = rdd.sortByKey(ascending=ascending, numPartitions=5)
+            self.assertEqual(sort.collect(), sorted(seq, reverse=not ascending))
+            sizes = sort.glom().map(len).collect()
+            for size in sizes:
+                self.assertGreater(size, 0)
+
 
 class ProfilerTests(PySparkTestCase):