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-rw-r--r--python/pyspark/sql/dataframe.py4
-rw-r--r--python/pyspark/sql/tests.py4
2 files changed, 4 insertions, 4 deletions
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index 5cfc348a69..7a69c4c70c 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -360,7 +360,7 @@ class DataFrame(object):
>>> df.repartition(10).rdd.getNumPartitions()
10
- >>> data = df.unionAll(df).repartition("age")
+ >>> data = df.union(df).repartition("age")
>>> data.show()
+---+-----+
|age| name|
@@ -919,7 +919,7 @@ class DataFrame(object):
This is equivalent to `UNION ALL` in SQL. To do a SQL-style set union
(that does deduplication of elements), use this function followed by a distinct.
"""
- return DataFrame(self._jdf.unionAll(other._jdf), self.sql_ctx)
+ return DataFrame(self._jdf.union(other._jdf), self.sql_ctx)
@since(1.3)
def unionAll(self, other):
diff --git a/python/pyspark/sql/tests.py b/python/pyspark/sql/tests.py
index 9722e9e9ca..83ef76c13c 100644
--- a/python/pyspark/sql/tests.py
+++ b/python/pyspark/sql/tests.py
@@ -599,7 +599,7 @@ class SQLTests(ReusedPySparkTestCase):
point = df1.head().point
self.assertEqual(point, PythonOnlyPoint(1.0, 2.0))
- def test_unionAll_with_udt(self):
+ def test_union_with_udt(self):
from pyspark.sql.tests import ExamplePoint, ExamplePointUDT
row1 = (1.0, ExamplePoint(1.0, 2.0))
row2 = (2.0, ExamplePoint(3.0, 4.0))
@@ -608,7 +608,7 @@ class SQLTests(ReusedPySparkTestCase):
df1 = self.sqlCtx.createDataFrame([row1], schema)
df2 = self.sqlCtx.createDataFrame([row2], schema)
- result = df1.unionAll(df2).orderBy("label").collect()
+ result = df1.union(df2).orderBy("label").collect()
self.assertEqual(
result,
[