Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/17077#discussion_r111214507
--- Diff: python/pyspark/sql/tests.py ---
@@ -2167,6 +2167,56 @@ def test_BinaryType_serialization(self):
df = self.spark.createDataFrame(data, schema=schema)
df.collect()
+ def test_bucketed_write(self):
+ data = [
+ (1, "foo", 3.0), (2, "foo", 5.0),
+ (3, "bar", -1.0), (4, "bar", 6.0),
+ ]
+ df = self.spark.createDataFrame(data, ["x", "y", "z"])
+
+ def count_bucketed_cols(names, table="pyspark_bucket"):
+ """Given a sequence of column names and a table name
+ query the catalog and return number o columns which are
+ used for bucketing
+ """
+ cols = self.spark.catalog.listColumns(table)
+ num = len([c for c in cols if c.name in names and c.isBucket])
+ return num
+
+ # Test write with one bucketing column
+ df.write.bucketBy(3,
"x").mode("overwrite").saveAsTable("pyspark_bucket")
+ self.assertEqual(count_bucketed_cols(["x"]), 1)
+ self.assertSetEqual(set(data),
set(self.spark.table("pyspark_bucket").collect()))
+
+ # Test write two bucketing columns
+ df.write.bucketBy(3, "x",
"y").mode("overwrite").saveAsTable("pyspark_bucket")
+ self.assertEqual(count_bucketed_cols(["x", "y"]), 2)
+ self.assertSetEqual(set(data),
set(self.spark.table("pyspark_bucket").collect()))
+
+ # Test write with bucket and sort
+ df.write.bucketBy(2,
"x").sortBy("z").mode("overwrite").saveAsTable("pyspark_bucket")
+ self.assertEqual(count_bucketed_cols(["x"]), 1)
+ self.assertSetEqual(set(data),
set(self.spark.table("pyspark_bucket").collect()))
+
+ # Test write with a list of columns
+ df.write.bucketBy(3, ["x",
"y"]).mode("overwrite").saveAsTable("pyspark_bucket")
+ self.assertEqual(count_bucketed_cols(["x", "y"]), 2)
+ self.assertSetEqual(set(data),
set(self.spark.table("pyspark_bucket").collect()))
+
+ # Test write with bucket and sort with a list of columns
+ (df.write.bucketBy(2, "x")
+ .sortBy(["y", "z"])
+ .mode("overwrite").saveAsTable("pyspark_bucket"))
+ self.assertSetEqual(set(data),
set(self.spark.table("pyspark_bucket").collect()))
+
+ # Test write with bucket and sort with multiple columns
+ (df.write.bucketBy(2, "x")
+ .sortBy("y", "z")
+ .mode("overwrite").saveAsTable("pyspark_bucket"))
+ self.assertSetEqual(set(data),
set(self.spark.table("pyspark_bucket").collect()))
+
+ self.spark.sql("DROP TABLE IF EXISTS pyspark_bucket")
--- End diff --
If we're going to drop the table here we should probably put it in a final
block.
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