machielg commented on a change in pull request #25496: [PYTHON][WIP] pyspark
schema.toDDL() and DataType.fromDDL(ddl)
URL: https://github.com/apache/spark/pull/25496#discussion_r345142007
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File path: python/pyspark/sql/tests/test_types.py
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@@ -713,6 +713,27 @@ def assertCollectSuccess(typecode, value):
a = array.array(t)
self.spark.createDataFrame([Row(myarray=a)]).collect()
+ def test_to_ddl(self):
+ schemaExpected=StructType([
+ StructField("string",StringType(),True),
+ StructField("long",LongType(),True),
+ StructField("decimal",DecimalType(10,2),True),
+ StructField("timestamp",TimestampType(),True),
+ StructField("array1",ArrayType(StructType([
+ StructField("item1",LongType(),True),
+ StructField("array2",ArrayType(StructType([
+ StructField("item2",LongType(),True),
+ StructField("array2",ArrayType(StructType([
+ StructField("item3",LongType(),True),
+ StructField("item4",StringType(),True),
+ ]),True),True),
+ ]),True),True),
+ ]),True),True)
+ ])
+ ddl=schemaExpected.toDDL()
+ schemaActual=_parse_datatype_string(ddl)
+ self.assertEqual(schemaExpected, schemaActual)
Review comment:
I was expecting the schemaExpected to be string, not a result of calling the
method under test.
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