allisonwang-db commented on code in PR #49961:
URL: https://github.com/apache/spark/pull/49961#discussion_r2002140192
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonDataSourceSuite.scala:
##########
@@ -213,6 +220,66 @@ class PythonDataSourceSuite extends
PythonDataSourceSuiteBase {
parameters = Map("inputSchema" -> "INT", "dataType" -> "\"INT\""))
}
+ test("data source reader with filter pushdown") {
+ assume(shouldTestPandasUDFs)
+ val dataSourceScript =
+ s"""
+ |from pyspark.sql.datasource import (
+ | DataSource,
+ | DataSourceReader,
+ | EqualTo,
+ | InputPartition,
+ |)
+ |
+ |class SimpleDataSourceReader(DataSourceReader):
+ | def partitions(self):
+ | return [InputPartition(i) for i in range(2)]
+ |
+ | def pushFilters(self, filters):
+ | yield filters[filters.index(EqualTo(("id",), 1))]
+ |
+ | def read(self, partition):
+ | yield (0, partition.value)
+ | yield (1, partition.value)
+ | yield (2, partition.value)
+ |
+ |class SimpleDataSource(DataSource):
+ | def schema(self):
+ | return "id int, partition int"
+ |
+ | def reader(self, schema):
+ | return SimpleDataSourceReader()
+ |""".stripMargin
+ val schema = StructType.fromDDL("id INT, partition INT")
+ val dataSource =
+ createUserDefinedPythonDataSource(name = dataSourceName, pythonScript =
dataSourceScript)
+ spark.conf.set(SQLConf.PYTHON_FILTER_PUSHDOWN_ENABLED, true)
Review Comment:
Let's use `withSQLConf`
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonDataSourceSuite.scala:
##########
@@ -213,6 +220,66 @@ class PythonDataSourceSuite extends
PythonDataSourceSuiteBase {
parameters = Map("inputSchema" -> "INT", "dataType" -> "\"INT\""))
}
+ test("data source reader with filter pushdown") {
+ assume(shouldTestPandasUDFs)
+ val dataSourceScript =
+ s"""
+ |from pyspark.sql.datasource import (
+ | DataSource,
+ | DataSourceReader,
+ | EqualTo,
+ | InputPartition,
+ |)
+ |
+ |class SimpleDataSourceReader(DataSourceReader):
+ | def partitions(self):
+ | return [InputPartition(i) for i in range(2)]
+ |
+ | def pushFilters(self, filters):
+ | yield filters[filters.index(EqualTo(("id",), 1))]
+ |
+ | def read(self, partition):
+ | yield (0, partition.value)
+ | yield (1, partition.value)
+ | yield (2, partition.value)
+ |
+ |class SimpleDataSource(DataSource):
+ | def schema(self):
+ | return "id int, partition int"
+ |
+ | def reader(self, schema):
+ | return SimpleDataSourceReader()
+ |""".stripMargin
+ val schema = StructType.fromDDL("id INT, partition INT")
+ val dataSource =
+ createUserDefinedPythonDataSource(name = dataSourceName, pythonScript =
dataSourceScript)
+ spark.conf.set(SQLConf.PYTHON_FILTER_PUSHDOWN_ENABLED, true)
Review Comment:
Can we also add another test case with this config disabled?
##########
python/pyspark/sql/tests/test_python_datasource.py:
##########
@@ -246,6 +251,161 @@ def reader(self, schema) -> "DataSourceReader":
assertDataFrameEqual(df, [Row(x=0, y="0"), Row(x=1, y="1")])
self.assertEqual(df.select(spark_partition_id()).distinct().count(), 2)
+ def test_filter_pushdown(self):
+ class TestDataSourceReader(DataSourceReader):
+ def __init__(self):
+ self.has_filter = False
+
+ def pushFilters(self, filters: List[Filter]) -> Iterable[Filter]:
+ assert set(filters) == {
+ EqualTo(("x",), 1),
+ EqualTo(("y",), 2),
+ }, filters
+ self.has_filter = True
+ # pretend we support x = 1 filter but in fact we don't
+ # so we only return y = 2 filter
+ yield filters[filters.index(EqualTo(("y",), 2))]
+
+ def partitions(self):
+ assert self.has_filter
+ return super().partitions()
+
+ def read(self, partition):
+ assert self.has_filter
+ yield [1, 1]
+ yield [1, 2]
+ yield [2, 2]
+
+ class TestDataSource(DataSource):
+ @classmethod
+ def name(cls):
+ return "test"
+
+ def schema(self):
+ return "x int, y int"
+
+ def reader(self, schema) -> "DataSourceReader":
+ return TestDataSourceReader()
+
+ self.spark.conf.set("spark.sql.python.filterPushdown.enabled", True)
Review Comment:
let's use `with self.sql_conf`
##########
python/pyspark/sql/tests/test_python_datasource.py:
##########
@@ -246,6 +251,161 @@ def reader(self, schema) -> "DataSourceReader":
assertDataFrameEqual(df, [Row(x=0, y="0"), Row(x=1, y="1")])
self.assertEqual(df.select(spark_partition_id()).distinct().count(), 2)
+ def test_filter_pushdown(self):
+ class TestDataSourceReader(DataSourceReader):
+ def __init__(self):
+ self.has_filter = False
+
+ def pushFilters(self, filters: List[Filter]) -> Iterable[Filter]:
+ assert set(filters) == {
+ EqualTo(("x",), 1),
+ EqualTo(("y",), 2),
+ }, filters
+ self.has_filter = True
+ # pretend we support x = 1 filter but in fact we don't
+ # so we only return y = 2 filter
+ yield filters[filters.index(EqualTo(("y",), 2))]
+
+ def partitions(self):
+ assert self.has_filter
+ return super().partitions()
+
+ def read(self, partition):
+ assert self.has_filter
+ yield [1, 1]
+ yield [1, 2]
+ yield [2, 2]
+
+ class TestDataSource(DataSource):
+ @classmethod
+ def name(cls):
+ return "test"
+
+ def schema(self):
+ return "x int, y int"
+
+ def reader(self, schema) -> "DataSourceReader":
+ return TestDataSourceReader()
+
+ self.spark.conf.set("spark.sql.python.filterPushdown.enabled", True)
+ self.spark.dataSource.register(TestDataSource)
+ df = self.spark.read.format("test").load().filter("x = 1 and y = 2")
+ # only the y = 2 filter is applied post scan
+ assertDataFrameEqual(df, [Row(x=1, y=2), Row(x=2, y=2)])
+
+ def test_extraneous_filter(self):
+ class TestDataSourceReader(DataSourceReader):
+ def pushFilters(self, filters: List[Filter]) -> Iterable[Filter]:
+ yield EqualTo(("x",), 1)
+
+ def partitions(self):
+ assert False
+
+ def read(self, partition):
+ assert False
+
+ class TestDataSource(DataSource):
+ @classmethod
+ def name(cls):
+ return "test"
+
+ def schema(self):
+ return "x int"
+
+ def reader(self, schema) -> "DataSourceReader":
+ return TestDataSourceReader()
+
+ self.spark.conf.set("spark.sql.python.filterPushdown.enabled", True)
+ self.spark.dataSource.register(TestDataSource)
+ with self.assertRaisesRegex(Exception,
"DATA_SOURCE_EXTRANEOUS_FILTERS"):
+ self.spark.read.format("test").load().filter("x = 1").show()
+
+ def test_filter_pushdown_error(self):
+ error_str = "dummy error"
+
+ class TestDataSourceReader(DataSourceReader):
+ def pushFilters(self, filters: List[Filter]) -> Iterable[Filter]:
+ raise Exception(error_str)
+
+ def read(self, partition):
+ yield [1]
+
+ class TestDataSource(DataSource):
+ def schema(self):
+ return "x int"
+
+ def reader(self, schema) -> "DataSourceReader":
+ return TestDataSourceReader()
+
+ self.spark.conf.set("spark.sql.python.filterPushdown.enabled", True)
+ self.spark.dataSource.register(TestDataSource)
+ df = self.spark.read.format("TestDataSource").load().filter("x = 1 or
x is null")
+ assertDataFrameEqual(df, [Row(x=1)]) # works when not pushing down
filters
+ with self.assertRaisesRegex(Exception, error_str):
+ df.filter("x = 1").explain()
+
+ def test_filter_pushdown_disabled(self):
+ class TestDataSourceReader(DataSourceReader):
+ def pushFilters(self, filters: List[Filter]) -> Iterable[Filter]:
+ assert False
+
+ def read(self, partition):
+ assert False
+
+ class TestDataSource(DataSource):
+ def reader(self, schema) -> "DataSourceReader":
+ return TestDataSourceReader()
+
+ self.spark.conf.set("spark.sql.python.filterPushdown.enabled", False)
Review Comment:
ditto
##########
python/pyspark/sql/tests/test_python_datasource.py:
##########
@@ -246,6 +251,161 @@ def reader(self, schema) -> "DataSourceReader":
assertDataFrameEqual(df, [Row(x=0, y="0"), Row(x=1, y="1")])
self.assertEqual(df.select(spark_partition_id()).distinct().count(), 2)
+ def test_filter_pushdown(self):
+ class TestDataSourceReader(DataSourceReader):
+ def __init__(self):
+ self.has_filter = False
+
+ def pushFilters(self, filters: List[Filter]) -> Iterable[Filter]:
+ assert set(filters) == {
+ EqualTo(("x",), 1),
+ EqualTo(("y",), 2),
+ }, filters
+ self.has_filter = True
+ # pretend we support x = 1 filter but in fact we don't
+ # so we only return y = 2 filter
+ yield filters[filters.index(EqualTo(("y",), 2))]
+
+ def partitions(self):
+ assert self.has_filter
+ return super().partitions()
+
+ def read(self, partition):
+ assert self.has_filter
+ yield [1, 1]
+ yield [1, 2]
+ yield [2, 2]
+
+ class TestDataSource(DataSource):
+ @classmethod
+ def name(cls):
+ return "test"
+
+ def schema(self):
+ return "x int, y int"
+
+ def reader(self, schema) -> "DataSourceReader":
+ return TestDataSourceReader()
+
+ self.spark.conf.set("spark.sql.python.filterPushdown.enabled", True)
+ self.spark.dataSource.register(TestDataSource)
+ df = self.spark.read.format("test").load().filter("x = 1 and y = 2")
+ # only the y = 2 filter is applied post scan
+ assertDataFrameEqual(df, [Row(x=1, y=2), Row(x=2, y=2)])
+
+ def test_extraneous_filter(self):
+ class TestDataSourceReader(DataSourceReader):
+ def pushFilters(self, filters: List[Filter]) -> Iterable[Filter]:
+ yield EqualTo(("x",), 1)
+
+ def partitions(self):
+ assert False
+
+ def read(self, partition):
+ assert False
+
+ class TestDataSource(DataSource):
+ @classmethod
+ def name(cls):
+ return "test"
+
+ def schema(self):
+ return "x int"
+
+ def reader(self, schema) -> "DataSourceReader":
+ return TestDataSourceReader()
+
+ self.spark.conf.set("spark.sql.python.filterPushdown.enabled", True)
Review Comment:
ditto
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonDataSourceSuite.scala:
##########
@@ -213,6 +220,66 @@ class PythonDataSourceSuite extends
PythonDataSourceSuiteBase {
parameters = Map("inputSchema" -> "INT", "dataType" -> "\"INT\""))
}
+ test("data source reader with filter pushdown") {
+ assume(shouldTestPandasUDFs)
+ val dataSourceScript =
+ s"""
+ |from pyspark.sql.datasource import (
+ | DataSource,
+ | DataSourceReader,
+ | EqualTo,
+ | InputPartition,
+ |)
+ |
+ |class SimpleDataSourceReader(DataSourceReader):
+ | def partitions(self):
+ | return [InputPartition(i) for i in range(2)]
+ |
+ | def pushFilters(self, filters):
+ | yield filters[filters.index(EqualTo(("id",), 1))]
+ |
+ | def read(self, partition):
+ | yield (0, partition.value)
+ | yield (1, partition.value)
+ | yield (2, partition.value)
+ |
+ |class SimpleDataSource(DataSource):
+ | def schema(self):
+ | return "id int, partition int"
+ |
+ | def reader(self, schema):
+ | return SimpleDataSourceReader()
+ |""".stripMargin
+ val schema = StructType.fromDDL("id INT, partition INT")
+ val dataSource =
+ createUserDefinedPythonDataSource(name = dataSourceName, pythonScript =
dataSourceScript)
+ spark.conf.set(SQLConf.PYTHON_FILTER_PUSHDOWN_ENABLED, true)
+ spark.dataSource.registerPython(dataSourceName, dataSource)
+ val df =
+ spark.read.format(dataSourceName).schema(schema).load().filter("id = 1
and partition = 0")
+ val plan = df.queryExecution.executedPlan
+
+ val filter = collectFirst(df.queryExecution.executedPlan) {
Review Comment:
Please also add the executed plan in the comment here.
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