sadikovi commented on code in PR #36328:
URL: https://github.com/apache/spark/pull/36328#discussion_r864490106
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala:
##########
@@ -1423,65 +1442,123 @@ abstract class ParquetFilterSuite extends QueryTest
with ParquetTest with Shared
}
}
- test("filter pushdown - StringStartsWith") {
+ private def checkStringFilterPushdown(
+ stringPredicate: String => Expression,
+ sourceFilter: (String, String) => sources.Filter): Unit = {
withParquetDataFrame((1 to 4).map(i => Tuple1(i + "str" + i))) { implicit
df =>
checkFilterPredicate(
- $"_1".startsWith("").asInstanceOf[Predicate],
+ stringPredicate("").asInstanceOf[Predicate],
classOf[UserDefinedByInstance[_, _]],
Seq("1str1", "2str2", "3str3", "4str4").map(Row(_)))
- Seq("2", "2s", "2st", "2str", "2str2").foreach { prefix =>
+ Seq("2", "2str2").foreach { str =>
checkFilterPredicate(
- $"_1".startsWith(prefix).asInstanceOf[Predicate],
+ stringPredicate(str).asInstanceOf[Predicate],
classOf[UserDefinedByInstance[_, _]],
"2str2")
}
- Seq("2S", "null", "2str22").foreach { prefix =>
+ Seq("2S", "null", "2str22").foreach { str =>
checkFilterPredicate(
- $"_1".startsWith(prefix).asInstanceOf[Predicate],
+ stringPredicate(str).asInstanceOf[Predicate],
classOf[UserDefinedByInstance[_, _]],
Seq.empty[Row])
}
checkFilterPredicate(
- !$"_1".startsWith("").asInstanceOf[Predicate],
+ !stringPredicate("").asInstanceOf[Predicate],
classOf[Operators.Not],
Seq().map(Row(_)))
- Seq("2", "2s", "2st", "2str", "2str2").foreach { prefix =>
+ Seq("2", "2str2").foreach { str =>
checkFilterPredicate(
- !$"_1".startsWith(prefix).asInstanceOf[Predicate],
+ !stringPredicate(str).asInstanceOf[Predicate],
classOf[Operators.Not],
Seq("1str1", "3str3", "4str4").map(Row(_)))
}
- Seq("2S", "null", "2str22").foreach { prefix =>
+ Seq("2S", "null", "2str22").foreach { str =>
checkFilterPredicate(
- !$"_1".startsWith(prefix).asInstanceOf[Predicate],
+ !stringPredicate(str).asInstanceOf[Predicate],
classOf[Operators.Not],
Seq("1str1", "2str2", "3str3", "4str4").map(Row(_)))
}
val schema = new SparkToParquetSchemaConverter(conf).convert(df.schema)
assertResult(None) {
-
createParquetFilters(schema).createFilter(sources.StringStartsWith("_1", null))
+ createParquetFilters(schema).createFilter(sourceFilter("_1", null))
}
}
// SPARK-28371: make sure filter is null-safe.
withParquetDataFrame(Seq(Tuple1[String](null))) { implicit df =>
checkFilterPredicate(
- $"_1".startsWith("blah").asInstanceOf[Predicate],
+ stringPredicate("blah").asInstanceOf[Predicate],
classOf[UserDefinedByInstance[_, _]],
Seq.empty[Row])
}
+ }
+
+ test("filter pushdown - StringStartsWith") {
+ checkStringFilterPushdown(
+ str => $"_1".startsWith(str),
+ (attr, value) => sources.StringStartsWith(attr, value))
+ }
+
+ test("filter pushdown - StringEndsWith") {
+ checkStringFilterPushdown(
+ str => $"_1".endsWith(str),
+ (attr, value) => sources.StringEndsWith(attr, value))
+ }
+
+ test("filter pushdown - StringContains") {
+ checkStringFilterPushdown(
+ str => $"_1".contains(str),
+ (attr, value) => sources.StringContains(attr, value))
+ }
+ test("filter pushdown - StringPredicate") {
import testImplicits._
- // Test canDrop() has taken effect
- testStringStartsWith(spark.range(1024).map(_.toString).toDF(), "value like
'a%'")
- // Test inverseCanDrop() has taken effect
- testStringStartsWith(spark.range(1024).map(c => "100").toDF(), "value not
like '10%'")
+ // keep() should take effect on StartsWith/EndsWith/Contains
+ Seq(
+ "value like 'a%'", // StartsWith
+ "value like '%a'", // EndsWith
+ "value like '%a%'" // Contains
Review Comment:
I think the test is buggy and does not reflect the actual implementation of
the filter. NumRowGroupAcc does not actually count row groups, it counts the
number of records passed through the filter. For example, for the contains
filter we should still read all of the row groups.
Example of the log:
```
[canDrop]
statistics=org.apache.parquet.filter2.predicate.Statistics@52cd90cd => false
[canDrop]
statistics=org.apache.parquet.filter2.predicate.Statistics@64e59f7e => false
[keep] statistics=Binary{1 constant bytes, [49]} => false
[keep] statistics=Binary{1 constant bytes, [50]} => false
[keep] statistics=Binary{1 constant bytes, [51]} => false
[keep] statistics=Binary{1 constant bytes, [52]} => false
...
```
Can the author update the test to reflect the implementation? cc @cloud-fan
@sunchao.
You may need to enforce things like row group/dictionary filtering as well
as record level filtering.
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