viirya commented on a change in pull request #34248:
URL: https://github.com/apache/spark/pull/34248#discussion_r727664500
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetAggregatePushDownSuite.scala
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@@ -240,6 +239,29 @@ abstract class ParquetAggregatePushDownSuite
}
}
+ test("aggregate push down - aggregate with partition filter can be pushed
down") {
+ withTempPath { dir =>
+ spark.range(10).selectExpr("id", "id % 3 as p")
+ .write.partitionBy("p").parquet(dir.getCanonicalPath)
+ withTempView("tmp") {
+
spark.read.parquet(dir.getCanonicalPath).createOrReplaceTempView("tmp");
+ Seq("false", "true").foreach { enableVectorizedReader =>
+ withSQLConf(SQLConf.PARQUET_AGGREGATE_PUSHDOWN_ENABLED.key -> "true",
+ vectorizedReaderEnabledKey -> enableVectorizedReader) {
+ val max = sql("SELECT max(id) FROM tmp WHERE p = 0")
Review comment:
Can you add other two supported aggregate functions? And how about group
by on partition column case?
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