[GitHub] [spark] viirya commented on a change in pull request #34248: [SPARK-36647][SQL][TESTS] Push down Aggregate (Min/Max/Count) for Parquet if filter is on partition col

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viirya commented on a change in pull request #34248:
URL: https://github.com/apache/spark/pull/34248#discussion_r727664500



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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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