felipepessoto commented on code in PR #12967: URL: https://github.com/apache/gluten/pull/12967#discussion_r3960735492
########## backends-velox/src-delta40/test/scala/org/apache/spark/sql/delta/GlutenDeltaStatsSuite.scala: ########## @@ -0,0 +1,68 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.spark.sql.delta + +import org.apache.spark.sql.Row +import org.apache.spark.sql.delta.sources.DeltaSQLConf +import org.apache.spark.sql.delta.test.DeltaSQLCommandTest + +class GlutenDeltaStatsSuite extends DeltaSQLCommandTest { + + import testImplicits._ + + test("collect TIMESTAMP_NTZ statistics natively") { + withSQLConf(DeltaSQLConf.DELTA_COLLECT_STATS.key -> "true") { + withTempDir { + dir => + val path = dir.getCanonicalPath + val data = Seq( + "1969-12-31 23:59:59.999999", + "2024-01-01 00:00:00.123456" + ).toDF("input") + .selectExpr( + "cast(input as timestamp_ntz) as ts", + "struct(cast(input as timestamp_ntz) as ts) as nested") + + data.coalesce(1).write.format("delta").save(path) + + val actual = spark.read.format("delta").load(path) + assert(actual.collect().toSet == data.collect().toSet) + + val addFiles = DeltaLog.forTable(spark, path).update().allFiles.collect() + assert(addFiles.length == 1) + val stats = addFiles.head.stats + assert(stats != null) + val statsValues = Seq(stats) + .toDF("stats") + .selectExpr( + "get_json_object(stats, '$.minValues.ts')", + "get_json_object(stats, '$.minValues.nested.ts')", + "get_json_object(stats, '$.maxValues.ts')", + "get_json_object(stats, '$.maxValues.nested.ts')" + ) + .head() + assert( + statsValues == Row( + "1969-12-31T23:59:59.999", + "1969-12-31T23:59:59.999", + "2024-01-01T00:00:00.123", + "2024-01-01T00:00:00.123"), + stats) Review Comment: I agree that an explicit offload assertion would strengthen this regression. The statistics aggregate is constructed locally inside `GlutenDeltaJobStatsTracker` in each write task and submitted directly to `NativePlanEvaluator`, so it is not visible in the outer DataFrame's executed plan ([code](https://github.com/apache/gluten/blob/6f80ab9cf4eac841c23c1ea4af4e2b3fb5f66e94/backends-velox/src-delta40/main/scala/org/apache/spark/sql/delta/stats/GlutenDeltaJobStatsTracker.scala#L151-L203)). The approach I found would require changing production tracker code in both Delta variants to add a test observation hook. The test could then assert that the hook was invoked and that the captured plan contains `HashAggregateExecTransformer`. Would you be comfortable with that, or do you know a simpler approach, such as an existing way to observe this internal plan from tests without adding a new hook? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
