cloud-fan commented on code in PR #39408: URL: https://github.com/apache/spark/pull/39408#discussion_r1069076438
########## sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileMetadataStructSuite.scala: ########## @@ -677,4 +677,90 @@ class FileMetadataStructSuite extends QueryTest with SharedSparkSession { assert(analyzedStruct.fields.forall(!_.nullable), analyzedStruct.fields.mkString(", ")) assert(executedStruct.fields.forall(!_.nullable), executedStruct.fields.mkString(", ")) } + + test("SPARK-41896: Filter on row_index and a stored column at the same time") { + withTempPath { dir => + val storedIdName = "stored_id" + val storedIdUpperLimitExclusive = 520 + val rowIndexLowerLimitInclusive = 10 + + spark.range(start = 500, end = 600) + .toDF(storedIdName) + .write + .format("parquet") + .save(dir.getAbsolutePath) + + // Select stored_id 510 to 519 via a stored_id and row_index filter. + val collectedRows = spark.read.load(dir.getAbsolutePath) + .select(storedIdName, METADATA_ROW_INDEX) + .where(col(storedIdName).lt(lit(storedIdUpperLimitExclusive))) + .where(col(METADATA_ROW_INDEX).geq(lit(rowIndexLowerLimitInclusive))) + .collect() + + assert(collectedRows.length === 10) + assert(collectedRows.forall(_.getLong(0) < storedIdUpperLimitExclusive)) + assert(collectedRows.forall(_.getLong(1) >= rowIndexLowerLimitInclusive)) + } + } + + test("SPARK-41896: Filter on constant and generated metadata attributes at the same time") { + withTempPath { dir => + val idColumnName = "id" + val partitionColumnName = "partition" + val numFiles = 4 + val totalNumRows = 40 + + spark.range(end = totalNumRows) + .toDF(idColumnName) + .withColumn(partitionColumnName, col(idColumnName).mod(lit(numFiles))) + .write + .partitionBy(partitionColumnName) + .format("parquet") + .save(dir.getAbsolutePath) + + // Get one file path. + val randomTableFilePath = spark.read.load(dir.getAbsolutePath) + .select(METADATA_FILE_PATH).collect().head.getString(0) + + val halfTheNumberOfRowsPerFile = totalNumRows / (numFiles * 2) + val collectedRows = spark.read.load(dir.getAbsolutePath) + .where(col(METADATA_FILE_PATH).equalTo(lit(randomTableFilePath))) + .where(col(METADATA_ROW_INDEX).leq(lit(halfTheNumberOfRowsPerFile))) Review Comment: is there a way to test that the metadata predicate is indeed pushed and evaluated? -- 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: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org