GGraziadei commented on code in PR #14984: URL: https://github.com/apache/iceberg/pull/14984#discussion_r3737425484
########## spark/v4.2/spark-extensions/src/test/java/org/apache/iceberg/spark/extensions/TestSystemFunctionPushDownDQL.java: ########## @@ -0,0 +1,318 @@ +/* + * 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.iceberg.spark.extensions; + +import static org.apache.iceberg.expressions.Expressions.bucket; +import static org.apache.iceberg.expressions.Expressions.day; +import static org.apache.iceberg.expressions.Expressions.equal; +import static org.apache.iceberg.expressions.Expressions.greaterThan; +import static org.apache.iceberg.expressions.Expressions.greaterThanOrEqual; +import static org.apache.iceberg.expressions.Expressions.hour; +import static org.apache.iceberg.expressions.Expressions.lessThan; +import static org.apache.iceberg.expressions.Expressions.lessThanOrEqual; +import static org.apache.iceberg.expressions.Expressions.month; +import static org.apache.iceberg.expressions.Expressions.notEqual; +import static org.apache.iceberg.expressions.Expressions.truncate; +import static org.apache.iceberg.expressions.Expressions.year; +import static org.apache.iceberg.spark.SystemFunctionPushDownHelper.STRUCT; +import static org.apache.iceberg.spark.SystemFunctionPushDownHelper.createPartitionedTable; +import static org.apache.iceberg.spark.SystemFunctionPushDownHelper.createUnpartitionedTable; +import static org.apache.iceberg.spark.SystemFunctionPushDownHelper.timestampStrToDayOrdinal; +import static org.apache.iceberg.spark.SystemFunctionPushDownHelper.timestampStrToHourOrdinal; +import static org.apache.iceberg.spark.SystemFunctionPushDownHelper.timestampStrToMonthOrdinal; +import static org.apache.iceberg.spark.SystemFunctionPushDownHelper.timestampStrToYearOrdinal; +import static org.assertj.core.api.Assertions.assertThat; + +import java.util.List; +import org.apache.iceberg.ParameterizedTestExtension; +import org.apache.iceberg.Parameters; +import org.apache.iceberg.expressions.ExpressionUtil; +import org.apache.iceberg.spark.SparkCatalogConfig; +import org.apache.iceberg.spark.source.PlanUtils; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.catalyst.expressions.ApplyFunctionExpression; +import org.apache.spark.sql.catalyst.expressions.Expression; +import org.apache.spark.sql.catalyst.expressions.objects.StaticInvoke; +import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.TestTemplate; +import org.junit.jupiter.api.extension.ExtendWith; + +@ExtendWith(ParameterizedTestExtension.class) +public class TestSystemFunctionPushDownDQL extends ExtensionsTestBase { + + @Parameters(name = "catalogName = {0}, implementation = {1}, config = {2}") + public static Object[][] parameters() { + return new Object[][] { + { + SparkCatalogConfig.HIVE.catalogName(), + SparkCatalogConfig.HIVE.implementation(), + SparkCatalogConfig.HIVE.properties(), + }, + }; + } + + @BeforeEach + public void before() { + super.before(); + sql("USE %s", catalogName); + } + + @AfterEach + public void removeTables() { + sql("DROP TABLE IF EXISTS %s", tableName); + } + + @TestTemplate + public void testYearsFunctionOnUnpartitionedTable() { + createUnpartitionedTable(spark, tableName); + testYearsFunction(false); + } + + @TestTemplate + public void testYearsFunctionOnPartitionedTable() { + createPartitionedTable(spark, tableName, "years(ts)"); + testYearsFunction(true); + } + + private void testYearsFunction(boolean partitioned) { + int targetYears = timestampStrToYearOrdinal("2017-11-22T00:00:00.000000+00:00"); + String query = + String.format( + "SELECT * FROM %s WHERE system.years(ts) = %s ORDER BY id", tableName, targetYears); + + Dataset<Row> df = spark.sql(query); + LogicalPlan optimizedPlan = df.queryExecution().optimizedPlan(); + + checkExpressions(optimizedPlan, partitioned, "years"); + checkPushedFilters(optimizedPlan, equal(year("ts"), targetYears)); + + List<Object[]> actual = rowsToJava(df.collectAsList()); + assertThat(actual).hasSize(5); + } + + @TestTemplate + public void testMonthsFunctionOnUnpartitionedTable() { + createUnpartitionedTable(spark, tableName); + testMonthsFunction(false); + } + + @TestTemplate + public void testMonthsFunctionOnPartitionedTable() { + createPartitionedTable(spark, tableName, "months(ts)"); + testMonthsFunction(true); + } + + private void testMonthsFunction(boolean partitioned) { + int targetMonths = timestampStrToMonthOrdinal("2017-11-22T00:00:00.000000+00:00"); + String query = + String.format( + "SELECT * FROM %s WHERE system.months(ts) > %s ORDER BY id", tableName, targetMonths); + + Dataset<Row> df = spark.sql(query); + LogicalPlan optimizedPlan = df.queryExecution().optimizedPlan(); + + checkExpressions(optimizedPlan, partitioned, "months"); + checkPushedFilters(optimizedPlan, greaterThan(month("ts"), targetMonths)); + + List<Object[]> actual = rowsToJava(df.collectAsList()); + assertThat(actual).hasSize(5); + } + + @TestTemplate + public void testDaysFunctionOnUnpartitionedTable() { + createUnpartitionedTable(spark, tableName); + testDaysFunction(false); + } + + @TestTemplate + public void testDaysFunctionOnPartitionedTable() { + createPartitionedTable(spark, tableName, "days(ts)"); + testDaysFunction(true); + } + + private void testDaysFunction(boolean partitioned) { + String timestamp = "2018-11-20T00:00:00.000000+00:00"; + int targetDays = timestampStrToDayOrdinal(timestamp); + String query = + String.format( + "SELECT * FROM %s WHERE system.days(ts) < date('%s') ORDER BY id", + tableName, timestamp); + + Dataset<Row> df = spark.sql(query); + LogicalPlan optimizedPlan = df.queryExecution().optimizedPlan(); + + checkExpressions(optimizedPlan, partitioned, "days"); + checkPushedFilters(optimizedPlan, lessThan(day("ts"), targetDays)); + + List<Object[]> actual = rowsToJava(df.collectAsList()); + assertThat(actual).hasSize(5); + } + + @TestTemplate + public void testHoursFunctionOnUnpartitionedTable() { + createUnpartitionedTable(spark, tableName); + testHoursFunction(false); + } + + @TestTemplate + public void testHoursFunctionOnPartitionedTable() { + createPartitionedTable(spark, tableName, "hours(ts)"); + testHoursFunction(true); + } + + private void testHoursFunction(boolean partitioned) { + int targetHours = timestampStrToHourOrdinal("2017-11-22T06:02:09.243857+00:00"); + String query = + String.format( + "SELECT * FROM %s WHERE system.hours(ts) >= %s ORDER BY id", tableName, targetHours); + + Dataset<Row> df = spark.sql(query); + LogicalPlan optimizedPlan = df.queryExecution().optimizedPlan(); + + checkExpressions(optimizedPlan, partitioned, "hours"); + checkPushedFilters(optimizedPlan, greaterThanOrEqual(hour("ts"), targetHours)); + + List<Object[]> actual = rowsToJava(df.collectAsList()); + assertThat(actual).hasSize(8); + } + + @TestTemplate + public void testBucketLongFunctionOnUnpartitionedTable() { + createUnpartitionedTable(spark, tableName); + testBucketLongFunction(false); + } + + @TestTemplate + public void testBucketLongFunctionOnPartitionedTable() { + createPartitionedTable(spark, tableName, "bucket(5, id)"); + testBucketLongFunction(true); + } + + private void testBucketLongFunction(boolean partitioned) { + int target = 2; + String query = + String.format( + "SELECT * FROM %s WHERE system.bucket(5, id) <= %s ORDER BY id", tableName, target); + + Dataset<Row> df = spark.sql(query); + LogicalPlan optimizedPlan = df.queryExecution().optimizedPlan(); + + checkExpressions(optimizedPlan, partitioned, "bucket"); + checkPushedFilters(optimizedPlan, lessThanOrEqual(bucket("id", 5), target)); + + List<Object[]> actual = rowsToJava(df.collectAsList()); + assertThat(actual).hasSize(5); + } + + @TestTemplate + public void testBucketStringFunctionOnUnpartitionedTable() { + createUnpartitionedTable(spark, tableName); + testBucketStringFunction(false); + } + + @TestTemplate + public void testBucketStringFunctionOnPartitionedTable() { + createPartitionedTable(spark, tableName, "bucket(5, data)"); + testBucketStringFunction(true); + } + + private void testBucketStringFunction(boolean partitioned) { + int target = 2; + String query = + String.format( + "SELECT * FROM %s WHERE system.bucket(5, data) != %s ORDER BY id", tableName, target); + + Dataset<Row> df = spark.sql(query); + LogicalPlan optimizedPlan = df.queryExecution().optimizedPlan(); + + checkExpressions(optimizedPlan, partitioned, "bucket"); + checkPushedFilters(optimizedPlan, notEqual(bucket("data", 5), target)); + + List<Object[]> actual = rowsToJava(df.collectAsList()); + assertThat(actual).hasSize(8); + } + + @TestTemplate + public void testTruncateFunctionOnUnpartitionedTable() { + createUnpartitionedTable(spark, tableName); + testTruncateFunction(false); + } + + @TestTemplate + public void testTruncateFunctionOnPartitionedTable() { + createPartitionedTable(spark, tableName, "truncate(4, data)"); + testTruncateFunction(true); + } + + private void testTruncateFunction(boolean partitioned) { + String target = "data"; + String query = + String.format( + "SELECT * FROM %s WHERE system.truncate(4, data) = '%s' ORDER BY id", + tableName, target); + + Dataset<Row> df = spark.sql(query); + LogicalPlan optimizedPlan = df.queryExecution().optimizedPlan(); + + checkExpressions(optimizedPlan, partitioned, "truncate"); + checkPushedFilters(optimizedPlan, equal(truncate("data", 4), target)); + + List<Object[]> actual = rowsToJava(df.collectAsList()); + assertThat(actual).hasSize(5); + } + + private void checkExpressions( + LogicalPlan optimizedPlan, boolean partitioned, String expectedFunctionName) { + List<Expression> staticInvokes = + PlanUtils.collectSparkExpressions( + optimizedPlan, expression -> expression instanceof StaticInvoke); + assertThat(staticInvokes).isEmpty(); + + List<Expression> applyExpressions = + PlanUtils.collectSparkExpressions( + optimizedPlan, expression -> expression instanceof ApplyFunctionExpression); + + assertThat(applyExpressions).hasSize(1); + ApplyFunctionExpression expression = (ApplyFunctionExpression) applyExpressions.get(0); + assertThat(expression.name()).isEqualTo(expectedFunctionName); + + List<Expression> pushedApplyExpressions = + PlanUtils.collectPushedSparkExpressions( + optimizedPlan, candidate -> candidate instanceof ApplyFunctionExpression); + if (partitioned) { + assertThat(pushedApplyExpressions).containsExactly(expression); Review Comment: Noting this for the earlier thread that asked whether switching the partitioned cases to `hasSize(1)` weakens the assertion: I do not think it does, and it is checkable. `collectPushedSparkExpressions` reads `DataSourceV2ScanRelation.pushedFilters()` directly, while `collectSparkExpressions` walks `plan.expressions()`. In Spark 4.2 `pushedFilters` is the sixth constructor parameter of the `DataSourceV2ScanRelation` case class (confirmed against `spark-catalyst_2.13-4.2.0`: it appears as `_6` in the generated `unapply`), so it is part of `productIterator` and therefore reachable through `expressions()`. That makes the `ApplyFunctionExpression` counted above the pushed filter itself, which `containsExactly(expression)` then asserts by identity. Count of one plus identity with the pushed filter means no residual filter survives, which is what 4.1's `applyExpressions.isEmpty()` asserted on the partitioned branch. Equivalent property, expressed against the new plan representation. -- 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. 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