aokolnychyi commented on a change in pull request #3400: URL: https://github.com/apache/iceberg/pull/3400#discussion_r744897622
########## File path: spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/source/TestRuntimeFiltering.java ########## @@ -0,0 +1,386 @@ +/* + * 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.source; + +import java.io.IOException; +import java.io.UncheckedIOException; +import java.util.List; +import java.util.Map; +import java.util.Set; +import org.apache.commons.lang3.StringUtils; +import org.apache.iceberg.FileScanTask; +import org.apache.iceberg.Table; +import org.apache.iceberg.expressions.Expression; +import org.apache.iceberg.expressions.Expressions; +import org.apache.iceberg.io.CloseableIterable; +import org.apache.iceberg.io.FileIO; +import org.apache.iceberg.relocated.com.google.common.collect.Sets; +import org.apache.iceberg.spark.SparkCatalogTestBase; +import org.apache.iceberg.spark.SparkWriteOptions; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.catalyst.analysis.NoSuchTableException; +import org.junit.After; +import org.junit.Assert; +import org.junit.Test; + +import static org.apache.spark.sql.functions.date_add; +import static org.apache.spark.sql.functions.expr; + +public class TestRuntimeFiltering extends SparkCatalogTestBase { + + public TestRuntimeFiltering(String catalogName, String implementation, Map<String, String> config) { + super(catalogName, implementation, config); + } + + @After + public void removeTables() { + sql("DROP TABLE IF EXISTS %s", tableName); + sql("DROP TABLE IF EXISTS dim"); + } + + @Test + public void testIdentityPartitionedTable() throws NoSuchTableException { + sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) " + + "USING iceberg " + + "PARTITIONED BY (date)", tableName); + + Dataset<Row> df = spark.range(1, 100) + .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id % 4 AS INT)"))) + .withColumn("ts", expr("TO_TIMESTAMP(date)")) + .withColumn("data", expr("CAST(date AS STRING)")) + .select("id", "data", "date", "ts"); + + df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED, "true").append(); + + sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet"); + Dataset<Row> dimDF = spark.range(1, 10) + .withColumn("date", expr("DATE '1970-01-02'")) + .select("id", "date"); + dimDF.coalesce(1).write().mode("append").insertInto("dim"); + + String query = String.format( + "SELECT f.* FROM %s f JOIN dim d ON f.date = d.date AND d.id = 1 ORDER BY id", + tableName); + + assertQueryContainsRuntimeFilter(query); + + deleteNotMatchingFiles(Expressions.equal("date", 1), 3); + + assertEquals("Should have expected rows", + sql("SELECT * FROM %s WHERE date = DATE '1970-01-02' ORDER BY id", tableName), + sql(query)); + } + + @Test + public void testBucketedTable() throws NoSuchTableException { + sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) " + + "USING iceberg " + + "PARTITIONED BY (bucket(8, id))", tableName); + + Dataset<Row> df = spark.range(1, 100) + .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id % 4 AS INT)"))) + .withColumn("ts", expr("TO_TIMESTAMP(date)")) + .withColumn("data", expr("CAST(date AS STRING)")) + .select("id", "data", "date", "ts"); + + df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED, "true").append(); + + sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet"); + Dataset<Row> dimDF = spark.range(1, 2) + .withColumn("date", expr("DATE '1970-01-02'")) + .select("id", "date"); + dimDF.coalesce(1).write().mode("append").insertInto("dim"); + + String query = String.format( + "SELECT f.* FROM %s f JOIN dim d ON f.id = d.id AND d.date = DATE '1970-01-02' ORDER BY date", + tableName); + + assertQueryContainsRuntimeFilter(query); + + deleteNotMatchingFiles(Expressions.equal("id", 1), 7); + + assertEquals("Should have expected rows", + sql("SELECT * FROM %s WHERE id = 1 ORDER BY date", tableName), + sql(query)); + } + + @Test + public void testRenamedSourceColumnTable() throws NoSuchTableException { + sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) " + + "USING iceberg " + + "PARTITIONED BY (bucket(8, id))", tableName); + + Dataset<Row> df = spark.range(1, 100) + .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id % 4 AS INT)"))) + .withColumn("ts", expr("TO_TIMESTAMP(date)")) + .withColumn("data", expr("CAST(date AS STRING)")) + .select("id", "data", "date", "ts"); + + df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED, "true").append(); + + sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet"); + Dataset<Row> dimDF = spark.range(1, 2) + .withColumn("date", expr("DATE '1970-01-02'")) + .select("id", "date"); + dimDF.coalesce(1).write().mode("append").insertInto("dim"); + + sql("ALTER TABLE %s RENAME COLUMN id TO row_id", tableName); + + String query = String.format( + "SELECT f.* FROM %s f JOIN dim d ON f.row_id = d.id AND d.date = DATE '1970-01-02' ORDER BY date", + tableName); + + assertQueryContainsRuntimeFilter(query); + + deleteNotMatchingFiles(Expressions.equal("row_id", 1), 7); + + assertEquals("Should have expected rows", + sql("SELECT * FROM %s WHERE row_id = 1 ORDER BY date", tableName), + sql(query)); + } + + @Test + public void testMultipleRuntimeFilters() throws NoSuchTableException { + sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) " + + "USING iceberg " + + "PARTITIONED BY (data, bucket(8, id))", tableName); + + Dataset<Row> df = spark.range(1, 100) + .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id % 4 AS INT)"))) + .withColumn("ts", expr("TO_TIMESTAMP(date)")) + .withColumn("data", expr("CAST(date AS STRING)")) + .select("id", "data", "date", "ts"); + + df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED, "true").append(); + + sql("CREATE TABLE dim (id BIGINT, date DATE, data STRING) USING parquet"); + Dataset<Row> dimDF = spark.range(1, 2) + .withColumn("date", expr("DATE '1970-01-02'")) + .withColumn("data", expr("'1970-01-02'")) + .select("id", "date", "data"); + dimDF.coalesce(1).write().mode("append").insertInto("dim"); + + String query = String.format( + "SELECT f.* FROM %s f JOIN dim d ON f.id = d.id AND f.data = d.data AND d.date = DATE '1970-01-02'", + tableName); + + assertQueryContainsRuntimeFilters(query, 2); + + deleteNotMatchingFiles(Expressions.equal("id", 1), 31); + + assertEquals("Should have expected rows", + sql("SELECT * FROM %s WHERE id = 1 AND data = '1970-01-02'", tableName), + sql(query)); + } + + @Test + public void testBucketedTableWithMultipleSpecs() throws NoSuchTableException { + sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) USING iceberg", tableName); + + Dataset<Row> df1 = spark.range(1, 100) + .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id % 2 AS INT)"))) + .withColumn("ts", expr("TO_TIMESTAMP(date)")) + .withColumn("data", expr("CAST(date AS STRING)")) + .select("id", "data", "date", "ts"); + + df1.coalesce(1).writeTo(tableName).append(); + + Table table = validationCatalog.loadTable(tableIdent); + table.updateSpec() + .addField(Expressions.bucket("id", 8)) + .commit(); + + sql("REFRESH TABLE %s", tableName); + + Dataset<Row> df2 = spark.range(1, 100) + .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id % 4 AS INT)"))) + .withColumn("ts", expr("TO_TIMESTAMP(date)")) + .withColumn("data", expr("CAST(date AS STRING)")) + .select("id", "data", "date", "ts"); + + df2.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED, "true").append(); + + sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet"); + Dataset<Row> dimDF = spark.range(1, 2) + .withColumn("date", expr("DATE '1970-01-02'")) + .select("id", "date"); + dimDF.coalesce(1).write().mode("append").insertInto("dim"); + + String query = String.format( + "SELECT f.* FROM %s f JOIN dim d ON f.id = d.id AND d.date = DATE '1970-01-02' ORDER BY date", + tableName); + + assertQueryContainsRuntimeFilter(query); + + deleteNotMatchingFiles(Expressions.equal("id", 1), 7); + + assertEquals("Should have expected rows", + sql("SELECT * FROM %s WHERE id = 1 ORDER BY date", tableName), + sql(query)); + } + + @Test + public void testSourceColumnWithDots() throws NoSuchTableException { + sql("CREATE TABLE %s (`i.d` BIGINT, data STRING, date DATE, ts TIMESTAMP) " + + "USING iceberg " + + "PARTITIONED BY (bucket(8, `i.d`))", tableName); + + Dataset<Row> df = spark.range(1, 100) + .withColumnRenamed("id", "i.d") + .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(`i.d` % 4 AS INT)"))) + .withColumn("ts", expr("TO_TIMESTAMP(date)")) + .withColumn("data", expr("CAST(date AS STRING)")) + .select("`i.d`", "data", "date", "ts"); + + df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED, "true").append(); + + sql("SELECT * FROM %s WHERE `i.d` = 1", tableName); + + sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet"); + Dataset<Row> dimDF = spark.range(1, 2) + .withColumn("date", expr("DATE '1970-01-02'")) + .select("id", "date"); + dimDF.coalesce(1).write().mode("append").insertInto("dim"); + + String query = String.format( + "SELECT f.* FROM %s f JOIN dim d ON f.`i.d` = d.id AND d.date = DATE '1970-01-02' ORDER BY date", + tableName); + + assertQueryContainsRuntimeFilter(query); + + deleteNotMatchingFiles(Expressions.equal("i.d", 1), 7); + + sql(query); + + assertEquals("Should have expected rows", + sql("SELECT * FROM %s WHERE `i.d` = 1 ORDER BY date", tableName), + sql(query)); + } + + @Test + public void testSourceColumnWithBackticks() throws NoSuchTableException { + sql("CREATE TABLE %s (`i``d` BIGINT, data STRING, date DATE, ts TIMESTAMP) " + + "USING iceberg " + + "PARTITIONED BY (bucket(8, `i``d`))", tableName); + + Dataset<Row> df = spark.range(1, 100) + .withColumnRenamed("id", "i`d") + .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(`i``d` % 4 AS INT)"))) + .withColumn("ts", expr("TO_TIMESTAMP(date)")) + .withColumn("data", expr("CAST(date AS STRING)")) + .select("`i``d`", "data", "date", "ts"); + + df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED, "true").append(); + + sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet"); + Dataset<Row> dimDF = spark.range(1, 2) + .withColumn("date", expr("DATE '1970-01-02'")) + .select("id", "date"); + dimDF.coalesce(1).write().mode("append").insertInto("dim"); + + String query = String.format( + "SELECT f.* FROM %s f JOIN dim d ON f.`i``d` = d.id AND d.date = DATE '1970-01-02' ORDER BY date", + tableName); + + assertQueryContainsRuntimeFilter(query); + + deleteNotMatchingFiles(Expressions.equal("i`d", 1), 7); + + assertEquals("Should have expected rows", + sql("SELECT * FROM %s WHERE `i``d` = 1 ORDER BY date", tableName), + sql(query)); + } + + @Test + public void testUnpartitionedTable() throws NoSuchTableException { + sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) USING iceberg", tableName); + + Dataset<Row> df = spark.range(1, 100) + .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id % 4 AS INT)"))) + .withColumn("ts", expr("TO_TIMESTAMP(date)")) + .withColumn("data", expr("CAST(date AS STRING)")) + .select("id", "data", "date", "ts"); + + df.coalesce(1).writeTo(tableName).append(); + + sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet"); + Dataset<Row> dimDF = spark.range(1, 2) + .withColumn("date", expr("DATE '1970-01-02'")) + .select("id", "date"); + dimDF.coalesce(1).write().mode("append").insertInto("dim"); + + String query = String.format( + "SELECT f.* FROM %s f JOIN dim d ON f.id = d.id AND d.date = DATE '1970-01-02' ORDER BY date", + tableName); + + assertQueryContainsNoRuntimeFilter(query); + + assertEquals("Should have expected rows", + sql("SELECT * FROM %s WHERE id = 1 ORDER BY date", tableName), + sql(query)); + } + + private void assertQueryContainsRuntimeFilter(String query) { + assertQueryContainsRuntimeFilters(query, 1); + } + + private void assertQueryContainsNoRuntimeFilter(String query) { + assertQueryContainsRuntimeFilters(query, 0); + } + + private void assertQueryContainsRuntimeFilters(String query, int expectedFilterCount) { + List<Row> output = spark.sql("EXPLAIN EXTENDED " + query).collectAsList(); + String plan = output.get(0).getString(0); + int actualFilterCount = StringUtils.countMatches(plan, "dynamicpruningexpression"); + Assert.assertEquals("Invalid number of runtime filters", expectedFilterCount, actualFilterCount); Review comment: Fixed. -- This is an automated message from the Apache Git Service. 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