aokolnychyi commented on a change in pull request #2500: URL: https://github.com/apache/iceberg/pull/2500#discussion_r617900532
########## File path: spark3/src/test/java/org/apache/iceberg/spark/TestFileRewriteCoordinator.java ########## @@ -0,0 +1,234 @@ +/* + * 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; + +import java.io.IOException; +import java.util.List; +import java.util.Map; +import java.util.UUID; +import org.apache.iceberg.FileScanTask; +import org.apache.iceberg.Table; +import org.apache.iceberg.io.CloseableIterable; +import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap; +import org.apache.iceberg.relocated.com.google.common.collect.ImmutableSet; +import org.apache.iceberg.relocated.com.google.common.collect.Iterables; +import org.apache.iceberg.relocated.com.google.common.collect.Lists; +import org.apache.iceberg.spark.source.SimpleRecord; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Encoders; +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; + +public class TestFileRewriteCoordinator extends SparkCatalogTestBase { + + public TestFileRewriteCoordinator(String catalogName, String implementation, Map<String, String> config) { + super(catalogName, implementation, config); + } + + @After + public void removeTables() { + sql("DROP TABLE IF EXISTS %s", tableName); + } + + @Test + public void testBinPackRewrite() throws NoSuchTableException, IOException { + sql("CREATE TABLE %s (id INT, data STRING) USING iceberg", tableName); + + Dataset<Row> df = newDF(1000); + df.coalesce(1).writeTo(tableName).append(); + df.coalesce(1).writeTo(tableName).append(); + df.coalesce(1).writeTo(tableName).append(); + df.coalesce(1).writeTo(tableName).append(); + + Table table = validationCatalog.loadTable(tableIdent); + Assert.assertEquals("Should produce 4 snapshots", 4, Iterables.size(table.snapshots())); + + Dataset<Row> fileDF = spark.read().format("iceberg").load(tableName(tableIdent.name() + ".files")); + List<Long> fileSizes = fileDF.select("file_size_in_bytes").as(Encoders.LONG()).collectAsList(); + long avgFileSize = fileSizes.stream().mapToLong(i -> i).sum() / fileSizes.size(); + + try (CloseableIterable<FileScanTask> fileScanTasks = table.newScan().planFiles()) { + String fileSetID = UUID.randomUUID().toString(); + + FileScanTaskSetManager taskSetManager = FileScanTaskSetManager.get(); + taskSetManager.stageTasks(table, fileSetID, Lists.newArrayList(fileScanTasks)); + + // read and pack original 4 files into 2 splits + Dataset<Row> scanDF = spark.read().format("iceberg") + .option(SparkReadOptions.FILE_SCAN_TASK_SET_ID, fileSetID) + .option(SparkReadOptions.SPLIT_SIZE, Long.toString(avgFileSize * 2)) + .option(SparkReadOptions.FILE_OPEN_COST, "0") + .load(tableName); + + // write the packed data into new files where each split becomes a new file + scanDF.writeTo(tableName) + .option(SparkWriteOptions.REWRITTEN_FILE_SCAN_TASK_SET_ID, fileSetID) + .append(); + + // commit the rewrite + FileRewriteCoordinator rewriteCoordinator = FileRewriteCoordinator.get(); + rewriteCoordinator.commitRewrite(table, fileSetID); + } + + table.refresh(); + + Map<String, String> summary = table.currentSnapshot().summary(); + Assert.assertEquals("Deleted files count must match", "4", summary.get("deleted-data-files")); + Assert.assertEquals("Added files count must match", "2", summary.get("added-data-files")); + + Object rowCount = scalarSql("SELECT count(*) FROM %s", tableName); + Assert.assertEquals("Row count must match", 4000L, rowCount); + } + + @Test + public void testSortRewrite() throws NoSuchTableException, IOException { + sql("CREATE TABLE %s (id INT, data STRING) USING iceberg", tableName); + + Dataset<Row> df = newDF(1000); + df.coalesce(1).writeTo(tableName).append(); + df.coalesce(1).writeTo(tableName).append(); + df.coalesce(1).writeTo(tableName).append(); + df.coalesce(1).writeTo(tableName).append(); + + Table table = validationCatalog.loadTable(tableIdent); + Assert.assertEquals("Should produce 4 snapshots", 4, Iterables.size(table.snapshots())); + + try (CloseableIterable<FileScanTask> fileScanTasks = table.newScan().planFiles()) { + String fileSetID = UUID.randomUUID().toString(); + + FileScanTaskSetManager taskSetManager = FileScanTaskSetManager.get(); + taskSetManager.stageTasks(table, fileSetID, Lists.newArrayList(fileScanTasks)); + + // read original 4 files as 4 splits + Dataset<Row> scanDF = spark.read().format("iceberg") + .option(SparkReadOptions.FILE_SCAN_TASK_SET_ID, fileSetID) + .option(SparkReadOptions.SPLIT_SIZE, "134217728") + .option(SparkReadOptions.FILE_OPEN_COST, "134217728") + .load(tableName); + + // make sure we disable AQE and set the number of shuffle partitions as the target num files + ImmutableMap<String, String> sqlConf = ImmutableMap.of( + "spark.sql.shuffle.partitions", "2", + "spark.sql.adaptive.enabled", "false" + ); + + withSQLConf(sqlConf, () -> { + try { + // write new files with sorted records + scanDF.sort("id").writeTo(tableName) Review comment: That's how the sort-based rewrites will look like. -- This is an automated message from the Apache Git Service. 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