This is an automated email from the ASF dual-hosted git repository.
pwason pushed a commit to branch release-0.14.0
in repository https://gitbox.apache.org/repos/asf/hudi.git
commit 256957a689e088dcb1b54ced68b742e3aa4221ae
Author: Jon Vexler <jbvex...@gmail.com>
AuthorDate: Sat Aug 26 14:01:02 2023 -0400
[HUDI-6681] Ensure MOR Column Stats Index skips reading filegroups
correctly (#9422)
- Create tests for MOR col stats index to ensure that filegroups are read
as expected
Co-authored-by: Jonathan Vexler <=>
---
.../TestDataSkippingWithMORColstats.java | 483 +++++++++++++++++++++
1 file changed, 483 insertions(+)
diff --git
a/hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/functional/TestDataSkippingWithMORColstats.java
b/hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/functional/TestDataSkippingWithMORColstats.java
new file mode 100644
index 00000000000..64d6c31c2fa
--- /dev/null
+++
b/hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/functional/TestDataSkippingWithMORColstats.java
@@ -0,0 +1,483 @@
+/*
+ * 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.hudi.functional;
+
+import org.apache.hudi.DataSourceReadOptions;
+import org.apache.hudi.DataSourceWriteOptions;
+import org.apache.hudi.client.SparkRDDWriteClient;
+import org.apache.hudi.common.config.HoodieMetadataConfig;
+import org.apache.hudi.common.fs.FSUtils;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.table.timeline.HoodieActiveTimeline;
+import org.apache.hudi.common.testutils.HoodieTestDataGenerator;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.config.HoodieCompactionConfig;
+import org.apache.hudi.config.HoodieWriteConfig;
+import org.apache.hudi.testutils.HoodieSparkClientTestBase;
+
+import org.apache.spark.SparkException;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.junit.jupiter.api.AfterEach;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.io.TempDir;
+
+import java.io.File;
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.Set;
+import java.util.stream.Collectors;
+import java.util.stream.Stream;
+
+import static
org.apache.hudi.common.testutils.RawTripTestPayload.recordToString;
+import static
org.apache.hudi.config.HoodieCompactionConfig.INLINE_COMPACT_NUM_DELTA_COMMITS;
+import static org.apache.spark.sql.SaveMode.Append;
+import static org.apache.spark.sql.SaveMode.Overwrite;
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertThrows;
+
+/**
+ * Test mor with colstats enabled in scenarios to ensure that files
+ * are being appropriately read or not read.
+ * The strategy employed is to corrupt targeted base files. If we want
+ * to prove the file is read, we assert that an exception will be thrown.
+ * If we want to prove the file is not read, we expect the read to
+ * successfully execute.
+ */
+public class TestDataSkippingWithMORColstats extends HoodieSparkClientTestBase
{
+
+ private static String matchCond = "trip_type = 'UBERX'";
+ private static String nonMatchCond = "trip_type = 'BLACK'";
+ private static String[] dropColumns = {"_hoodie_commit_time",
"_hoodie_commit_seqno",
+ "_hoodie_record_key", "_hoodie_partition_path", "_hoodie_file_name"};
+
+ private Boolean shouldOverwrite;
+ Map<String, String> options;
+ @TempDir
+ public java.nio.file.Path basePath;
+
+ @BeforeEach
+ public void setUp() throws Exception {
+ initSparkContexts();
+ dataGen = new HoodieTestDataGenerator();
+ shouldOverwrite = true;
+ options = getOptions();
+ Properties props = new Properties();
+ props.putAll(options);
+ try {
+ metaClient = HoodieTableMetaClient.initTableAndGetMetaClient(hadoopConf,
basePath.toString(), props);
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
+
+ @AfterEach
+ public void tearDown() throws IOException {
+ cleanupSparkContexts();
+ cleanupTestDataGenerator();
+ metaClient = null;
+ }
+
+ /**
+ * Create two files, one should be excluded by colstats
+ */
+ @Test
+ public void testBaseFileOnly() {
+ Dataset<Row> inserts = makeInsertDf("000", 100);
+ Dataset<Row> batch1 = inserts.where(matchCond);
+ Dataset<Row> batch2 = inserts.where(nonMatchCond);
+ doWrite(batch1);
+ doWrite(batch2);
+ List<Path> filesToCorrupt = getFilesToCorrupt();
+ assertEquals(1, filesToCorrupt.size());
+ filesToCorrupt.forEach(TestDataSkippingWithMORColstats::corruptFile);
+ assertEquals(0, readMatchingRecords().except(batch1).count());
+ //Read without data skipping to show that it will fail
+ //Reading with data skipping succeeded so that means that data skipping is
working and the corrupted
+ //file was not read
+ assertThrows(SparkException.class, () ->
readMatchingRecords(false).count());
+ }
+
+ /**
+ * Create two base files, One base file doesn't match the condition
+ * Then add a log file so that both file groups match
+ * both file groups must be read
+ */
+ @Test
+ public void testBaseFileAndLogFileUpdateMatches() {
+ testBaseFileAndLogFileUpdateMatchesHelper(false, false,false, false);
+ }
+
+ /**
+ * Create two base files, One base file doesn't match the condition
+ * Then add a log file so that both file groups match
+ * Then do a compaction
+ * Now you have two base files that match
+ * both file groups must be read
+ */
+ @Test
+ public void testBaseFileAndLogFileUpdateMatchesDoCompaction() {
+ testBaseFileAndLogFileUpdateMatchesHelper(false, true,false, false);
+ }
+
+ /**
+ * Create two base files, One base file doesn't match the condition
+ * Then add a log file for each filegroup that contains exactly the same
records as the base file
+ * Then schedule an async compaction
+ * Then add a log file so that both file groups match the condition
+ * The new log file is a member of a newer file slice
+ * both file groups must be read
+ */
+ @Test
+ public void testBaseFileAndLogFileUpdateMatchesScheduleCompaction() {
+ testBaseFileAndLogFileUpdateMatchesHelper(true, false,false, false);
+ }
+
+ /**
+ * Create two base files, One base file doesn't match the condition
+ * Then add a log file so that both file groups match the condition
+ * Then add a delete for that record so that the file group no longer
matches the condition
+ * both file groups must still be read
+ */
+ @Test
+ public void testBaseFileAndLogFileUpdateMatchesDeleteBlock() {
+ testBaseFileAndLogFileUpdateMatchesHelper(false, false,true, false);
+ }
+
+ /**
+ * Create two base files, One base file doesn't match the condition
+ * Then add a log file so that both file groups match the condition
+ * Then add a delete for that record so that the file group no longer
matches the condition
+ * Then compact
+ * Only the first file group needs to be read
+ */
+ @Test
+ public void testBaseFileAndLogFileUpdateMatchesDeleteBlockCompact() {
+ testBaseFileAndLogFileUpdateMatchesHelper(false, true,true, false);
+ }
+
+ /**
+ * Create two base files, One base file doesn't match the condition
+ * Then add a log file so that both file groups match the condition
+ * Then delete the deltacommit and write the original value for the
+ * record so that a rollback is triggered and the file group no
+ * longer matches the condition
+ * both filegroups should be read
+ */
+ @Test
+ public void testBaseFileAndLogFileUpdateMatchesAndRollBack() {
+ testBaseFileAndLogFileUpdateMatchesHelper(false, false,false, true);
+ }
+
+ /**
+ * Test where one filegroup doesn't match the condition, then update so both
filegroups match
+ */
+ private void testBaseFileAndLogFileUpdateMatchesHelper(Boolean
shouldScheduleCompaction,
+ Boolean
shouldInlineCompact,
+ Boolean shouldDelete,
+ Boolean
shouldRollback) {
+ Dataset<Row> inserts = makeInsertDf("000", 100);
+ Dataset<Row> batch1 = inserts.where(matchCond);
+ Dataset<Row> batch2 = inserts.where(nonMatchCond);
+ doWrite(batch1);
+ doWrite(batch2);
+ if (shouldScheduleCompaction) {
+ doWrite(inserts);
+ scheduleCompaction();
+ }
+ List<Path> filesToCorrupt = getFilesToCorrupt();
+ assertEquals(1, filesToCorrupt.size());
+ Dataset<Row> recordToUpdate = batch2.limit(1);
+ Dataset<Row> updatedRecord = makeRecordMatch(recordToUpdate);
+ doWrite(updatedRecord);
+ if (shouldRollback) {
+ deleteLatestDeltacommit();
+ enableInlineCompaction(shouldInlineCompact);
+ doWrite(recordToUpdate);
+ assertEquals(0, readMatchingRecords().except(batch1).count());
+ } else if (shouldDelete) {
+ enableInlineCompaction(shouldInlineCompact);
+ doDelete(updatedRecord);
+ assertEquals(0, readMatchingRecords().except(batch1).count());
+ } else {
+ assertEquals(0,
readMatchingRecords().except(batch1.union(updatedRecord)).count());
+ }
+
+ if (shouldInlineCompact) {
+ filesToCorrupt = getFilesToCorrupt();
+ filesToCorrupt.forEach(TestDataSkippingWithMORColstats::corruptFile);
+ if (shouldDelete || shouldRollback) {
+ assertEquals(1, filesToCorrupt.size());
+ assertEquals(0, readMatchingRecords().except(batch1).count());
+ } else {
+ enableInlineCompaction(true);
+ doWrite(updatedRecord);
+ assertEquals(0, filesToCorrupt.size());
+ }
+ } else {
+ //Corrupt to prove that colstats does not exclude filegroup
+ filesToCorrupt.forEach(TestDataSkippingWithMORColstats::corruptFile);
+ assertEquals(1, filesToCorrupt.size());
+ assertThrows(SparkException.class, () -> readMatchingRecords().count());
+ }
+ }
+
+ /**
+ * Create two base files, One base file all records match the condition.
+ * The other base file has one record that matches the condition.
+ * Then add a log file that makes that one matching record not match anymore.
+ * both file groups must be read even though no records from the second file
slice
+ * will pass the condition after mor merging
+ */
+ @Test
+ public void testBaseFileAndLogFileUpdateUnmatches() {
+ testBaseFileAndLogFileUpdateUnmatchesHelper(false);
+ }
+
+ /**
+ * Create two base files, One base file all records match the condition.
+ * The other base file has one record that matches the condition.
+ * Then add a log file for each filegroup that contains exactly the same
records as the base file
+ * Then schedule a compaction
+ * Then add a log file that makes that one matching record not match anymore.
+ * The new log file is a member of a newer file slice
+ * both file groups must be read even though no records from the second file
slice
+ * will pass the condition after mor merging
+ */
+ @Test
+ public void testBaseFileAndLogFileUpdateUnmatchesScheduleCompaction() {
+ testBaseFileAndLogFileUpdateUnmatchesHelper(true);
+ }
+
+ /**
+ * Test where one filegroup all records match the condition and the other
has only a single record that matches
+ * an update is added that makes the second filegroup no longer match
+ * Dataskipping should not exclude the second filegroup
+ */
+ private void testBaseFileAndLogFileUpdateUnmatchesHelper(Boolean
shouldScheduleCompaction) {
+ Dataset<Row> inserts = makeInsertDf("000", 100);
+ Dataset<Row> batch1 = inserts.where(matchCond);
+ doWrite(batch1);
+ //no matches in batch2
+ Dataset<Row> batch2 = inserts.where(nonMatchCond);
+ //make 1 record match
+ Dataset<Row> recordToMod = batch2.limit(1);
+ Dataset<Row> initialRecordToMod = makeRecordMatch(recordToMod);
+ Dataset<Row> modBatch2 = removeRecord(batch2,
recordToMod).union(initialRecordToMod);
+ doWrite(modBatch2);
+ if (shouldScheduleCompaction) {
+ doWrite(batch1.union(modBatch2));
+ scheduleCompaction();
+ }
+
+ //update batch2 so no matching records in the filegroup
+ doWrite(recordToMod);
+ assertEquals(0, readMatchingRecords().except(batch1).count());
+
+ //Corrupt to prove that colstats does not exclude filegroup
+ List<Path> filesToCorrupt = getFilesToCorrupt();
+ assertEquals(1, filesToCorrupt.size());
+ filesToCorrupt.forEach(TestDataSkippingWithMORColstats::corruptFile);
+ assertThrows(SparkException.class, () -> readMatchingRecords().count());
+ }
+
+ private Map<String, String> getOptions() {
+ Map<String, String> options = new HashMap<>();
+ options.put(HoodieMetadataConfig.ENABLE.key(), "true");
+ options.put(HoodieMetadataConfig.ENABLE_METADATA_INDEX_COLUMN_STATS.key(),
"true");
+ options.put(HoodieMetadataConfig.COLUMN_STATS_INDEX_FOR_COLUMNS.key(),
"trip_type");
+ options.put(DataSourceReadOptions.ENABLE_DATA_SKIPPING().key(), "true");
+ options.put(DataSourceWriteOptions.TABLE_TYPE().key(),
DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL());
+ options.put(HoodieWriteConfig.TBL_NAME.key(), "testTable");
+ options.put(DataSourceWriteOptions.PRECOMBINE_FIELD().key(), "timestamp");
+ options.put(DataSourceWriteOptions.RECORDKEY_FIELD().key(), "_row_key");
+ options.put("hoodie.datasource.write.keygenerator.class",
"org.apache.hudi.keygen.NonpartitionedKeyGenerator");
+ options.put(HoodieCompactionConfig.PARQUET_SMALL_FILE_LIMIT.key(), "0");
+ options.put(HoodieWriteConfig.ROLLBACK_USING_MARKERS_ENABLE.key(),
"false");
+ options.put(HoodieCompactionConfig.INLINE_COMPACT.key(), "false");
+ return options;
+ }
+
+ private void scheduleCompaction() {
+ HoodieWriteConfig cfg =
HoodieWriteConfig.newBuilder().withPath(basePath.toString())
+ .withRollbackUsingMarkers(false)
+ .withAutoCommit(false)
+ .withMetadataConfig(HoodieMetadataConfig.newBuilder()
+ .enable(true)
+ .withMetadataIndexColumnStats(true)
+ .withColumnStatsIndexForColumns("trip_type").build())
+
.withCompactionConfig(HoodieCompactionConfig.newBuilder().compactionSmallFileSize(0)
+
.withInlineCompaction(false).withMaxNumDeltaCommitsBeforeCompaction(1).build())
+ .forTable("testTable")
+ .withKeyGenerator("org.apache.hudi.keygen.NonpartitionedKeyGenerator")
+ .build();
+ try (SparkRDDWriteClient client = getHoodieWriteClient(cfg)) {
+
client.scheduleCompactionAtInstant(HoodieActiveTimeline.createNewInstantTime(),
Option.empty());
+ }
+ }
+
+ /**
+ * remove recordToRemove from batch
+ * recordToRemove is expected to only have 1 row
+ */
+ private Dataset<Row> removeRecord(Dataset<Row> batch, Dataset<Row>
recordToRemove) {
+ return batch.where("_row_key != '" + recordToRemove.first().getString(1) +
"'");
+ }
+
+ /**
+ * Returns a list of the base parquet files for the latest fileslice in it's
filegroup where
+ * no records match the condition
+ */
+ private List<Path> getFilesToCorrupt() {
+ Set<String> fileNames = new HashSet<>();
+ sparkSession.read().format("hudi").load(basePath.toString())
+ .where(matchCond)
+ .select("_hoodie_file_name").distinct()
+ .collectAsList().forEach(row -> {
+ String fileName = row.getString(0);
+ if (fileName.contains(".parquet")) {
+ fileNames.add(FSUtils.getFileId(fileName));
+ } else {
+ fileNames.add(fileName);
+ }
+ });
+
+ try (Stream<Path> stream = Files.list(basePath)) {
+ Map<String,Path> latestBaseFiles = new HashMap<>();
+ List<Path> files = stream
+ .filter(file -> !Files.isDirectory(file))
+ .filter(file -> file.toString().contains(".parquet"))
+ .filter(file -> !file.toString().contains(".crc"))
+ .filter(file ->
!fileNames.contains(FSUtils.getFileId(file.getFileName().toString())))
+ .collect(Collectors.toList());
+ files.forEach(f -> {
+ String fileID = FSUtils.getFileId(f.getFileName().toString());
+ if (!latestBaseFiles.containsKey(fileID) ||
FSUtils.getCommitTime(f.getFileName().toString())
+
.compareTo(FSUtils.getCommitTime(latestBaseFiles.get(fileID).getFileName().toString()))
> 0) {
+ latestBaseFiles.put(fileID, f);
+ }
+ });
+ return new ArrayList<>(latestBaseFiles.values());
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
+
+ private void doWrite(Dataset<Row> df) {
+ if (shouldOverwrite) {
+ shouldOverwrite = false;
+
df.write().format("hudi").options(options).mode(Overwrite).save(basePath.toString());
+ } else {
+
df.write().format("hudi").options(options).mode(Append).save(basePath.toString());
+ }
+ }
+
+ private void doDelete(Dataset<Row> df) {
+
df.write().format("hudi").options(options).option(DataSourceWriteOptions.OPERATION().key(),
+
DataSourceWriteOptions.DELETE_OPERATION_OPT_VAL()).mode(Append).save(basePath.toString());
+ }
+
+ /**
+ * update rowToMod to make it match the condition.
+ * rowToMod is expected to only have 1 row
+ */
+ private Dataset<Row> makeRecordMatch(Dataset<Row> rowToMod) {
+ return updateTripType(rowToMod, "UBERX");
+ }
+
+ private Dataset<Row> updateTripType(Dataset<Row> rowToMod, String value) {
+ rowToMod.createOrReplaceTempView("rowToMod");
+ return sparkSession.sqlContext().createDataFrame(sparkSession.sql("select
_hoodie_is_deleted, _row_key, "
+ + "begin_lat, begin_lon, current_date, current_ts, distance_in_meters,
driver, end_lat, end_lon, fare, height, "
+ + "nation, partition, partition_path, rider, seconds_since_epoch,
timestamp, tip_history, '" + value
+ + "' as trip_type, weight from rowToMod").rdd(), rowToMod.schema());
+ }
+
+ /**
+ * Read records from Hudi that match the condition
+ * and drop the meta cols
+ */
+ private Dataset<Row> readMatchingRecords() {
+ return readMatchingRecords(true);
+ }
+
+ public Dataset<Row> readMatchingRecords(Boolean useDataSkipping) {
+ if (useDataSkipping) {
+ return sparkSession.read().format("hudi").options(options)
+ .load(basePath.toString()).where(matchCond).drop(dropColumns);
+ } else {
+ return sparkSession.read().format("hudi")
+ .option(DataSourceReadOptions.ENABLE_DATA_SKIPPING().key(), "false")
+ .load(basePath.toString()).where(matchCond).drop(dropColumns);
+ }
+ }
+
+ /**
+ * Corrupt a parquet file by deleting it and replacing
+ * it with an empty file
+ */
+ protected static void corruptFile(Path path) {
+ File fileToCorrupt = path.toFile();
+ fileToCorrupt.delete();
+ try {
+ fileToCorrupt.createNewFile();
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
+
+ protected Dataset<Row> makeInsertDf(String instantTime, Integer n) {
+ List<String> records = dataGen.generateInserts(instantTime, n).stream()
+ .map(r -> recordToString(r).get()).collect(Collectors.toList());
+ JavaRDD<String> rdd = jsc.parallelize(records);
+ //cant do df.except with city_to_state and our testing is for the
+ //col stats index so it is ok to just drop this here
+ return sparkSession.read().json(rdd).drop("city_to_state");
+ }
+
+ public void deleteLatestDeltacommit() {
+ String filename =
metaClient.getActiveTimeline().lastInstant().get().getFileName();
+ File deltacommit = new File(metaClient.getBasePathV2() + "/.hoodie/" +
filename);
+ deltacommit.delete();
+ }
+
+ /**
+ * Need to enable inline compaction before final write. We need to do this
+ * before the final write instead of setting a num delta commits number
+ * because in the case of rollback, we do 3 updates and then rollback
+ * and do an update, but we only want to compact the second time
+ * we have 3
+ */
+ public void enableInlineCompaction(Boolean shouldEnable) {
+ if (shouldEnable) {
+ this.options.put(HoodieCompactionConfig.INLINE_COMPACT.key(), "true");
+ this.options.put(INLINE_COMPACT_NUM_DELTA_COMMITS.key(), "1");
+ }
+ }
+}
