Examples with HoodieSparkWriteableTestTable org.apache.hudi.testutils.HoodieSparkWriteableTestTable used on opensource projects

Example 6 with HoodieSparkWriteableTestTable

use of org.apache.hudi.testutils.HoodieSparkWriteableTestTable in project hudi by apache.

the class TestHoodieBloomIndex method testBloomFilterFalseError.

@ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
@MethodSource("configParams")
public void testBloomFilterFalseError(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) throws Exception {
    // We have two hoodie records
    String recordStr1 = "{\"_row_key\":\"1eb5b87a-1feh-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}";
    String recordStr2 = "{\"_row_key\":\"2eb5b87b-1feu-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2016-01-31T03:20:41.415Z\",\"number\":100}";
    // We write record1 to a parquet file, using a bloom filter having both records
    RawTripTestPayload rowChange1 = new RawTripTestPayload(recordStr1);
    HoodieRecord record1 = new HoodieAvroRecord(new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath()), rowChange1);
    RawTripTestPayload rowChange2 = new RawTripTestPayload(recordStr2);
    HoodieRecord record2 = new HoodieAvroRecord(new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath()), rowChange2);
    BloomFilter filter = BloomFilterFactory.createBloomFilter(10000, 0.0000001, -1, BloomFilterTypeCode.SIMPLE.name());
    filter.add(record2.getRecordKey());
    HoodieSparkWriteableTestTable testTable = HoodieSparkWriteableTestTable.of(metaClient, SCHEMA, filter);
    String fileId = testTable.addCommit("000").getFileIdWithInserts("2016/01/31", record1);
    assertTrue(filter.mightContain(record1.getRecordKey()));
    assertTrue(filter.mightContain(record2.getRecordKey()));
    // We do the tag
    JavaRDD<HoodieRecord> recordRDD = jsc.parallelize(Arrays.asList(record1, record2));
    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
    metaClient = HoodieTableMetaClient.reload(metaClient);
    HoodieTable table = HoodieSparkTable.create(config, context, metaClient);
    HoodieBloomIndex bloomIndex = new HoodieBloomIndex(config, SparkHoodieBloomIndexHelper.getInstance());
    JavaRDD<HoodieRecord> taggedRecordRDD = tagLocation(bloomIndex, recordRDD, table);
    // Check results
    for (HoodieRecord record : taggedRecordRDD.collect()) {
        if (record.getKey().equals("1eb5b87a-1feh-4edd-87b4-6ec96dc405a0")) {
            assertEquals(record.getCurrentLocation().getFileId(), fileId);
        } else if (record.getRecordKey().equals("2eb5b87b-1feu-4edd-87b4-6ec96dc405a0")) {
            assertFalse(record.isCurrentLocationKnown());
        }
    }
}

Example 7 with HoodieSparkWriteableTestTable

use of org.apache.hudi.testutils.HoodieSparkWriteableTestTable in project hudi by apache.

the class TestHoodieBloomIndex method testTagLocation.

@ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
@MethodSource("configParams")
public void testTagLocation(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) throws Exception {
    // We have some records to be tagged (two different partitions)
    String rowKey1 = UUID.randomUUID().toString();
    String rowKey2 = UUID.randomUUID().toString();
    String rowKey3 = UUID.randomUUID().toString();
    String recordStr1 = "{\"_row_key\":\"" + rowKey1 + "\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}";
    String recordStr2 = "{\"_row_key\":\"" + rowKey2 + "\",\"time\":\"2016-01-31T03:20:41.415Z\",\"number\":100}";
    String recordStr3 = "{\"_row_key\":\"" + rowKey3 + "\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":15}";
    // place same row key under a different partition.
    String recordStr4 = "{\"_row_key\":\"" + rowKey1 + "\",\"time\":\"2015-01-31T03:16:41.415Z\",\"number\":32}";
    RawTripTestPayload rowChange1 = new RawTripTestPayload(recordStr1);
    HoodieRecord record1 = new HoodieAvroRecord(new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath()), rowChange1);
    RawTripTestPayload rowChange2 = new RawTripTestPayload(recordStr2);
    HoodieRecord record2 = new HoodieAvroRecord(new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath()), rowChange2);
    RawTripTestPayload rowChange3 = new RawTripTestPayload(recordStr3);
    HoodieRecord record3 = new HoodieAvroRecord(new HoodieKey(rowChange3.getRowKey(), rowChange3.getPartitionPath()), rowChange3);
    RawTripTestPayload rowChange4 = new RawTripTestPayload(recordStr4);
    HoodieRecord record4 = new HoodieAvroRecord(new HoodieKey(rowChange4.getRowKey(), rowChange4.getPartitionPath()), rowChange4);
    JavaRDD<HoodieRecord> recordRDD = jsc.parallelize(Arrays.asList(record1, record2, record3, record4));
    // Also create the metadata and config
    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
    HoodieSparkTable hoodieTable = HoodieSparkTable.create(config, context, metaClient);
    HoodieSparkWriteableTestTable testTable = HoodieSparkWriteableTestTable.of(metaClient, SCHEMA, metadataWriter);
    // Let's tag
    HoodieBloomIndex bloomIndex = new HoodieBloomIndex(config, SparkHoodieBloomIndexHelper.getInstance());
    JavaRDD<HoodieRecord> taggedRecordRDD = tagLocation(bloomIndex, recordRDD, hoodieTable);
    // Should not find any files
    for (HoodieRecord record : taggedRecordRDD.collect()) {
        assertFalse(record.isCurrentLocationKnown());
    }
    final Map<String, List<Pair<String, Integer>>> partitionToFilesNameLengthMap = new HashMap<>();
    final String partition1 = "2016/01/31";
    final String partition2 = "2015/01/31";
    // We create three parquet file, each having one record. (two different partitions)
    final String fileId1 = UUID.randomUUID().toString();
    final String commit1 = "0000001";
    Path baseFilePath = testTable.forCommit(commit1).withInserts(partition1, fileId1, Collections.singletonList(record1));
    long baseFileLength = fs.getFileStatus(baseFilePath).getLen();
    partitionToFilesNameLengthMap.computeIfAbsent(partition1, k -> new ArrayList<>()).add(Pair.of(fileId1, Integer.valueOf((int) baseFileLength)));
    testTable.doWriteOperation(commit1, WriteOperationType.UPSERT, Collections.singletonList(partition1), partitionToFilesNameLengthMap, false, false);
    final String fileId2 = UUID.randomUUID().toString();
    final String commit2 = "0000002";
    baseFilePath = testTable.forCommit(commit2).withInserts(partition1, fileId2, Collections.singletonList(record2));
    baseFileLength = fs.getFileStatus(baseFilePath).getLen();
    partitionToFilesNameLengthMap.clear();
    partitionToFilesNameLengthMap.computeIfAbsent(partition1, k -> new ArrayList<>()).add(Pair.of(fileId2, Integer.valueOf((int) baseFileLength)));
    testTable.doWriteOperation(commit2, WriteOperationType.UPSERT, Collections.singletonList(partition1), partitionToFilesNameLengthMap, false, false);
    final String fileId3 = UUID.randomUUID().toString();
    final String commit3 = "0000003";
    baseFilePath = testTable.forCommit(commit3).withInserts(partition2, fileId3, Collections.singletonList(record4));
    baseFileLength = fs.getFileStatus(baseFilePath).getLen();
    partitionToFilesNameLengthMap.clear();
    partitionToFilesNameLengthMap.computeIfAbsent(partition2, k -> new ArrayList<>()).add(Pair.of(fileId3, Integer.valueOf((int) baseFileLength)));
    testTable.doWriteOperation(commit3, WriteOperationType.UPSERT, Collections.singletonList(partition2), partitionToFilesNameLengthMap, false, false);
    // We do the tag again
    taggedRecordRDD = tagLocation(bloomIndex, recordRDD, HoodieSparkTable.create(config, context, metaClient));
    // Check results
    for (HoodieRecord record : taggedRecordRDD.collect()) {
        if (record.getRecordKey().equals(rowKey1)) {
            if (record.getPartitionPath().equals(partition2)) {
                assertEquals(record.getCurrentLocation().getFileId(), fileId3);
            } else {
                assertEquals(record.getCurrentLocation().getFileId(), fileId1);
            }
        } else if (record.getRecordKey().equals(rowKey2)) {
            assertEquals(record.getCurrentLocation().getFileId(), fileId2);
        } else if (record.getRecordKey().equals(rowKey3)) {
            assertFalse(record.isCurrentLocationKnown());
        }
    }
}

Example 8 with HoodieSparkWriteableTestTable

use of org.apache.hudi.testutils.HoodieSparkWriteableTestTable in project hudi by apache.

the class TestHoodieMergeOnReadTable method testLogFileCountsAfterCompaction.

// TODO: Enable metadata virtual keys in this test once the feature HUDI-2593 is completed
@ParameterizedTest
@ValueSource(booleans = { false, true })
public void testLogFileCountsAfterCompaction(boolean preserveCommitMeta) throws Exception {
    boolean populateMetaFields = true;
    // insert 100 records
    HoodieWriteConfig.Builder cfgBuilder = getConfigBuilder(true, false, HoodieIndex.IndexType.BLOOM, 1024 * 1024 * 1024L, HoodieClusteringConfig.newBuilder().build(), preserveCommitMeta);
    addConfigsForPopulateMetaFields(cfgBuilder, populateMetaFields);
    HoodieWriteConfig config = cfgBuilder.build();
    try (SparkRDDWriteClient writeClient = getHoodieWriteClient(config)) {
        String newCommitTime = "100";
        writeClient.startCommitWithTime(newCommitTime);
        List<HoodieRecord> records = dataGen.generateInserts(newCommitTime, 100);
        JavaRDD<HoodieRecord> recordsRDD = jsc().parallelize(records, 1);
        writeClient.insert(recordsRDD, newCommitTime).collect();
        // Update all the 100 records
        newCommitTime = "101";
        List<HoodieRecord> updatedRecords = dataGen.generateUpdates(newCommitTime, records);
        JavaRDD<HoodieRecord> updatedRecordsRDD = jsc().parallelize(updatedRecords, 1);
        HoodieReadClient readClient = new HoodieReadClient(context(), config);
        JavaRDD<HoodieRecord> updatedTaggedRecordsRDD = readClient.tagLocation(updatedRecordsRDD);
        writeClient.startCommitWithTime(newCommitTime);
        writeClient.upsertPreppedRecords(updatedTaggedRecordsRDD, newCommitTime).collect();
        // Write them to corresponding avro logfiles
        metaClient = HoodieTableMetaClient.reload(metaClient);
        HoodieTableMetadataWriter metadataWriter = SparkHoodieBackedTableMetadataWriter.create(writeClient.getEngineContext().getHadoopConf().get(), config, writeClient.getEngineContext());
        HoodieSparkWriteableTestTable testTable = HoodieSparkWriteableTestTable.of(metaClient, HoodieTestDataGenerator.AVRO_SCHEMA_WITH_METADATA_FIELDS, metadataWriter);
        Set<String> allPartitions = updatedRecords.stream().map(record -> record.getPartitionPath()).collect(Collectors.groupingBy(partitionPath -> partitionPath)).keySet();
        assertEquals(allPartitions.size(), testTable.listAllBaseFiles().length);
        // Verify that all data file has one log file
        HoodieTable table = HoodieSparkTable.create(config, context(), metaClient, true);
        for (String partitionPath : dataGen.getPartitionPaths()) {
            List<FileSlice> groupedLogFiles = table.getSliceView().getLatestFileSlices(partitionPath).collect(Collectors.toList());
            for (FileSlice fileSlice : groupedLogFiles) {
                assertEquals(1, fileSlice.getLogFiles().count(), "There should be 1 log file written for the latest data file - " + fileSlice);
            }
        }
        // Do a compaction
        String compactionInstantTime = writeClient.scheduleCompaction(Option.empty()).get().toString();
        HoodieWriteMetadata<JavaRDD<WriteStatus>> result = writeClient.compact(compactionInstantTime);
        // Verify that recently written compacted data file has no log file
        metaClient = HoodieTableMetaClient.reload(metaClient);
        table = HoodieSparkTable.create(config, context(), metaClient);
        HoodieActiveTimeline timeline = metaClient.getActiveTimeline();
        assertTrue(HoodieTimeline.compareTimestamps(timeline.lastInstant().get().getTimestamp(), HoodieTimeline.GREATER_THAN, newCommitTime), "Compaction commit should be > than last insert");
        for (String partitionPath : dataGen.getPartitionPaths()) {
            List<FileSlice> groupedLogFiles = table.getSliceView().getLatestFileSlices(partitionPath).collect(Collectors.toList());
            for (FileSlice slice : groupedLogFiles) {
                assertEquals(0, slice.getLogFiles().count(), "After compaction there should be no log files visible on a full view");
            }
            assertTrue(result.getCommitMetadata().get().getWritePartitionPaths().stream().anyMatch(part -> part.contentEquals(partitionPath)));
        }
        // Check the entire dataset has all records still
        String[] fullPartitionPaths = new String[dataGen.getPartitionPaths().length];
        for (int i = 0; i < fullPartitionPaths.length; i++) {
            fullPartitionPaths[i] = String.format("%s/%s/*", basePath(), dataGen.getPartitionPaths()[i]);
        }
        Dataset<Row> actual = HoodieClientTestUtils.read(jsc(), basePath(), sqlContext(), fs(), fullPartitionPaths);
        List<Row> rows = actual.collectAsList();
        assertEquals(updatedRecords.size(), rows.size());
        for (Row row : rows) {
            assertEquals(row.getAs(HoodieRecord.COMMIT_TIME_METADATA_FIELD), preserveCommitMeta ? newCommitTime : compactionInstantTime);
        }
    }
}

Example 9 with HoodieSparkWriteableTestTable

use of org.apache.hudi.testutils.HoodieSparkWriteableTestTable in project hudi by apache.

the class TestHoodieBloomIndex method testCheckUUIDsAgainstOneFile.

@Test
public void testCheckUUIDsAgainstOneFile() throws Exception {
    final String partition = "2016/01/31";
    // Create some records to use
    String recordStr1 = "{\"_row_key\":\"1eb5b87a-1feh-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}";
    String recordStr2 = "{\"_row_key\":\"2eb5b87b-1feu-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2016-01-31T03:20:41.415Z\",\"number\":100}";
    String recordStr3 = "{\"_row_key\":\"3eb5b87c-1fej-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":15}";
    String recordStr4 = "{\"_row_key\":\"4eb5b87c-1fej-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":32}";
    RawTripTestPayload rowChange1 = new RawTripTestPayload(recordStr1);
    HoodieRecord record1 = new HoodieAvroRecord(new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath()), rowChange1);
    RawTripTestPayload rowChange2 = new RawTripTestPayload(recordStr2);
    HoodieRecord record2 = new HoodieAvroRecord(new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath()), rowChange2);
    RawTripTestPayload rowChange3 = new RawTripTestPayload(recordStr3);
    HoodieRecord record3 = new HoodieAvroRecord(new HoodieKey(rowChange3.getRowKey(), rowChange3.getPartitionPath()), rowChange3);
    RawTripTestPayload rowChange4 = new RawTripTestPayload(recordStr4);
    HoodieRecord record4 = new HoodieAvroRecord(new HoodieKey(rowChange4.getRowKey(), rowChange4.getPartitionPath()), rowChange4);
    // We write record1, record2 to a parquet file, but the bloom filter contains (record1,
    // record2, record3).
    BloomFilter filter = BloomFilterFactory.createBloomFilter(10000, 0.0000001, -1, BloomFilterTypeCode.SIMPLE.name());
    filter.add(record3.getRecordKey());
    HoodieSparkWriteableTestTable testTable = HoodieSparkWriteableTestTable.of(metaClient, SCHEMA, filter, metadataWriter);
    final Map<String, List<Pair<String, Integer>>> partitionToFilesNameLengthMap = new HashMap<>();
    final String commitTime = "0000001";
    final String fileId = UUID.randomUUID().toString();
    Path baseFilePath = testTable.forCommit(commitTime).withInserts(partition, fileId, Arrays.asList(record1, record2));
    long baseFileLength = fs.getFileStatus(baseFilePath).getLen();
    partitionToFilesNameLengthMap.computeIfAbsent(partition, k -> new ArrayList<>()).add(Pair.of(fileId, Integer.valueOf((int) baseFileLength)));
    testTable.doWriteOperation(commitTime, WriteOperationType.UPSERT, Collections.singletonList(partition), partitionToFilesNameLengthMap, false, false);
    final String filename = testTable.getBaseFileNameById(fileId);
    // The bloom filter contains 3 records
    assertTrue(filter.mightContain(record1.getRecordKey()));
    assertTrue(filter.mightContain(record2.getRecordKey()));
    assertTrue(filter.mightContain(record3.getRecordKey()));
    assertFalse(filter.mightContain(record4.getRecordKey()));
    // Compare with file
    List<String> uuids = Arrays.asList(record1.getRecordKey(), record2.getRecordKey(), record3.getRecordKey(), record4.getRecordKey());
    HoodieWriteConfig config = HoodieWriteConfig.newBuilder().withPath(basePath).build();
    HoodieSparkTable table = HoodieSparkTable.create(config, context, metaClient);
    List<String> results = HoodieIndexUtils.filterKeysFromFile(new Path(Paths.get(basePath, partition, filename).toString()), uuids, hadoopConf);
    assertEquals(results.size(), 2);
    assertTrue(results.get(0).equals("1eb5b87a-1feh-4edd-87b4-6ec96dc405a0") || results.get(1).equals("1eb5b87a-1feh-4edd-87b4-6ec96dc405a0"));
    assertTrue(results.get(0).equals("2eb5b87b-1feu-4edd-87b4-6ec96dc405a0") || results.get(1).equals("2eb5b87b-1feu-4edd-87b4-6ec96dc405a0"));
// TODO(vc): Need more coverage on actual filenames
// assertTrue(results.get(0)._2().equals(filename));
// assertTrue(results.get(1)._2().equals(filename));
}

Example 10 with HoodieSparkWriteableTestTable

use of org.apache.hudi.testutils.HoodieSparkWriteableTestTable in project hudi by apache.

the class TestHoodieBloomIndex method testCheckExists.

@ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
@MethodSource("configParams")
public void testCheckExists(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) throws Exception {
    // We have some records to be tagged (two different partitions)
    String recordStr1 = "{\"_row_key\":\"1eb5b87a-1feh-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}";
    String recordStr2 = "{\"_row_key\":\"2eb5b87b-1feu-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2016-01-31T03:20:41.415Z\",\"number\":100}";
    String recordStr3 = "{\"_row_key\":\"3eb5b87c-1fej-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":15}";
    // record key same as recordStr2
    String recordStr4 = "{\"_row_key\":\"2eb5b87b-1feu-4edd-87b4-6ec96dc405a0\"," + "\"time\":\"2015-01-31T03:16:41.415Z\",\"number\":32}";
    RawTripTestPayload rowChange1 = new RawTripTestPayload(recordStr1);
    HoodieKey key1 = new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath());
    HoodieRecord record1 = new HoodieAvroRecord(key1, rowChange1);
    RawTripTestPayload rowChange2 = new RawTripTestPayload(recordStr2);
    HoodieKey key2 = new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath());
    HoodieRecord record2 = new HoodieAvroRecord(key2, rowChange2);
    RawTripTestPayload rowChange3 = new RawTripTestPayload(recordStr3);
    HoodieKey key3 = new HoodieKey(rowChange3.getRowKey(), rowChange3.getPartitionPath());
    RawTripTestPayload rowChange4 = new RawTripTestPayload(recordStr4);
    HoodieKey key4 = new HoodieKey(rowChange4.getRowKey(), rowChange4.getPartitionPath());
    HoodieRecord record4 = new HoodieAvroRecord(key4, rowChange4);
    JavaRDD<HoodieKey> keysRDD = jsc.parallelize(Arrays.asList(key1, key2, key3, key4));
    // Also create the metadata and config
    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
    HoodieTable hoodieTable = HoodieSparkTable.create(config, context, metaClient);
    HoodieSparkWriteableTestTable testTable = HoodieSparkWriteableTestTable.of(metaClient, SCHEMA, metadataWriter);
    // Let's tag
    HoodieBloomIndex bloomIndex = new HoodieBloomIndex(config, SparkHoodieBloomIndexHelper.getInstance());
    JavaRDD<HoodieRecord> taggedRecords = tagLocation(bloomIndex, keysRDD.map(k -> new HoodieAvroRecord(k, null)), hoodieTable);
    JavaPairRDD<HoodieKey, Option<Pair<String, String>>> recordLocationsRDD = taggedRecords.mapToPair(hr -> new Tuple2<>(hr.getKey(), hr.isCurrentLocationKnown() ? Option.of(Pair.of(hr.getPartitionPath(), hr.getCurrentLocation().getFileId())) : Option.empty()));
    // Should not find any files
    for (Tuple2<HoodieKey, Option<Pair<String, String>>> record : recordLocationsRDD.collect()) {
        assertTrue(!record._2.isPresent());
    }
    final String partition1 = "2016/01/31";
    final String partition2 = "2015/01/31";
    final String fileId1 = UUID.randomUUID().toString();
    final String fileId2 = UUID.randomUUID().toString();
    final String fileId3 = UUID.randomUUID().toString();
    final Map<String, List<Pair<String, Integer>>> partitionToFilesNameLengthMap = new HashMap<>();
    // We create three parquet file, each having one record. (two different partitions)
    final String commit1 = "0000001";
    Path baseFilePath = testTable.forCommit(commit1).withInserts(partition1, fileId1, Collections.singletonList(record1));
    long baseFileLength = fs.getFileStatus(baseFilePath).getLen();
    partitionToFilesNameLengthMap.computeIfAbsent(partition1, k -> new ArrayList<>()).add(Pair.of(fileId1, Integer.valueOf((int) baseFileLength)));
    testTable.doWriteOperation(commit1, WriteOperationType.UPSERT, Collections.singletonList(partition1), partitionToFilesNameLengthMap, false, false);
    final String commit2 = "0000002";
    partitionToFilesNameLengthMap.clear();
    baseFilePath = testTable.forCommit(commit2).withInserts(partition1, fileId2, Collections.singletonList(record2));
    baseFileLength = fs.getFileStatus(baseFilePath).getLen();
    partitionToFilesNameLengthMap.computeIfAbsent(partition1, k -> new ArrayList<>()).add(Pair.of(fileId2, Integer.valueOf((int) baseFileLength)));
    testTable.doWriteOperation(commit2, WriteOperationType.UPSERT, Collections.singletonList(partition1), partitionToFilesNameLengthMap, false, false);
    final String commit3 = "0000003";
    partitionToFilesNameLengthMap.clear();
    baseFilePath = testTable.forCommit(commit3).withInserts(partition2, fileId3, Collections.singletonList(record4));
    baseFileLength = fs.getFileStatus(baseFilePath).getLen();
    partitionToFilesNameLengthMap.computeIfAbsent(partition2, k -> new ArrayList<>()).add(Pair.of(fileId3, Integer.valueOf((int) baseFileLength)));
    testTable.doWriteOperation(commit3, WriteOperationType.UPSERT, Collections.singletonList(partition2), partitionToFilesNameLengthMap, false, false);
    // We do the tag again
    metaClient = HoodieTableMetaClient.reload(metaClient);
    hoodieTable = HoodieSparkTable.create(config, context, metaClient);
    taggedRecords = tagLocation(bloomIndex, keysRDD.map(k -> new HoodieAvroRecord(k, null)), hoodieTable);
    recordLocationsRDD = taggedRecords.mapToPair(hr -> new Tuple2<>(hr.getKey(), hr.isCurrentLocationKnown() ? Option.of(Pair.of(hr.getPartitionPath(), hr.getCurrentLocation().getFileId())) : Option.empty()));
    // Check results
    for (Tuple2<HoodieKey, Option<Pair<String, String>>> record : recordLocationsRDD.collect()) {
        if (record._1.getRecordKey().equals("1eb5b87a-1feh-4edd-87b4-6ec96dc405a0")) {
            assertTrue(record._2.isPresent());
            assertEquals(fileId1, record._2.get().getRight());
        } else if (record._1.getRecordKey().equals("2eb5b87b-1feu-4edd-87b4-6ec96dc405a0")) {
            assertTrue(record._2.isPresent());
            if (record._1.getPartitionPath().equals(partition2)) {
                assertEquals(fileId3, record._2.get().getRight());
            } else {
                assertEquals(fileId2, record._2.get().getRight());
            }
        } else if (record._1.getRecordKey().equals("3eb5b87c-1fej-4edd-87b4-6ec96dc405a0")) {
            assertFalse(record._2.isPresent());
        }
    }
}