Examples with HoodieTable org.apache.hudi.table.HoodieTable used on opensource projects

Example 46 with HoodieTable

use of org.apache.hudi.table.HoodieTable in project hudi by apache.

the class ListBasedHoodieBloomIndexHelper method findMatchingFilesForRecordKeys.

@Override
public HoodiePairData<HoodieKey, HoodieRecordLocation> findMatchingFilesForRecordKeys(HoodieWriteConfig config, HoodieEngineContext context, HoodieTable hoodieTable, HoodiePairData<String, String> partitionRecordKeyPairs, HoodieData<Pair<String, HoodieKey>> fileComparisonPairs, Map<String, List<BloomIndexFileInfo>> partitionToFileInfo, Map<String, Long> recordsPerPartition) {
    List<Pair<String, HoodieKey>> fileComparisonPairList = HoodieList.getList(fileComparisonPairs).stream().sorted(Comparator.comparing(Pair::getLeft)).collect(toList());
    List<HoodieKeyLookupResult> keyLookupResults = new ArrayList<>();
    Iterator<List<HoodieKeyLookupResult>> iterator = new HoodieBaseBloomIndexCheckFunction(hoodieTable, config).apply(fileComparisonPairList.iterator());
    while (iterator.hasNext()) {
        keyLookupResults.addAll(iterator.next());
    }
    keyLookupResults = keyLookupResults.stream().filter(lr -> lr.getMatchingRecordKeys().size() > 0).collect(toList());
    return context.parallelize(keyLookupResults).flatMap(lookupResult -> lookupResult.getMatchingRecordKeys().stream().map(recordKey -> new ImmutablePair<>(lookupResult, recordKey)).iterator()).mapToPair(pair -> {
        HoodieKeyLookupResult lookupResult = pair.getLeft();
        String recordKey = pair.getRight();
        return new ImmutablePair<>(new HoodieKey(recordKey, lookupResult.getPartitionPath()), new HoodieRecordLocation(lookupResult.getBaseInstantTime(), lookupResult.getFileId()));
    });
}

Example 47 with HoodieTable

use of org.apache.hudi.table.HoodieTable in project hudi by apache.

the class TestFlinkHoodieBloomIndex 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);
    List<HoodieKey> keys = asList(key1, key2, key3, key4);
    // Also create the metadata and config
    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
    HoodieTable hoodieTable = HoodieFlinkTable.create(config, context, metaClient);
    HoodieFlinkWriteableTestTable testTable = HoodieFlinkWriteableTestTable.of(hoodieTable, SCHEMA);
    // Let's tag
    HoodieBloomIndex bloomIndex = new HoodieBloomIndex(config, ListBasedHoodieBloomIndexHelper.getInstance());
    List<HoodieRecord> toTagRecords = new ArrayList<>();
    toTagRecords.add(new HoodieAvroRecord(record4.getKey(), null));
    List<HoodieRecord> taggedRecords = tagLocation(bloomIndex, toTagRecords, hoodieTable);
    Map<HoodieKey, Option<Pair<String, String>>> recordLocations = new HashMap<>();
    for (HoodieRecord taggedRecord : taggedRecords) {
        recordLocations.put(taggedRecord.getKey(), taggedRecord.isCurrentLocationKnown() ? Option.of(Pair.of(taggedRecord.getPartitionPath(), taggedRecord.getCurrentLocation().getFileId())) : Option.empty());
    }
    // Should not find any files
    for (Option<Pair<String, String>> record : recordLocations.values()) {
        assertTrue(!record.isPresent());
    }
    // We create three base file, each having one record. (two different partitions)
    String fileId1 = testTable.addCommit("001").getFileIdWithInserts("2016/01/31", record1);
    String fileId2 = testTable.addCommit("002").getFileIdWithInserts("2016/01/31", record2);
    String fileId3 = testTable.addCommit("003").getFileIdWithInserts("2015/01/31", record4);
    // We do the tag again
    metaClient = HoodieTableMetaClient.reload(metaClient);
    hoodieTable = HoodieFlinkTable.create(config, context, metaClient);
    List<HoodieRecord> toTagRecords1 = new ArrayList<>();
    for (HoodieKey key : keys) {
        taggedRecords.add(new HoodieAvroRecord(key, null));
    }
    taggedRecords = tagLocation(bloomIndex, toTagRecords1, hoodieTable);
    recordLocations.clear();
    for (HoodieRecord taggedRecord : taggedRecords) {
        recordLocations.put(taggedRecord.getKey(), taggedRecord.isCurrentLocationKnown() ? Option.of(Pair.of(taggedRecord.getPartitionPath(), taggedRecord.getCurrentLocation().getFileId())) : Option.empty());
    }
    // Check results
    for (Map.Entry<HoodieKey, Option<Pair<String, String>>> record : recordLocations.entrySet()) {
        if (record.getKey().getRecordKey().equals("1eb5b87a-1feh-4edd-87b4-6ec96dc405a0")) {
            assertTrue(record.getValue().isPresent());
            assertEquals(fileId1, record.getValue().get().getRight());
        } else if (record.getKey().getRecordKey().equals("2eb5b87b-1feu-4edd-87b4-6ec96dc405a0")) {
            assertTrue(record.getValue().isPresent());
            if (record.getKey().getPartitionPath().equals("2015/01/31")) {
                assertEquals(fileId3, record.getValue().get().getRight());
            } else {
                assertEquals(fileId2, record.getValue().get().getRight());
            }
        } else if (record.getKey().getRecordKey().equals("3eb5b87c-1fej-4edd-87b4-6ec96dc405a0")) {
            assertFalse(record.getValue().isPresent());
        }
    }
}

Example 48 with HoodieTable

use of org.apache.hudi.table.HoodieTable in project hudi by apache.

the class TestFlinkHoodieBloomIndex method testLoadInvolvedFiles.

@ParameterizedTest(name = TEST_NAME_WITH_PARAMS)
@MethodSource("configParams")
public void testLoadInvolvedFiles(boolean rangePruning, boolean treeFiltering, boolean bucketizedChecking) throws Exception {
    HoodieWriteConfig config = makeConfig(rangePruning, treeFiltering, bucketizedChecking);
    HoodieBloomIndex index = new HoodieBloomIndex(config, ListBasedHoodieBloomIndexHelper.getInstance());
    HoodieTable hoodieTable = HoodieFlinkTable.create(config, context, metaClient, false);
    HoodieFlinkWriteableTestTable testTable = HoodieFlinkWriteableTestTable.of(hoodieTable, SCHEMA);
    // Create some partitions, and put some files
    // "2016/01/21": 0 file
    // "2016/04/01": 1 file (2_0_20160401010101.parquet)
    // "2015/03/12": 3 files (1_0_20150312101010.parquet, 3_0_20150312101010.parquet, 4_0_20150312101010.parquet)
    testTable.withPartitionMetaFiles("2016/01/21", "2016/04/01", "2015/03/12");
    RawTripTestPayload rowChange1 = new RawTripTestPayload("{\"_row_key\":\"000\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}");
    HoodieRecord record1 = new HoodieAvroRecord(new HoodieKey(rowChange1.getRowKey(), rowChange1.getPartitionPath()), rowChange1);
    RawTripTestPayload rowChange2 = new RawTripTestPayload("{\"_row_key\":\"001\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}");
    HoodieRecord record2 = new HoodieAvroRecord(new HoodieKey(rowChange2.getRowKey(), rowChange2.getPartitionPath()), rowChange2);
    RawTripTestPayload rowChange3 = new RawTripTestPayload("{\"_row_key\":\"002\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}");
    HoodieRecord record3 = new HoodieAvroRecord(new HoodieKey(rowChange3.getRowKey(), rowChange3.getPartitionPath()), rowChange3);
    RawTripTestPayload rowChange4 = new RawTripTestPayload("{\"_row_key\":\"003\",\"time\":\"2016-01-31T03:16:41.415Z\",\"number\":12}");
    HoodieRecord record4 = new HoodieAvroRecord(new HoodieKey(rowChange4.getRowKey(), rowChange4.getPartitionPath()), rowChange4);
    List<String> partitions = asList("2016/01/21", "2016/04/01", "2015/03/12");
    List<Pair<String, BloomIndexFileInfo>> filesList = index.loadColumnRangesFromFiles(partitions, context, hoodieTable);
    // Still 0, as no valid commit
    assertEquals(0, filesList.size());
    testTable.addCommit("20160401010101").withInserts("2016/04/01", "2");
    testTable.addCommit("20150312101010").withInserts("2015/03/12", "1").withInserts("2015/03/12", "3", record1).withInserts("2015/03/12", "4", record2, record3, record4);
    metaClient.reloadActiveTimeline();
    filesList = index.loadColumnRangesFromFiles(partitions, context, hoodieTable);
    assertEquals(4, filesList.size());
    if (rangePruning) {
        // these files will not have the key ranges
        assertNull(filesList.get(0).getRight().getMaxRecordKey());
        assertNull(filesList.get(0).getRight().getMinRecordKey());
        assertFalse(filesList.get(1).getRight().hasKeyRanges());
        assertNotNull(filesList.get(2).getRight().getMaxRecordKey());
        assertNotNull(filesList.get(2).getRight().getMinRecordKey());
        assertTrue(filesList.get(3).getRight().hasKeyRanges());
        // no longer sorted, but should have same files.
        List<Pair<String, BloomIndexFileInfo>> expected = asList(Pair.of("2016/04/01", new BloomIndexFileInfo("2")), Pair.of("2015/03/12", new BloomIndexFileInfo("1")), Pair.of("2015/03/12", new BloomIndexFileInfo("3", "000", "000")), Pair.of("2015/03/12", new BloomIndexFileInfo("4", "001", "003")));
        assertEquals(expected, filesList);
    }
}

Example 49 with HoodieTable

use of org.apache.hudi.table.HoodieTable in project hudi by apache.

the class MultipleSparkJobExecutionStrategy method readRecordsForGroupWithLogs.

/**
 * Read records from baseFiles, apply updates and convert to RDD.
 */
private HoodieData<HoodieRecord<T>> readRecordsForGroupWithLogs(JavaSparkContext jsc, List<ClusteringOperation> clusteringOps, String instantTime) {
    HoodieWriteConfig config = getWriteConfig();
    HoodieTable table = getHoodieTable();
    return HoodieJavaRDD.of(jsc.parallelize(clusteringOps, clusteringOps.size()).mapPartitions(clusteringOpsPartition -> {
        List<Iterator<HoodieRecord<T>>> recordIterators = new ArrayList<>();
        clusteringOpsPartition.forEachRemaining(clusteringOp -> {
            long maxMemoryPerCompaction = IOUtils.getMaxMemoryPerCompaction(new SparkTaskContextSupplier(), config);
            LOG.info("MaxMemoryPerCompaction run as part of clustering => " + maxMemoryPerCompaction);
            try {
                Schema readerSchema = HoodieAvroUtils.addMetadataFields(new Schema.Parser().parse(config.getSchema()));
                HoodieMergedLogRecordScanner scanner = HoodieMergedLogRecordScanner.newBuilder().withFileSystem(table.getMetaClient().getFs()).withBasePath(table.getMetaClient().getBasePath()).withLogFilePaths(clusteringOp.getDeltaFilePaths()).withReaderSchema(readerSchema).withLatestInstantTime(instantTime).withMaxMemorySizeInBytes(maxMemoryPerCompaction).withReadBlocksLazily(config.getCompactionLazyBlockReadEnabled()).withReverseReader(config.getCompactionReverseLogReadEnabled()).withBufferSize(config.getMaxDFSStreamBufferSize()).withSpillableMapBasePath(config.getSpillableMapBasePath()).withPartition(clusteringOp.getPartitionPath()).build();
                Option<HoodieFileReader> baseFileReader = StringUtils.isNullOrEmpty(clusteringOp.getDataFilePath()) ? Option.empty() : Option.of(HoodieFileReaderFactory.getFileReader(table.getHadoopConf(), new Path(clusteringOp.getDataFilePath())));
                HoodieTableConfig tableConfig = table.getMetaClient().getTableConfig();
                recordIterators.add(getFileSliceReader(baseFileReader, scanner, readerSchema, tableConfig.getPayloadClass(), tableConfig.getPreCombineField(), tableConfig.populateMetaFields() ? Option.empty() : Option.of(Pair.of(tableConfig.getRecordKeyFieldProp(), tableConfig.getPartitionFieldProp()))));
            } catch (IOException e) {
                throw new HoodieClusteringException("Error reading input data for " + clusteringOp.getDataFilePath() + " and " + clusteringOp.getDeltaFilePaths(), e);
            }
        });
        return new ConcatenatingIterator<>(recordIterators);
    }));
}

Example 50 with HoodieTable

use of org.apache.hudi.table.HoodieTable in project hudi by apache.

the class SparkRDDWriteClient method preCommit.

@Override
protected void preCommit(HoodieInstant inflightInstant, HoodieCommitMetadata metadata) {
    // Create a Hoodie table after startTxn which encapsulated the commits and files visible.
    // Important to create this after the lock to ensure the latest commits show up in the timeline without need for reload
    HoodieTable table = createTable(config, hadoopConf);
    TransactionUtils.resolveWriteConflictIfAny(table, this.txnManager.getCurrentTransactionOwner(), Option.of(metadata), config, txnManager.getLastCompletedTransactionOwner());
}