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Example 11 with FileMetaData

use of org.apache.parquet.hadoop.metadata.FileMetaData in project parquet-mr by apache.

the class ParquetFileWriter method end.

/**
 * ends a file once all blocks have been written.
 * closes the file.
 * @param extraMetaData the extra meta data to write in the footer
 * @throws IOException
 */
public void end(Map<String, String> extraMetaData) throws IOException {
    state = state.end();
    LOG.debug("{}: end", out.getPos());
    this.footer = new ParquetMetadata(new FileMetaData(schema, extraMetaData, Version.FULL_VERSION), blocks);
    serializeFooter(footer, out);
    out.close();
}
Also used : ParquetMetadata(org.apache.parquet.hadoop.metadata.ParquetMetadata) Util.writeFileMetaData(org.apache.parquet.format.Util.writeFileMetaData) FileMetaData(org.apache.parquet.hadoop.metadata.FileMetaData)

Example 12 with FileMetaData

use of org.apache.parquet.hadoop.metadata.FileMetaData in project parquet-mr by apache.

the class TestInputFormat method setUp.

/*
    The test File contains 2-3 hdfs blocks based on the setting of each test, when hdfsBlock size is set to 50: [0-49][50-99]
    each row group is of size 10, so the rowGroups layout on hdfs is like:
    xxxxx xxxxx
    each x is a row group, each groups of x's is a hdfsBlock
   */
@Before
public void setUp() {
    blocks = new ArrayList<BlockMetaData>();
    for (int i = 0; i < 10; i++) {
        blocks.add(newBlock(i * 10, 10));
    }
    schema = MessageTypeParser.parseMessageType("message doc { required binary foo; }");
    fileMetaData = new FileMetaData(schema, new HashMap<String, String>(), "parquet-mr");
}
Also used : BlockMetaData(org.apache.parquet.hadoop.metadata.BlockMetaData) HashMap(java.util.HashMap) FileMetaData(org.apache.parquet.hadoop.metadata.FileMetaData) Before(org.junit.Before)

Example 13 with FileMetaData

use of org.apache.parquet.hadoop.metadata.FileMetaData in project components by Talend.

the class ParquetHdfsFileSink method mergeOutput.

@Override
protected boolean mergeOutput(FileSystem fs, String sourceFolder, String targetFile) {
    try {
        FileStatus[] sourceStatuses = FileSystemUtil.listSubFiles(fs, sourceFolder);
        List<Path> sourceFiles = new ArrayList<>();
        for (FileStatus sourceStatus : sourceStatuses) {
            sourceFiles.add(sourceStatus.getPath());
        }
        FileMetaData mergedMeta = ParquetFileWriter.mergeMetadataFiles(sourceFiles, fs.getConf()).getFileMetaData();
        ParquetFileWriter writer = new ParquetFileWriter(fs.getConf(), mergedMeta.getSchema(), new Path(targetFile), ParquetFileWriter.Mode.CREATE);
        writer.start();
        for (Path input : sourceFiles) {
            writer.appendFile(fs.getConf(), input);
        }
        writer.end(mergedMeta.getKeyValueMetaData());
    } catch (Exception e) {
        LOG.error("Error when merging files in {}.\n{}", sourceFolder, e.getMessage());
        return false;
    }
    return true;
}
Also used : Path(org.apache.hadoop.fs.Path) FileStatus(org.apache.hadoop.fs.FileStatus) ParquetFileWriter(org.apache.parquet.hadoop.ParquetFileWriter) ArrayList(java.util.ArrayList) FileMetaData(org.apache.parquet.hadoop.metadata.FileMetaData)

Example 14 with FileMetaData

use of org.apache.parquet.hadoop.metadata.FileMetaData in project hive by apache.

the class ParquetRecordReaderBase method getSplit.

/**
 * gets a ParquetInputSplit corresponding to a split given by Hive
 *
 * @param oldSplit The split given by Hive
 * @param conf The JobConf of the Hive job
 * @return a ParquetInputSplit corresponding to the oldSplit
 * @throws IOException if the config cannot be enhanced or if the footer cannot be read from the file
 */
@SuppressWarnings("deprecation")
protected ParquetInputSplit getSplit(final org.apache.hadoop.mapred.InputSplit oldSplit, final JobConf conf) throws IOException {
    if (oldSplit.getLength() == 0) {
        return null;
    }
    ParquetInputSplit split;
    if (oldSplit instanceof FileSplit) {
        final Path finalPath = ((FileSplit) oldSplit).getPath();
        jobConf = projectionPusher.pushProjectionsAndFilters(conf, finalPath.getParent());
        // TODO enable MetadataFilter by using readFooter(Configuration configuration, Path file,
        // MetadataFilter filter) API
        final ParquetMetadata parquetMetadata = ParquetFileReader.readFooter(jobConf, finalPath);
        final List<BlockMetaData> blocks = parquetMetadata.getBlocks();
        final FileMetaData fileMetaData = parquetMetadata.getFileMetaData();
        final ReadSupport.ReadContext readContext = new DataWritableReadSupport().init(new InitContext(jobConf, null, fileMetaData.getSchema()));
        // Compute stats
        for (BlockMetaData bmd : blocks) {
            serDeStats.setRowCount(serDeStats.getRowCount() + bmd.getRowCount());
            serDeStats.setRawDataSize(serDeStats.getRawDataSize() + bmd.getTotalByteSize());
        }
        schemaSize = MessageTypeParser.parseMessageType(readContext.getReadSupportMetadata().get(DataWritableReadSupport.HIVE_TABLE_AS_PARQUET_SCHEMA)).getFieldCount();
        final List<BlockMetaData> splitGroup = new ArrayList<BlockMetaData>();
        final long splitStart = ((FileSplit) oldSplit).getStart();
        final long splitLength = ((FileSplit) oldSplit).getLength();
        for (final BlockMetaData block : blocks) {
            final long firstDataPage = block.getColumns().get(0).getFirstDataPageOffset();
            if (firstDataPage >= splitStart && firstDataPage < splitStart + splitLength) {
                splitGroup.add(block);
            }
        }
        if (splitGroup.isEmpty()) {
            LOG.warn("Skipping split, could not find row group in: " + oldSplit);
            return null;
        }
        FilterCompat.Filter filter = setFilter(jobConf, fileMetaData.getSchema());
        if (filter != null) {
            filtedBlocks = RowGroupFilter.filterRowGroups(filter, splitGroup, fileMetaData.getSchema());
            if (filtedBlocks.isEmpty()) {
                LOG.debug("All row groups are dropped due to filter predicates");
                return null;
            }
            long droppedBlocks = splitGroup.size() - filtedBlocks.size();
            if (droppedBlocks > 0) {
                LOG.debug("Dropping " + droppedBlocks + " row groups that do not pass filter predicate");
            }
        } else {
            filtedBlocks = splitGroup;
        }
        if (HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_PARQUET_TIMESTAMP_SKIP_CONVERSION)) {
            skipTimestampConversion = !Strings.nullToEmpty(fileMetaData.getCreatedBy()).startsWith("parquet-mr");
        }
        skipProlepticConversion = DataWritableReadSupport.getWriterDateProleptic(fileMetaData.getKeyValueMetaData());
        if (skipProlepticConversion == null) {
            skipProlepticConversion = HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_PARQUET_DATE_PROLEPTIC_GREGORIAN_DEFAULT);
        }
        legacyConversionEnabled = HiveConf.getBoolVar(conf, ConfVars.HIVE_PARQUET_TIMESTAMP_LEGACY_CONVERSION_ENABLED);
        if (fileMetaData.getKeyValueMetaData().containsKey(DataWritableWriteSupport.WRITER_ZONE_CONVERSION_LEGACY)) {
            legacyConversionEnabled = Boolean.parseBoolean(fileMetaData.getKeyValueMetaData().get(DataWritableWriteSupport.WRITER_ZONE_CONVERSION_LEGACY));
        }
        split = new ParquetInputSplit(finalPath, splitStart, splitLength, oldSplit.getLocations(), filtedBlocks, readContext.getRequestedSchema().toString(), fileMetaData.getSchema().toString(), fileMetaData.getKeyValueMetaData(), readContext.getReadSupportMetadata());
        return split;
    } else {
        throw new IllegalArgumentException("Unknown split type: " + oldSplit);
    }
}
Also used : Path(org.apache.hadoop.fs.Path) BlockMetaData(org.apache.parquet.hadoop.metadata.BlockMetaData) DataWritableReadSupport(org.apache.hadoop.hive.ql.io.parquet.read.DataWritableReadSupport) ParquetMetadata(org.apache.parquet.hadoop.metadata.ParquetMetadata) FilterCompat(org.apache.parquet.filter2.compat.FilterCompat) ArrayList(java.util.ArrayList) FileSplit(org.apache.hadoop.mapred.FileSplit) ReadSupport(org.apache.parquet.hadoop.api.ReadSupport) DataWritableReadSupport(org.apache.hadoop.hive.ql.io.parquet.read.DataWritableReadSupport) InitContext(org.apache.parquet.hadoop.api.InitContext) ParquetInputSplit(org.apache.parquet.hadoop.ParquetInputSplit) FileMetaData(org.apache.parquet.hadoop.metadata.FileMetaData)

Example 15 with FileMetaData

use of org.apache.parquet.hadoop.metadata.FileMetaData in project presto by prestodb.

the class ParquetPageSourceFactory method createParquetPageSource.

public static ConnectorPageSource createParquetPageSource(HdfsEnvironment hdfsEnvironment, String user, Configuration configuration, Path path, long start, long length, long fileSize, List<HiveColumnHandle> columns, SchemaTableName tableName, boolean useParquetColumnNames, DataSize maxReadBlockSize, boolean batchReaderEnabled, boolean verificationEnabled, TypeManager typeManager, StandardFunctionResolution functionResolution, TupleDomain<HiveColumnHandle> effectivePredicate, FileFormatDataSourceStats stats, HiveFileContext hiveFileContext, ParquetMetadataSource parquetMetadataSource, boolean columnIndexFilterEnabled) {
    AggregatedMemoryContext systemMemoryContext = newSimpleAggregatedMemoryContext();
    ParquetDataSource dataSource = null;
    try {
        FSDataInputStream inputStream = hdfsEnvironment.getFileSystem(user, path, configuration).openFile(path, hiveFileContext);
        dataSource = buildHdfsParquetDataSource(inputStream, path, stats);
        ParquetMetadata parquetMetadata = parquetMetadataSource.getParquetMetadata(dataSource, fileSize, hiveFileContext.isCacheable()).getParquetMetadata();
        if (!columns.isEmpty() && columns.stream().allMatch(hiveColumnHandle -> hiveColumnHandle.getColumnType() == AGGREGATED)) {
            return new AggregatedParquetPageSource(columns, parquetMetadata, typeManager, functionResolution);
        }
        FileMetaData fileMetaData = parquetMetadata.getFileMetaData();
        MessageType fileSchema = fileMetaData.getSchema();
        Optional<MessageType> message = columns.stream().filter(column -> column.getColumnType() == REGULAR || isPushedDownSubfield(column)).map(column -> getColumnType(typeManager.getType(column.getTypeSignature()), fileSchema, useParquetColumnNames, column, tableName, path)).filter(Optional::isPresent).map(Optional::get).map(type -> new MessageType(fileSchema.getName(), type)).reduce(MessageType::union);
        MessageType requestedSchema = message.orElse(new MessageType(fileSchema.getName(), ImmutableList.of()));
        ImmutableList.Builder<BlockMetaData> footerBlocks = ImmutableList.builder();
        for (BlockMetaData block : parquetMetadata.getBlocks()) {
            long firstDataPage = block.getColumns().get(0).getFirstDataPageOffset();
            if (firstDataPage >= start && firstDataPage < start + length) {
                footerBlocks.add(block);
            }
        }
        Map<List<String>, RichColumnDescriptor> descriptorsByPath = getDescriptors(fileSchema, requestedSchema);
        TupleDomain<ColumnDescriptor> parquetTupleDomain = getParquetTupleDomain(descriptorsByPath, effectivePredicate);
        Predicate parquetPredicate = buildPredicate(requestedSchema, parquetTupleDomain, descriptorsByPath);
        final ParquetDataSource finalDataSource = dataSource;
        ImmutableList.Builder<BlockMetaData> blocks = ImmutableList.builder();
        List<ColumnIndexStore> blockIndexStores = new ArrayList<>();
        for (BlockMetaData block : footerBlocks.build()) {
            Optional<ColumnIndexStore> columnIndexStore = ColumnIndexFilterUtils.getColumnIndexStore(parquetPredicate, finalDataSource, block, descriptorsByPath, columnIndexFilterEnabled);
            if (predicateMatches(parquetPredicate, block, finalDataSource, descriptorsByPath, parquetTupleDomain, columnIndexStore, columnIndexFilterEnabled)) {
                blocks.add(block);
                blockIndexStores.add(columnIndexStore.orElse(null));
                hiveFileContext.incrementCounter("parquet.blocksRead", 1);
                hiveFileContext.incrementCounter("parquet.rowsRead", block.getRowCount());
                hiveFileContext.incrementCounter("parquet.totalBytesRead", block.getTotalByteSize());
            } else {
                hiveFileContext.incrementCounter("parquet.blocksSkipped", 1);
                hiveFileContext.incrementCounter("parquet.rowsSkipped", block.getRowCount());
                hiveFileContext.incrementCounter("parquet.totalBytesSkipped", block.getTotalByteSize());
            }
        }
        MessageColumnIO messageColumnIO = getColumnIO(fileSchema, requestedSchema);
        ParquetReader parquetReader = new ParquetReader(messageColumnIO, blocks.build(), dataSource, systemMemoryContext, maxReadBlockSize, batchReaderEnabled, verificationEnabled, parquetPredicate, blockIndexStores, columnIndexFilterEnabled);
        ImmutableList.Builder<String> namesBuilder = ImmutableList.builder();
        ImmutableList.Builder<Type> typesBuilder = ImmutableList.builder();
        ImmutableList.Builder<Optional<Field>> fieldsBuilder = ImmutableList.builder();
        for (HiveColumnHandle column : columns) {
            checkArgument(column.getColumnType() == REGULAR || column.getColumnType() == SYNTHESIZED, "column type must be regular or synthesized column");
            String name = column.getName();
            Type type = typeManager.getType(column.getTypeSignature());
            namesBuilder.add(name);
            typesBuilder.add(type);
            if (column.getColumnType() == SYNTHESIZED) {
                Subfield pushedDownSubfield = getPushedDownSubfield(column);
                List<String> nestedColumnPath = nestedColumnPath(pushedDownSubfield);
                Optional<ColumnIO> columnIO = findNestedColumnIO(lookupColumnByName(messageColumnIO, pushedDownSubfield.getRootName()), nestedColumnPath);
                if (columnIO.isPresent()) {
                    fieldsBuilder.add(constructField(type, columnIO.get()));
                } else {
                    fieldsBuilder.add(Optional.empty());
                }
            } else if (getParquetType(type, fileSchema, useParquetColumnNames, column, tableName, path).isPresent()) {
                String columnName = useParquetColumnNames ? name : fileSchema.getFields().get(column.getHiveColumnIndex()).getName();
                fieldsBuilder.add(constructField(type, lookupColumnByName(messageColumnIO, columnName)));
            } else {
                fieldsBuilder.add(Optional.empty());
            }
        }
        return new ParquetPageSource(parquetReader, typesBuilder.build(), fieldsBuilder.build(), namesBuilder.build(), hiveFileContext.getStats());
    } catch (Exception e) {
        try {
            if (dataSource != null) {
                dataSource.close();
            }
        } catch (IOException ignored) {
        }
        if (e instanceof PrestoException) {
            throw (PrestoException) e;
        }
        if (e instanceof ParquetCorruptionException) {
            throw new PrestoException(HIVE_BAD_DATA, e);
        }
        if (e instanceof AccessControlException) {
            throw new PrestoException(PERMISSION_DENIED, e.getMessage(), e);
        }
        if (nullToEmpty(e.getMessage()).trim().equals("Filesystem closed") || e instanceof FileNotFoundException) {
            throw new PrestoException(HIVE_CANNOT_OPEN_SPLIT, e);
        }
        String message = format("Error opening Hive split %s (offset=%s, length=%s): %s", path, start, length, e.getMessage());
        if (e.getClass().getSimpleName().equals("BlockMissingException")) {
            throw new PrestoException(HIVE_MISSING_DATA, message, e);
        }
        throw new PrestoException(HIVE_CANNOT_OPEN_SPLIT, message, e);
    }
}
Also used : RichColumnDescriptor(com.facebook.presto.parquet.RichColumnDescriptor) DateTimeZone(org.joda.time.DateTimeZone) TINYINT(com.facebook.presto.common.type.StandardTypes.TINYINT) HIVE_PARTITION_SCHEMA_MISMATCH(com.facebook.presto.hive.HiveErrorCode.HIVE_PARTITION_SCHEMA_MISMATCH) HiveSessionProperties.isUseParquetColumnNames(com.facebook.presto.hive.HiveSessionProperties.isUseParquetColumnNames) ROW(com.facebook.presto.common.type.StandardTypes.ROW) ParquetCorruptionException(com.facebook.presto.parquet.ParquetCorruptionException) AGGREGATED(com.facebook.presto.hive.HiveColumnHandle.ColumnType.AGGREGATED) Configuration(org.apache.hadoop.conf.Configuration) Map(java.util.Map) FileFormatDataSourceStats(com.facebook.presto.hive.FileFormatDataSourceStats) FSDataInputStream(org.apache.hadoop.fs.FSDataInputStream) ParquetDataSource(com.facebook.presto.parquet.ParquetDataSource) ParquetMetadataSource(com.facebook.presto.parquet.cache.ParquetMetadataSource) Set(java.util.Set) 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Aggregations

FileMetaData (org.apache.parquet.hadoop.metadata.FileMetaData)16 ParquetMetadata (org.apache.parquet.hadoop.metadata.ParquetMetadata)11 Path (org.apache.hadoop.fs.Path)10 ArrayList (java.util.ArrayList)7 BlockMetaData (org.apache.parquet.hadoop.metadata.BlockMetaData)7 Domain (com.facebook.presto.common.predicate.Domain)3 TupleDomain (com.facebook.presto.common.predicate.TupleDomain)3 Type (com.facebook.presto.common.type.Type)3 TypeManager (com.facebook.presto.common.type.TypeManager)3 FileFormatDataSourceStats (com.facebook.presto.hive.FileFormatDataSourceStats)3 HdfsEnvironment (com.facebook.presto.hive.HdfsEnvironment)3 IOException (java.io.IOException)3 ColumnDescriptor (org.apache.parquet.column.ColumnDescriptor)3 RuntimeStats (com.facebook.presto.common.RuntimeStats)2 HdfsContext (com.facebook.presto.hive.HdfsContext)2 HdfsParquetDataSource.buildHdfsParquetDataSource (com.facebook.presto.hive.parquet.HdfsParquetDataSource.buildHdfsParquetDataSource)2 ParquetPageSource (com.facebook.presto.hive.parquet.ParquetPageSource)2 AggregatedMemoryContext (com.facebook.presto.memory.context.AggregatedMemoryContext)2 AggregatedMemoryContext.newSimpleAggregatedMemoryContext (com.facebook.presto.memory.context.AggregatedMemoryContext.newSimpleAggregatedMemoryContext)2 Field (com.facebook.presto.parquet.Field)2