Examples with BlockMetaData parquet.hadoop.metadata.BlockMetaData used on opensource projects

Example 1 with BlockMetaData

use of parquet.hadoop.metadata.BlockMetaData in project presto by prestodb.

the class ParquetHiveRecordCursor method createParquetRecordReader.

private ParquetRecordReader<FakeParquetRecord> createParquetRecordReader(HdfsEnvironment hdfsEnvironment, String sessionUser, Configuration configuration, Path path, long start, long length, List<HiveColumnHandle> columns, boolean useParquetColumnNames, TypeManager typeManager, boolean predicatePushdownEnabled, TupleDomain<HiveColumnHandle> effectivePredicate) {
    ParquetDataSource dataSource = null;
    try {
        FileSystem fileSystem = hdfsEnvironment.getFileSystem(sessionUser, path, configuration);
        dataSource = buildHdfsParquetDataSource(fileSystem, path, start, length);
        ParquetMetadata parquetMetadata = hdfsEnvironment.doAs(sessionUser, () -> ParquetFileReader.readFooter(configuration, path, NO_FILTER));
        List<BlockMetaData> blocks = parquetMetadata.getBlocks();
        FileMetaData fileMetaData = parquetMetadata.getFileMetaData();
        MessageType fileSchema = fileMetaData.getSchema();
        PrestoReadSupport readSupport = new PrestoReadSupport(useParquetColumnNames, columns, fileSchema);
        List<parquet.schema.Type> fields = columns.stream().filter(column -> column.getColumnType() == REGULAR).map(column -> getParquetType(column, fileSchema, useParquetColumnNames)).filter(Objects::nonNull).collect(toList());
        MessageType requestedSchema = new MessageType(fileSchema.getName(), fields);
        LongArrayList offsets = new LongArrayList(blocks.size());
        for (BlockMetaData block : blocks) {
            long firstDataPage = block.getColumns().get(0).getFirstDataPageOffset();
            if (firstDataPage >= start && firstDataPage < start + length) {
                if (predicatePushdownEnabled) {
                    ParquetPredicate parquetPredicate = buildParquetPredicate(columns, effectivePredicate, fileMetaData.getSchema(), typeManager);
                    if (predicateMatches(parquetPredicate, block, dataSource, requestedSchema, effectivePredicate)) {
                        offsets.add(block.getStartingPos());
                    }
                } else {
                    offsets.add(block.getStartingPos());
                }
            }
        }
        ParquetInputSplit split = new ParquetInputSplit(path, start, start + length, length, null, offsets.toLongArray());
        TaskAttemptContext taskContext = ContextUtil.newTaskAttemptContext(configuration, new TaskAttemptID());
        return hdfsEnvironment.doAs(sessionUser, () -> {
            ParquetRecordReader<FakeParquetRecord> realReader = new PrestoParquetRecordReader(readSupport);
            realReader.initialize(split, taskContext);
            return realReader;
        });
    } catch (Exception e) {
        Throwables.propagateIfInstanceOf(e, PrestoException.class);
        if (e instanceof InterruptedException) {
            Thread.currentThread().interrupt();
            throw Throwables.propagate(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);
    } finally {
        if (dataSource != null) {
            try {
                dataSource.close();
            } catch (IOException ignored) {
            }
        }
    }
}

Example 2 with BlockMetaData

use of parquet.hadoop.metadata.BlockMetaData in project presto by prestodb.

the class ParquetPageSourceFactory method createParquetPageSource.

public static ParquetPageSource createParquetPageSource(HdfsEnvironment hdfsEnvironment, String user, Configuration configuration, Path path, long start, long length, Properties schema, List<HiveColumnHandle> columns, boolean useParquetColumnNames, TypeManager typeManager, boolean predicatePushdownEnabled, TupleDomain<HiveColumnHandle> effectivePredicate) {
    AggregatedMemoryContext systemMemoryContext = new AggregatedMemoryContext();
    ParquetDataSource dataSource = null;
    try {
        FileSystem fileSystem = hdfsEnvironment.getFileSystem(user, path, configuration);
        dataSource = buildHdfsParquetDataSource(fileSystem, path, start, length);
        ParquetMetadata parquetMetadata = ParquetMetadataReader.readFooter(fileSystem, path);
        FileMetaData fileMetaData = parquetMetadata.getFileMetaData();
        MessageType fileSchema = fileMetaData.getSchema();
        List<parquet.schema.Type> fields = columns.stream().filter(column -> column.getColumnType() == REGULAR).map(column -> getParquetType(column, fileSchema, useParquetColumnNames)).filter(Objects::nonNull).collect(toList());
        MessageType requestedSchema = new MessageType(fileSchema.getName(), fields);
        List<BlockMetaData> blocks = new ArrayList<>();
        for (BlockMetaData block : parquetMetadata.getBlocks()) {
            long firstDataPage = block.getColumns().get(0).getFirstDataPageOffset();
            if (firstDataPage >= start && firstDataPage < start + length) {
                blocks.add(block);
            }
        }
        if (predicatePushdownEnabled) {
            ParquetPredicate parquetPredicate = buildParquetPredicate(columns, effectivePredicate, fileMetaData.getSchema(), typeManager);
            final ParquetDataSource finalDataSource = dataSource;
            blocks = blocks.stream().filter(block -> predicateMatches(parquetPredicate, block, finalDataSource, requestedSchema, effectivePredicate)).collect(toList());
        }
        ParquetReader parquetReader = new ParquetReader(fileSchema, requestedSchema, blocks, dataSource, typeManager, systemMemoryContext);
        return new ParquetPageSource(parquetReader, dataSource, fileSchema, requestedSchema, length, schema, columns, effectivePredicate, typeManager, useParquetColumnNames, systemMemoryContext);
    } catch (Exception e) {
        try {
            if (dataSource != null) {
                dataSource.close();
            }
        } catch (IOException ignored) {
        }
        if (e instanceof PrestoException) {
            throw (PrestoException) 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);
    }
}

Example 3 with BlockMetaData

use of parquet.hadoop.metadata.BlockMetaData in project presto by prestodb.

the class ParquetMetadataReader method readFooter.

public static ParquetMetadata readFooter(FileSystem fileSystem, Path file) throws IOException {
    FileStatus fileStatus = fileSystem.getFileStatus(file);
    try (FSDataInputStream inputStream = fileSystem.open(file)) {
        // Parquet File Layout:
        //
        // MAGIC
        // variable: Data
        // variable: Metadata
        // 4 bytes: MetadataLength
        // MAGIC
        long length = fileStatus.getLen();
        validateParquet(length >= MAGIC.length + PARQUET_METADATA_LENGTH + MAGIC.length, "%s is not a valid Parquet File", file);
        long metadataLengthIndex = length - PARQUET_METADATA_LENGTH - MAGIC.length;
        inputStream.seek(metadataLengthIndex);
        int metadataLength = readIntLittleEndian(inputStream);
        byte[] magic = new byte[MAGIC.length];
        inputStream.readFully(magic);
        validateParquet(Arrays.equals(MAGIC, magic), "Not valid Parquet file: %s expected magic number: %s got: %s", file, Arrays.toString(MAGIC), Arrays.toString(magic));
        long metadataIndex = metadataLengthIndex - metadataLength;
        validateParquet(metadataIndex >= MAGIC.length && metadataIndex < metadataLengthIndex, "Corrupted Parquet file: %s metadata index: %s out of range", file, metadataIndex);
        inputStream.seek(metadataIndex);
        FileMetaData fileMetaData = readFileMetaData(inputStream);
        List<SchemaElement> schema = fileMetaData.getSchema();
        validateParquet(!schema.isEmpty(), "Empty Parquet schema in file: %s", file);
        MessageType messageType = readParquetSchema(schema);
        List<BlockMetaData> blocks = new ArrayList<>();
        List<RowGroup> rowGroups = fileMetaData.getRow_groups();
        if (rowGroups != null) {
            for (RowGroup rowGroup : rowGroups) {
                BlockMetaData blockMetaData = new BlockMetaData();
                blockMetaData.setRowCount(rowGroup.getNum_rows());
                blockMetaData.setTotalByteSize(rowGroup.getTotal_byte_size());
                List<ColumnChunk> columns = rowGroup.getColumns();
                validateParquet(!columns.isEmpty(), "No columns in row group: %s", rowGroup);
                String filePath = columns.get(0).getFile_path();
                for (ColumnChunk columnChunk : columns) {
                    validateParquet((filePath == null && columnChunk.getFile_path() == null) || (filePath != null && filePath.equals(columnChunk.getFile_path())), "all column chunks of the same row group must be in the same file");
                    ColumnMetaData metaData = columnChunk.meta_data;
                    String[] path = metaData.path_in_schema.toArray(new String[metaData.path_in_schema.size()]);
                    ColumnPath columnPath = ColumnPath.get(path);
                    ColumnChunkMetaData column = ColumnChunkMetaData.get(columnPath, messageType.getType(columnPath.toArray()).asPrimitiveType().getPrimitiveTypeName(), CompressionCodecName.fromParquet(metaData.codec), readEncodings(metaData.encodings), readStats(metaData.statistics, messageType.getType(columnPath.toArray()).asPrimitiveType().getPrimitiveTypeName()), metaData.data_page_offset, metaData.dictionary_page_offset, metaData.num_values, metaData.total_compressed_size, metaData.total_uncompressed_size);
                    blockMetaData.addColumn(column);
                }
                blockMetaData.setPath(filePath);
                blocks.add(blockMetaData);
            }
        }
        Map<String, String> keyValueMetaData = new HashMap<>();
        List<KeyValue> keyValueList = fileMetaData.getKey_value_metadata();
        if (keyValueList != null) {
            for (KeyValue keyValue : keyValueList) {
                keyValueMetaData.put(keyValue.key, keyValue.value);
            }
        }
        return new ParquetMetadata(new parquet.hadoop.metadata.FileMetaData(messageType, keyValueMetaData, fileMetaData.getCreated_by()), blocks);
    }
}