Examples with ParquetDataSource io.trino.parquet.ParquetDataSource used on opensource projects

Example 1 with ParquetDataSource

use of io.trino.parquet.ParquetDataSource in project trino by trinodb.

the class ParquetPageSourceFactory method createPageSource.

/**
 * This method is available for other callers to use directly.
 */
public static ReaderPageSource createPageSource(Path path, long start, long length, long estimatedFileSize, List<HiveColumnHandle> columns, TupleDomain<HiveColumnHandle> effectivePredicate, boolean useColumnNames, HdfsEnvironment hdfsEnvironment, Configuration configuration, ConnectorIdentity identity, DateTimeZone timeZone, FileFormatDataSourceStats stats, ParquetReaderOptions options) {
    // Ignore predicates on partial columns for now.
    effectivePredicate = effectivePredicate.filter((column, domain) -> column.isBaseColumn());
    MessageType fileSchema;
    MessageType requestedSchema;
    MessageColumnIO messageColumn;
    ParquetReader parquetReader;
    ParquetDataSource dataSource = null;
    try {
        FileSystem fileSystem = hdfsEnvironment.getFileSystem(identity, path, configuration);
        FSDataInputStream inputStream = hdfsEnvironment.doAs(identity, () -> fileSystem.open(path));
        dataSource = new HdfsParquetDataSource(new ParquetDataSourceId(path.toString()), estimatedFileSize, inputStream, stats, options);
        ParquetMetadata parquetMetadata = MetadataReader.readFooter(dataSource);
        FileMetaData fileMetaData = parquetMetadata.getFileMetaData();
        fileSchema = fileMetaData.getSchema();
        Optional<MessageType> message = projectSufficientColumns(columns).map(projection -> projection.get().stream().map(HiveColumnHandle.class::cast).collect(toUnmodifiableList())).orElse(columns).stream().filter(column -> column.getColumnType() == REGULAR).map(column -> getColumnType(column, fileSchema, useColumnNames)).filter(Optional::isPresent).map(Optional::get).map(type -> new MessageType(fileSchema.getName(), type)).reduce(MessageType::union);
        requestedSchema = message.orElse(new MessageType(fileSchema.getName(), ImmutableList.of()));
        messageColumn = getColumnIO(fileSchema, requestedSchema);
        Map<List<String>, RichColumnDescriptor> descriptorsByPath = getDescriptors(fileSchema, requestedSchema);
        TupleDomain<ColumnDescriptor> parquetTupleDomain = options.isIgnoreStatistics() ? TupleDomain.all() : getParquetTupleDomain(descriptorsByPath, effectivePredicate, fileSchema, useColumnNames);
        Predicate parquetPredicate = buildPredicate(requestedSchema, parquetTupleDomain, descriptorsByPath, timeZone);
        long nextStart = 0;
        ImmutableList.Builder<BlockMetaData> blocks = ImmutableList.builder();
        ImmutableList.Builder<Long> blockStarts = ImmutableList.builder();
        ImmutableList.Builder<Optional<ColumnIndexStore>> columnIndexes = ImmutableList.builder();
        for (BlockMetaData block : parquetMetadata.getBlocks()) {
            long firstDataPage = block.getColumns().get(0).getFirstDataPageOffset();
            Optional<ColumnIndexStore> columnIndex = getColumnIndexStore(dataSource, block, descriptorsByPath, parquetTupleDomain, options);
            if (start <= firstDataPage && firstDataPage < start + length && predicateMatches(parquetPredicate, block, dataSource, descriptorsByPath, parquetTupleDomain, columnIndex)) {
                blocks.add(block);
                blockStarts.add(nextStart);
                columnIndexes.add(columnIndex);
            }
            nextStart += block.getRowCount();
        }
        parquetReader = new ParquetReader(Optional.ofNullable(fileMetaData.getCreatedBy()), messageColumn, blocks.build(), Optional.of(blockStarts.build()), dataSource, timeZone, newSimpleAggregatedMemoryContext(), options, parquetPredicate, columnIndexes.build());
    } catch (Exception e) {
        try {
            if (dataSource != null) {
                dataSource.close();
            }
        } catch (IOException ignored) {
        }
        if (e instanceof TrinoException) {
            throw (TrinoException) e;
        }
        if (e instanceof ParquetCorruptionException) {
            throw new TrinoException(HIVE_BAD_DATA, e);
        }
        if (nullToEmpty(e.getMessage()).trim().equals("Filesystem closed") || e instanceof FileNotFoundException) {
            throw new TrinoException(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 instanceof BlockMissingException) {
            throw new TrinoException(HIVE_MISSING_DATA, message, e);
        }
        throw new TrinoException(HIVE_CANNOT_OPEN_SPLIT, message, e);
    }
    Optional<ReaderColumns> readerProjections = projectBaseColumns(columns);
    List<HiveColumnHandle> baseColumns = readerProjections.map(projection -> projection.get().stream().map(HiveColumnHandle.class::cast).collect(toUnmodifiableList())).orElse(columns);
    for (HiveColumnHandle column : baseColumns) {
        checkArgument(column == PARQUET_ROW_INDEX_COLUMN || column.getColumnType() == REGULAR, "column type must be REGULAR: %s", column);
    }
    ImmutableList.Builder<Type> trinoTypes = ImmutableList.builder();
    ImmutableList.Builder<Optional<Field>> internalFields = ImmutableList.builder();
    ImmutableList.Builder<Boolean> rowIndexColumns = ImmutableList.builder();
    for (HiveColumnHandle column : baseColumns) {
        trinoTypes.add(column.getBaseType());
        rowIndexColumns.add(column == PARQUET_ROW_INDEX_COLUMN);
        if (column == PARQUET_ROW_INDEX_COLUMN) {
            internalFields.add(Optional.empty());
        } else {
            internalFields.add(Optional.ofNullable(getParquetType(column, fileSchema, useColumnNames)).flatMap(field -> {
                String columnName = useColumnNames ? column.getBaseColumnName() : fileSchema.getFields().get(column.getBaseHiveColumnIndex()).getName();
                return constructField(column.getBaseType(), lookupColumnByName(messageColumn, columnName));
            }));
        }
    }
    ConnectorPageSource parquetPageSource = new ParquetPageSource(parquetReader, trinoTypes.build(), rowIndexColumns.build(), internalFields.build());
    return new ReaderPageSource(parquetPageSource, readerProjections);
}

Example 2 with ParquetDataSource

use of io.trino.parquet.ParquetDataSource in project trino by trinodb.

the class IcebergPageSourceProvider method createParquetPageSource.

private static ReaderPageSource createParquetPageSource(HdfsEnvironment hdfsEnvironment, ConnectorIdentity identity, Configuration configuration, Path path, long start, long length, long fileSize, List<IcebergColumnHandle> regularColumns, ParquetReaderOptions options, TupleDomain<IcebergColumnHandle> effectivePredicate, FileFormatDataSourceStats fileFormatDataSourceStats, Optional<NameMapping> nameMapping) {
    AggregatedMemoryContext memoryContext = newSimpleAggregatedMemoryContext();
    ParquetDataSource dataSource = null;
    try {
        FileSystem fileSystem = hdfsEnvironment.getFileSystem(identity, path, configuration);
        FSDataInputStream inputStream = hdfsEnvironment.doAs(identity, () -> fileSystem.open(path));
        dataSource = new HdfsParquetDataSource(new ParquetDataSourceId(path.toString()), fileSize, inputStream, fileFormatDataSourceStats, options);
        // extra variable required for lambda below
        ParquetDataSource theDataSource = dataSource;
        ParquetMetadata parquetMetadata = hdfsEnvironment.doAs(identity, () -> MetadataReader.readFooter(theDataSource));
        FileMetaData fileMetaData = parquetMetadata.getFileMetaData();
        MessageType fileSchema = fileMetaData.getSchema();
        if (nameMapping.isPresent() && !ParquetSchemaUtil.hasIds(fileSchema)) {
            // NameMapping conversion is necessary because MetadataReader converts all column names to lowercase and NameMapping is case sensitive
            fileSchema = ParquetSchemaUtil.applyNameMapping(fileSchema, convertToLowercase(nameMapping.get()));
        }
        // Mapping from Iceberg field ID to Parquet fields.
        Map<Integer, org.apache.parquet.schema.Type> parquetIdToField = fileSchema.getFields().stream().filter(field -> field.getId() != null).collect(toImmutableMap(field -> field.getId().intValue(), Function.identity()));
        Optional<ReaderColumns> columnProjections = projectColumns(regularColumns);
        List<IcebergColumnHandle> readColumns = columnProjections.map(readerColumns -> (List<IcebergColumnHandle>) readerColumns.get().stream().map(IcebergColumnHandle.class::cast).collect(toImmutableList())).orElse(regularColumns);
        List<org.apache.parquet.schema.Type> parquetFields = readColumns.stream().map(column -> parquetIdToField.get(column.getId())).collect(toList());
        MessageType requestedSchema = new MessageType(fileSchema.getName(), parquetFields.stream().filter(Objects::nonNull).collect(toImmutableList()));
        Map<List<String>, RichColumnDescriptor> descriptorsByPath = getDescriptors(fileSchema, requestedSchema);
        TupleDomain<ColumnDescriptor> parquetTupleDomain = getParquetTupleDomain(descriptorsByPath, effectivePredicate);
        Predicate parquetPredicate = buildPredicate(requestedSchema, parquetTupleDomain, descriptorsByPath, UTC);
        List<BlockMetaData> blocks = new ArrayList<>();
        for (BlockMetaData block : parquetMetadata.getBlocks()) {
            long firstDataPage = block.getColumns().get(0).getFirstDataPageOffset();
            if (start <= firstDataPage && firstDataPage < start + length && predicateMatches(parquetPredicate, block, dataSource, descriptorsByPath, parquetTupleDomain)) {
                blocks.add(block);
            }
        }
        MessageColumnIO messageColumnIO = getColumnIO(fileSchema, requestedSchema);
        ParquetReader parquetReader = new ParquetReader(Optional.ofNullable(fileMetaData.getCreatedBy()), messageColumnIO, blocks, Optional.empty(), dataSource, UTC, memoryContext, options);
        ImmutableList.Builder<Type> trinoTypes = ImmutableList.builder();
        ImmutableList.Builder<Optional<Field>> internalFields = ImmutableList.builder();
        for (int columnIndex = 0; columnIndex < readColumns.size(); columnIndex++) {
            IcebergColumnHandle column = readColumns.get(columnIndex);
            org.apache.parquet.schema.Type parquetField = parquetFields.get(columnIndex);
            Type trinoType = column.getBaseType();
            trinoTypes.add(trinoType);
            if (parquetField == null) {
                internalFields.add(Optional.empty());
            } else {
                // The top level columns are already mapped by name/id appropriately.
                ColumnIO columnIO = messageColumnIO.getChild(parquetField.getName());
                internalFields.add(IcebergParquetColumnIOConverter.constructField(new FieldContext(trinoType, column.getColumnIdentity()), columnIO));
            }
        }
        return new ReaderPageSource(new ParquetPageSource(parquetReader, trinoTypes.build(), internalFields.build()), columnProjections);
    } catch (IOException | RuntimeException e) {
        try {
            if (dataSource != null) {
                dataSource.close();
            }
        } catch (IOException ignored) {
        }
        if (e instanceof TrinoException) {
            throw (TrinoException) e;
        }
        String message = format("Error opening Iceberg split %s (offset=%s, length=%s): %s", path, start, length, e.getMessage());
        if (e instanceof ParquetCorruptionException) {
            throw new TrinoException(ICEBERG_BAD_DATA, message, e);
        }
        if (e instanceof BlockMissingException) {
            throw new TrinoException(ICEBERG_MISSING_DATA, message, e);
        }
        throw new TrinoException(ICEBERG_CANNOT_OPEN_SPLIT, message, e);
    }
}

Example 3 with ParquetDataSource

use of io.trino.parquet.ParquetDataSource in project trino by trinodb.

the class ParquetPageSourceFactory method getColumnIndexStore.

private static Optional<ColumnIndexStore> getColumnIndexStore(ParquetDataSource dataSource, BlockMetaData blockMetadata, Map<List<String>, RichColumnDescriptor> descriptorsByPath, TupleDomain<ColumnDescriptor> parquetTupleDomain, ParquetReaderOptions options) {
    if (!options.isUseColumnIndex() || parquetTupleDomain.isAll() || parquetTupleDomain.isNone()) {
        return Optional.empty();
    }
    boolean hasColumnIndex = false;
    for (ColumnChunkMetaData column : blockMetadata.getColumns()) {
        if (column.getColumnIndexReference() != null && column.getOffsetIndexReference() != null) {
            hasColumnIndex = true;
            break;
        }
    }
    if (!hasColumnIndex) {
        return Optional.empty();
    }
    Set<ColumnPath> columnsReadPaths = new HashSet<>(descriptorsByPath.size());
    for (List<String> path : descriptorsByPath.keySet()) {
        columnsReadPaths.add(ColumnPath.get(path.toArray(new String[0])));
    }
    Map<ColumnDescriptor, Domain> parquetDomains = parquetTupleDomain.getDomains().orElseThrow(() -> new IllegalStateException("Predicate other than none should have domains"));
    Set<ColumnPath> columnsFilteredPaths = parquetDomains.keySet().stream().map(column -> ColumnPath.get(column.getPath())).collect(toImmutableSet());
    return Optional.of(new TrinoColumnIndexStore(dataSource, blockMetadata, columnsReadPaths, columnsFilteredPaths));
}

Example 4 with ParquetDataSource

use of io.trino.parquet.ParquetDataSource in project trino by trinodb.

the class MetadataReader method readFooter.

public static ParquetMetadata readFooter(ParquetDataSource dataSource) throws IOException {
    // Parquet File Layout:
    // 
    // MAGIC
    // variable: Data
    // variable: Metadata
    // 4 bytes: MetadataLength
    // MAGIC
    validateParquet(dataSource.getEstimatedSize() >= MAGIC.length() + POST_SCRIPT_SIZE, "%s is not a valid Parquet File", dataSource.getId());
    // Read the tail of the file
    long estimatedFileSize = dataSource.getEstimatedSize();
    long expectedReadSize = min(estimatedFileSize, EXPECTED_FOOTER_SIZE);
    Slice buffer = dataSource.readTail(toIntExact(expectedReadSize));
    Slice magic = buffer.slice(buffer.length() - MAGIC.length(), MAGIC.length());
    validateParquet(MAGIC.equals(magic), "Not valid Parquet file: %s expected magic number: %s got: %s", dataSource.getId(), MAGIC.toStringUtf8(), magic.toStringUtf8());
    int metadataLength = buffer.getInt(buffer.length() - POST_SCRIPT_SIZE);
    long metadataIndex = estimatedFileSize - POST_SCRIPT_SIZE - metadataLength;
    validateParquet(metadataIndex >= MAGIC.length() && metadataIndex < estimatedFileSize - POST_SCRIPT_SIZE, "Corrupted Parquet file: %s metadata index: %s out of range", dataSource.getId(), metadataIndex);
    int completeFooterSize = metadataLength + POST_SCRIPT_SIZE;
    if (completeFooterSize > buffer.length()) {
        // initial read was not large enough, so just read again with the correct size
        buffer = dataSource.readTail(completeFooterSize);
    }
    InputStream metadataStream = buffer.slice(buffer.length() - completeFooterSize, metadataLength).getInput();
    FileMetaData fileMetaData = readFileMetaData(metadataStream);
    List<SchemaElement> schema = fileMetaData.getSchema();
    validateParquet(!schema.isEmpty(), "Empty Parquet schema in file: %s", dataSource.getId());
    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.stream().map(value -> value.toLowerCase(Locale.ENGLISH)).toArray(String[]::new);
                ColumnPath columnPath = ColumnPath.get(path);
                PrimitiveType primitiveType = messageType.getType(columnPath.toArray()).asPrimitiveType();
                ColumnChunkMetaData column = ColumnChunkMetaData.get(columnPath, primitiveType, CompressionCodecName.fromParquet(metaData.codec), PARQUET_METADATA_CONVERTER.convertEncodingStats(metaData.encoding_stats), readEncodings(metaData.encodings), readStats(Optional.ofNullable(fileMetaData.getCreated_by()), Optional.ofNullable(metaData.statistics), primitiveType), metaData.data_page_offset, metaData.dictionary_page_offset, metaData.num_values, metaData.total_compressed_size, metaData.total_uncompressed_size);
                column.setColumnIndexReference(toColumnIndexReference(columnChunk));
                column.setOffsetIndexReference(toOffsetIndexReference(columnChunk));
                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 org.apache.parquet.hadoop.metadata.FileMetaData(messageType, keyValueMetaData, fileMetaData.getCreated_by()), blocks);
}