Examples with FileFormatDataSourceStats com.facebook.presto.hive.FileFormatDataSourceStats used on opensource projects

Example 1 with FileFormatDataSourceStats

use of com.facebook.presto.hive.FileFormatDataSourceStats in project presto by prestodb.

the class DeltaPageSourceProvider method createParquetPageSource.

private static ConnectorPageSource createParquetPageSource(HdfsEnvironment hdfsEnvironment, String user, Configuration configuration, Path path, long start, long length, long fileSize, List<DeltaColumnHandle> columns, SchemaTableName tableName, DataSize maxReadBlockSize, boolean batchReaderEnabled, boolean verificationEnabled, TypeManager typeManager, TupleDomain<DeltaColumnHandle> effectivePredicate, FileFormatDataSourceStats stats, boolean columnIndexFilterEnabled) {
    AggregatedMemoryContext systemMemoryContext = newSimpleAggregatedMemoryContext();
    ParquetDataSource dataSource = null;
    try {
        FSDataInputStream inputStream = hdfsEnvironment.getFileSystem(user, path, configuration).open(path);
        dataSource = buildHdfsParquetDataSource(inputStream, path, stats);
        ParquetMetadata parquetMetadata = MetadataReader.readFooter(dataSource, fileSize).getParquetMetadata();
        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.getDataType()), fileSchema, 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));
            }
        }
        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 (DeltaColumnHandle column : columns) {
            checkArgument(column.getColumnType() == REGULAR || column.getColumnType() == SUBFIELD, "column type must be regular or subfield column");
            String name = column.getName();
            Type type = typeManager.getType(column.getDataType());
            namesBuilder.add(name);
            typesBuilder.add(type);
            if (isPushedDownSubfield(column)) {
                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, column, tableName, path).isPresent()) {
                fieldsBuilder.add(constructField(type, lookupColumnByName(messageColumnIO, name)));
            } else {
                fieldsBuilder.add(Optional.empty());
            }
        }
        return new ParquetPageSource(parquetReader, typesBuilder.build(), fieldsBuilder.build(), namesBuilder.build(), new RuntimeStats());
    } catch (Exception exception) {
        try {
            if (dataSource != null) {
                dataSource.close();
            }
        } catch (IOException ignored) {
        }
        if (exception instanceof PrestoException) {
            throw (PrestoException) exception;
        }
        if (exception instanceof ParquetCorruptionException) {
            throw new PrestoException(DELTA_BAD_DATA, exception);
        }
        if (exception instanceof AccessControlException) {
            throw new PrestoException(PERMISSION_DENIED, exception.getMessage(), exception);
        }
        if (nullToEmpty(exception.getMessage()).trim().equals("Filesystem closed") || exception instanceof FileNotFoundException) {
            throw new PrestoException(DELTA_CANNOT_OPEN_SPLIT, exception);
        }
        String message = format("Error opening Hive split %s (offset=%s, length=%s): %s", path, start, length, exception.getMessage());
        if (exception.getClass().getSimpleName().equals("BlockMissingException")) {
            throw new PrestoException(DELTA_MISSING_DATA, message, exception);
        }
        throw new PrestoException(DELTA_CANNOT_OPEN_SPLIT, message, exception);
    }
}

Example 2 with FileFormatDataSourceStats

use of com.facebook.presto.hive.FileFormatDataSourceStats in project presto by prestodb.

the class IcebergPageSourceProvider method createParquetPageSource.

private static ConnectorPageSource createParquetPageSource(HdfsEnvironment hdfsEnvironment, String user, Configuration configuration, Path path, long start, long length, SchemaTableName tableName, List<IcebergColumnHandle> regularColumns, boolean useParquetColumnNames, DataSize maxReadBlockSize, boolean batchReaderEnabled, boolean verificationEnabled, TupleDomain<IcebergColumnHandle> effectivePredicate, FileFormatDataSourceStats fileFormatDataSourceStats, boolean columnIndexFilterEnabled) {
    AggregatedMemoryContext systemMemoryContext = newSimpleAggregatedMemoryContext();
    ParquetDataSource dataSource = null;
    try {
        ExtendedFileSystem fileSystem = hdfsEnvironment.getFileSystem(user, path, configuration);
        FileStatus fileStatus = fileSystem.getFileStatus(path);
        long fileSize = fileStatus.getLen();
        long modificationTime = fileStatus.getModificationTime();
        HiveFileContext hiveFileContext = new HiveFileContext(true, NO_CACHE_CONSTRAINTS, Optional.empty(), Optional.of(fileSize), modificationTime, false);
        FSDataInputStream inputStream = fileSystem.openFile(path, hiveFileContext);
        dataSource = buildHdfsParquetDataSource(inputStream, path, fileFormatDataSourceStats);
        ParquetMetadata parquetMetadata = MetadataReader.readFooter(dataSource, fileSize).getParquetMetadata();
        FileMetaData fileMetaData = parquetMetadata.getFileMetaData();
        MessageType fileSchema = fileMetaData.getSchema();
        // 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()));
        List<org.apache.parquet.schema.Type> parquetFields = regularColumns.stream().map(column -> {
            if (parquetIdToField.isEmpty()) {
                // This is a migrated table
                return getParquetTypeByName(column.getName(), fileSchema);
            }
            return parquetIdToField.get(column.getId());
        }).collect(toList());
        // TODO: support subfield pushdown
        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);
        final ParquetDataSource finalDataSource = dataSource;
        List<BlockMetaData> blocks = new ArrayList<>();
        List<ColumnIndexStore> blockIndexStores = new ArrayList<>();
        for (BlockMetaData block : parquetMetadata.getBlocks()) {
            long firstDataPage = block.getColumns().get(0).getFirstDataPageOffset();
            Optional<ColumnIndexStore> columnIndexStore = ColumnIndexFilterUtils.getColumnIndexStore(parquetPredicate, finalDataSource, block, descriptorsByPath, columnIndexFilterEnabled);
            if ((firstDataPage >= start) && (firstDataPage < (start + length)) && predicateMatches(parquetPredicate, block, dataSource, descriptorsByPath, parquetTupleDomain, columnIndexStore, columnIndexFilterEnabled)) {
                blocks.add(block);
                blockIndexStores.add(columnIndexStore.orElse(null));
            }
        }
        MessageColumnIO messageColumnIO = getColumnIO(fileSchema, requestedSchema);
        ParquetReader parquetReader = new ParquetReader(messageColumnIO, blocks, dataSource, systemMemoryContext, maxReadBlockSize, batchReaderEnabled, verificationEnabled, parquetPredicate, blockIndexStores, columnIndexFilterEnabled);
        ImmutableList.Builder<String> namesBuilder = ImmutableList.builder();
        ImmutableList.Builder<Type> prestoTypes = ImmutableList.builder();
        ImmutableList.Builder<Optional<Field>> internalFields = ImmutableList.builder();
        for (int columnIndex = 0; columnIndex < regularColumns.size(); columnIndex++) {
            IcebergColumnHandle column = regularColumns.get(columnIndex);
            namesBuilder.add(column.getName());
            org.apache.parquet.schema.Type parquetField = parquetFields.get(columnIndex);
            Type prestoType = column.getType();
            prestoTypes.add(prestoType);
            if (parquetField == null) {
                internalFields.add(Optional.empty());
            } else {
                internalFields.add(constructField(column.getType(), messageColumnIO.getChild(parquetField.getName())));
            }
        }
        return new ParquetPageSource(parquetReader, prestoTypes.build(), internalFields.build(), namesBuilder.build(), new RuntimeStats());
    } catch (Exception e) {
        try {
            if (dataSource != null) {
                dataSource.close();
            }
        } catch (IOException ignored) {
        }
        if (e instanceof PrestoException) {
            throw (PrestoException) 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 PrestoException(ICEBERG_BAD_DATA, message, e);
        }
        if (e instanceof BlockMissingException) {
            throw new PrestoException(ICEBERG_MISSING_DATA, message, e);
        }
        throw new PrestoException(ICEBERG_CANNOT_OPEN_SPLIT, message, e);
    }
}

Example 3 with FileFormatDataSourceStats

use of com.facebook.presto.hive.FileFormatDataSourceStats 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);
    }
}

Example 4 with FileFormatDataSourceStats

use of com.facebook.presto.hive.FileFormatDataSourceStats in project presto by prestodb.

the class OrcBatchPageSourceFactory method createOrcPageSource.

public static ConnectorPageSource createOrcPageSource(OrcEncoding orcEncoding, HdfsEnvironment hdfsEnvironment, String sessionUser, Configuration configuration, Path path, long start, long length, long fileSize, List<HiveColumnHandle> columns, boolean useOrcColumnNames, TupleDomain<HiveColumnHandle> effectivePredicate, DateTimeZone hiveStorageTimeZone, TypeManager typeManager, StandardFunctionResolution functionResolution, DataSize maxBufferSize, DataSize streamBufferSize, boolean lazyReadSmallRanges, boolean orcBloomFiltersEnabled, FileFormatDataSourceStats stats, int domainCompactionThreshold, OrcFileTailSource orcFileTailSource, StripeMetadataSourceFactory stripeMetadataSourceFactory, HiveFileContext hiveFileContext, OrcReaderOptions orcReaderOptions, Optional<EncryptionInformation> encryptionInformation, DwrfEncryptionProvider dwrfEncryptionProvider) {
    checkArgument(domainCompactionThreshold >= 1, "domainCompactionThreshold must be at least 1");
    OrcDataSource orcDataSource;
    try {
        FSDataInputStream inputStream = hdfsEnvironment.getFileSystem(sessionUser, path, configuration).openFile(path, hiveFileContext);
        orcDataSource = new HdfsOrcDataSource(new OrcDataSourceId(path.toString()), fileSize, orcReaderOptions.getMaxMergeDistance(), maxBufferSize, streamBufferSize, lazyReadSmallRanges, inputStream, stats);
    } catch (Exception e) {
        if (nullToEmpty(e.getMessage()).trim().equals("Filesystem closed") || e instanceof FileNotFoundException) {
            throw new PrestoException(HIVE_CANNOT_OPEN_SPLIT, e);
        }
        throw new PrestoException(HIVE_CANNOT_OPEN_SPLIT, splitError(e, path, start, length), e);
    }
    OrcAggregatedMemoryContext systemMemoryUsage = new HiveOrcAggregatedMemoryContext();
    try {
        DwrfKeyProvider dwrfKeyProvider = new ProjectionBasedDwrfKeyProvider(encryptionInformation, columns, useOrcColumnNames, path);
        OrcReader reader = new OrcReader(orcDataSource, orcEncoding, orcFileTailSource, stripeMetadataSourceFactory, new HiveOrcAggregatedMemoryContext(), orcReaderOptions, hiveFileContext.isCacheable(), dwrfEncryptionProvider, dwrfKeyProvider, hiveFileContext.getStats());
        List<HiveColumnHandle> physicalColumns = getPhysicalHiveColumnHandles(columns, useOrcColumnNames, reader.getTypes(), path);
        ImmutableMap.Builder<Integer, Type> includedColumns = ImmutableMap.builder();
        ImmutableList.Builder<ColumnReference<HiveColumnHandle>> columnReferences = ImmutableList.builder();
        for (HiveColumnHandle column : physicalColumns) {
            if (column.getColumnType() == REGULAR) {
                Type type = typeManager.getType(column.getTypeSignature());
                includedColumns.put(column.getHiveColumnIndex(), type);
                columnReferences.add(new ColumnReference<>(column, column.getHiveColumnIndex(), type));
            }
        }
        if (!physicalColumns.isEmpty() && physicalColumns.stream().allMatch(hiveColumnHandle -> hiveColumnHandle.getColumnType() == AGGREGATED)) {
            return new AggregatedOrcPageSource(physicalColumns, reader.getFooter(), typeManager, functionResolution);
        }
        OrcPredicate predicate = new TupleDomainOrcPredicate<>(effectivePredicate, columnReferences.build(), orcBloomFiltersEnabled, Optional.of(domainCompactionThreshold));
        OrcBatchRecordReader recordReader = reader.createBatchRecordReader(includedColumns.build(), predicate, start, length, hiveStorageTimeZone, systemMemoryUsage, INITIAL_BATCH_SIZE);
        return new OrcBatchPageSource(recordReader, reader.getOrcDataSource(), physicalColumns, typeManager, systemMemoryUsage, stats, hiveFileContext.getStats());
    } catch (Exception e) {
        try {
            orcDataSource.close();
        } catch (IOException ignored) {
        }
        if (e instanceof PrestoException) {
            throw (PrestoException) e;
        }
        String message = splitError(e, path, start, length);
        if (e.getClass().getSimpleName().equals("BlockMissingException")) {
            throw new PrestoException(HIVE_MISSING_DATA, message, e);
        }
        throw new PrestoException(HIVE_CANNOT_OPEN_SPLIT, message, e);
    }
}

Example 5 with FileFormatDataSourceStats

use of com.facebook.presto.hive.FileFormatDataSourceStats in project presto by prestodb.

the class IcebergPageSourceProvider method createBatchOrcPageSource.

private static ConnectorPageSource createBatchOrcPageSource(HdfsEnvironment hdfsEnvironment, String user, Configuration configuration, Path path, long start, long length, boolean isCacheable, List<IcebergColumnHandle> regularColumns, TypeManager typeManager, TupleDomain<IcebergColumnHandle> effectivePredicate, OrcReaderOptions options, OrcEncoding orcEncoding, DataSize maxBufferSize, DataSize streamBufferSize, boolean lazyReadSmallRanges, boolean orcBloomFiltersEnabled, int domainCompactionThreshold, OrcFileTailSource orcFileTailSource, StripeMetadataSourceFactory stripeMetadataSourceFactory, FileFormatDataSourceStats stats, Optional<EncryptionInformation> encryptionInformation, DwrfEncryptionProvider dwrfEncryptionProvider) {
    OrcDataSource orcDataSource = null;
    try {
        ExtendedFileSystem fileSystem = hdfsEnvironment.getFileSystem(user, path, configuration);
        FileStatus fileStatus = fileSystem.getFileStatus(path);
        long fileSize = fileStatus.getLen();
        long modificationTime = fileStatus.getModificationTime();
        HiveFileContext hiveFileContext = new HiveFileContext(true, NO_CACHE_CONSTRAINTS, Optional.empty(), Optional.of(fileSize), modificationTime, false);
        FSDataInputStream inputStream = hdfsEnvironment.doAs(user, () -> fileSystem.openFile(path, hiveFileContext));
        orcDataSource = new HdfsOrcDataSource(new OrcDataSourceId(path.toString()), fileSize, options.getMaxMergeDistance(), maxBufferSize, streamBufferSize, lazyReadSmallRanges, inputStream, stats);
        // Todo: pass real columns to ProjectionBasedDwrfKeyProvider instead of ImmutableList.of()
        DwrfKeyProvider dwrfKeyProvider = new ProjectionBasedDwrfKeyProvider(encryptionInformation, ImmutableList.of(), true, path);
        RuntimeStats runtimeStats = new RuntimeStats();
        OrcReader reader = new OrcReader(orcDataSource, orcEncoding, orcFileTailSource, stripeMetadataSourceFactory, new HiveOrcAggregatedMemoryContext(), options, isCacheable, dwrfEncryptionProvider, dwrfKeyProvider, runtimeStats);
        List<HiveColumnHandle> physicalColumnHandles = new ArrayList<>(regularColumns.size());
        ImmutableMap.Builder<Integer, Type> includedColumns = ImmutableMap.builder();
        ImmutableList.Builder<TupleDomainOrcPredicate.ColumnReference<HiveColumnHandle>> columnReferences = ImmutableList.builder();
        List<IcebergOrcColumn> fileOrcColumns = getFileOrcColumns(reader);
        Map<Integer, IcebergOrcColumn> fileOrcColumnByIcebergId = fileOrcColumns.stream().filter(orcColumn -> orcColumn.getAttributes().containsKey(ORC_ICEBERG_ID_KEY)).collect(toImmutableMap(orcColumn -> Integer.parseInt(orcColumn.getAttributes().get(ORC_ICEBERG_ID_KEY)), orcColumn -> IcebergOrcColumn.copy(orcColumn).setIcebergColumnId(Optional.of(Integer.parseInt(orcColumn.getAttributes().get(ORC_ICEBERG_ID_KEY))))));
        Map<String, IcebergOrcColumn> fileOrcColumnsByName = uniqueIndex(fileOrcColumns, orcColumn -> orcColumn.getColumnName().toLowerCase(ENGLISH));
        int nextMissingColumnIndex = fileOrcColumnsByName.size();
        for (IcebergColumnHandle column : regularColumns) {
            IcebergOrcColumn icebergOrcColumn;
            boolean isExcludeColumn = false;
            if (fileOrcColumnByIcebergId.isEmpty()) {
                icebergOrcColumn = fileOrcColumnsByName.get(column.getName());
            } else {
                icebergOrcColumn = fileOrcColumnByIcebergId.get(column.getId());
                if (icebergOrcColumn == null) {
                    // Cannot get orc column from 'fileOrcColumnByIcebergId', which means SchemaEvolution may have happened, so we get orc column by column name.
                    icebergOrcColumn = fileOrcColumnsByName.get(column.getName());
                    if (icebergOrcColumn != null) {
                        isExcludeColumn = true;
                    }
                }
            }
            if (icebergOrcColumn != null) {
                HiveColumnHandle columnHandle = new HiveColumnHandle(// Todo: using orc file column name
                column.getName(), toHiveType(column.getType()), column.getType().getTypeSignature(), icebergOrcColumn.getOrcColumnId(), icebergOrcColumn.getColumnType(), Optional.empty(), Optional.empty());
                physicalColumnHandles.add(columnHandle);
                // Skip SchemaEvolution column
                if (!isExcludeColumn) {
                    includedColumns.put(columnHandle.getHiveColumnIndex(), typeManager.getType(columnHandle.getTypeSignature()));
                    columnReferences.add(new TupleDomainOrcPredicate.ColumnReference<>(columnHandle, columnHandle.getHiveColumnIndex(), typeManager.getType(columnHandle.getTypeSignature())));
                }
            } else {
                physicalColumnHandles.add(new HiveColumnHandle(column.getName(), toHiveType(column.getType()), column.getType().getTypeSignature(), nextMissingColumnIndex++, REGULAR, Optional.empty(), Optional.empty()));
            }
        }
        TupleDomain<HiveColumnHandle> hiveColumnHandleTupleDomain = effectivePredicate.transform(column -> {
            IcebergOrcColumn icebergOrcColumn;
            if (fileOrcColumnByIcebergId.isEmpty()) {
                icebergOrcColumn = fileOrcColumnsByName.get(column.getName());
            } else {
                icebergOrcColumn = fileOrcColumnByIcebergId.get(column.getId());
                if (icebergOrcColumn == null) {
                    // Cannot get orc column from 'fileOrcColumnByIcebergId', which means SchemaEvolution may have happened, so we get orc column by column name.
                    icebergOrcColumn = fileOrcColumnsByName.get(column.getName());
                }
            }
            return new HiveColumnHandle(column.getName(), toHiveType(column.getType()), column.getType().getTypeSignature(), // Note: the HiveColumnHandle.hiveColumnIndex starts from '0' while the IcebergColumnHandle.id starts from '1'
            icebergOrcColumn != null ? icebergOrcColumn.getOrcColumnId() : column.getId() - 1, icebergOrcColumn != null ? icebergOrcColumn.getColumnType() : REGULAR, Optional.empty(), Optional.empty());
        });
        OrcPredicate predicate = new TupleDomainOrcPredicate<>(hiveColumnHandleTupleDomain, columnReferences.build(), orcBloomFiltersEnabled, Optional.of(domainCompactionThreshold));
        OrcAggregatedMemoryContext systemMemoryUsage = new HiveOrcAggregatedMemoryContext();
        OrcBatchRecordReader recordReader = reader.createBatchRecordReader(includedColumns.build(), predicate, start, length, UTC, systemMemoryUsage, INITIAL_BATCH_SIZE);
        return new OrcBatchPageSource(recordReader, orcDataSource, physicalColumnHandles, typeManager, systemMemoryUsage, stats, runtimeStats);
    } catch (Exception e) {
        if (orcDataSource != null) {
            try {
                orcDataSource.close();
            } catch (IOException ignored) {
            }
        }
        if (e instanceof PrestoException) {
            throw (PrestoException) e;
        }
        String message = format("Error opening Iceberg split %s (offset=%s, length=%s): %s", path, start, length, e.getMessage());
        if (e instanceof BlockMissingException) {
            throw new PrestoException(ICEBERG_MISSING_DATA, message, e);
        }
        throw new PrestoException(ICEBERG_CANNOT_OPEN_SPLIT, message, e);
    }
}