Examples with NO_CACHE_CONSTRAINTS com.facebook.presto.hive.CacheQuota.NO_CACHE_CONSTRAINTS used on opensource projects

Example 1 with NO_CACHE_CONSTRAINTS

use of com.facebook.presto.hive.CacheQuota.NO_CACHE_CONSTRAINTS 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 2 with NO_CACHE_CONSTRAINTS

use of com.facebook.presto.hive.CacheQuota.NO_CACHE_CONSTRAINTS 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);
    }
}