Examples with ICEBERG_MISSING_DATA io.trino.plugin.iceberg.IcebergErrorCode.ICEBERG_MISSING_DATA used on opensource projects

Example 1 with ICEBERG_MISSING_DATA

use of io.trino.plugin.iceberg.IcebergErrorCode.ICEBERG_MISSING_DATA 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 2 with ICEBERG_MISSING_DATA

use of io.trino.plugin.iceberg.IcebergErrorCode.ICEBERG_MISSING_DATA in project trino by trinodb.

the class IcebergPageSourceProvider method createOrcPageSource.

private static ReaderPageSource createOrcPageSource(HdfsEnvironment hdfsEnvironment, ConnectorIdentity identity, Configuration configuration, Path path, long start, long length, long fileSize, List<IcebergColumnHandle> columns, TupleDomain<IcebergColumnHandle> effectivePredicate, OrcReaderOptions options, FileFormatDataSourceStats stats, TypeManager typeManager, Optional<NameMapping> nameMapping) {
    OrcDataSource orcDataSource = null;
    try {
        FileSystem fileSystem = hdfsEnvironment.getFileSystem(identity, path, configuration);
        FSDataInputStream inputStream = hdfsEnvironment.doAs(identity, () -> fileSystem.open(path));
        orcDataSource = new HdfsOrcDataSource(new OrcDataSourceId(path.toString()), fileSize, options, inputStream, stats);
        OrcReader reader = OrcReader.createOrcReader(orcDataSource, options).orElseThrow(() -> new TrinoException(ICEBERG_BAD_DATA, "ORC file is zero length"));
        List<OrcColumn> fileColumns = reader.getRootColumn().getNestedColumns();
        if (nameMapping.isPresent() && !hasIds(reader.getRootColumn())) {
            fileColumns = fileColumns.stream().map(orcColumn -> setMissingFieldIds(orcColumn, nameMapping.get(), ImmutableList.of(orcColumn.getColumnName()))).collect(toImmutableList());
        }
        Map<Integer, OrcColumn> fileColumnsByIcebergId = mapIdsToOrcFileColumns(fileColumns);
        TupleDomainOrcPredicateBuilder predicateBuilder = TupleDomainOrcPredicate.builder().setBloomFiltersEnabled(options.isBloomFiltersEnabled());
        Map<IcebergColumnHandle, Domain> effectivePredicateDomains = effectivePredicate.getDomains().orElseThrow(() -> new IllegalArgumentException("Effective predicate is none"));
        Optional<ReaderColumns> columnProjections = projectColumns(columns);
        Map<Integer, List<List<Integer>>> projectionsByFieldId = columns.stream().collect(groupingBy(column -> column.getBaseColumnIdentity().getId(), mapping(IcebergColumnHandle::getPath, toUnmodifiableList())));
        List<IcebergColumnHandle> readColumns = columnProjections.map(readerColumns -> (List<IcebergColumnHandle>) readerColumns.get().stream().map(IcebergColumnHandle.class::cast).collect(toImmutableList())).orElse(columns);
        List<OrcColumn> fileReadColumns = new ArrayList<>(readColumns.size());
        List<Type> fileReadTypes = new ArrayList<>(readColumns.size());
        List<ProjectedLayout> projectedLayouts = new ArrayList<>(readColumns.size());
        List<ColumnAdaptation> columnAdaptations = new ArrayList<>(readColumns.size());
        for (IcebergColumnHandle column : readColumns) {
            verify(column.isBaseColumn(), "Column projections must be based from a root column");
            OrcColumn orcColumn = fileColumnsByIcebergId.get(column.getId());
            if (orcColumn != null) {
                Type readType = getOrcReadType(column.getType(), typeManager);
                if (column.getType() == UUID && !"UUID".equals(orcColumn.getAttributes().get(ICEBERG_BINARY_TYPE))) {
                    throw new TrinoException(ICEBERG_BAD_DATA, format("Expected ORC column for UUID data to be annotated with %s=UUID: %s", ICEBERG_BINARY_TYPE, orcColumn));
                }
                List<List<Integer>> fieldIdProjections = projectionsByFieldId.get(column.getId());
                ProjectedLayout projectedLayout = IcebergOrcProjectedLayout.createProjectedLayout(orcColumn, fieldIdProjections);
                int sourceIndex = fileReadColumns.size();
                columnAdaptations.add(ColumnAdaptation.sourceColumn(sourceIndex));
                fileReadColumns.add(orcColumn);
                fileReadTypes.add(readType);
                projectedLayouts.add(projectedLayout);
                for (Map.Entry<IcebergColumnHandle, Domain> domainEntry : effectivePredicateDomains.entrySet()) {
                    IcebergColumnHandle predicateColumn = domainEntry.getKey();
                    OrcColumn predicateOrcColumn = fileColumnsByIcebergId.get(predicateColumn.getId());
                    if (predicateOrcColumn != null && column.getColumnIdentity().equals(predicateColumn.getBaseColumnIdentity())) {
                        predicateBuilder.addColumn(predicateOrcColumn.getColumnId(), domainEntry.getValue());
                    }
                }
            } else {
                columnAdaptations.add(ColumnAdaptation.nullColumn(column.getType()));
            }
        }
        AggregatedMemoryContext memoryUsage = newSimpleAggregatedMemoryContext();
        OrcDataSourceId orcDataSourceId = orcDataSource.getId();
        OrcRecordReader recordReader = reader.createRecordReader(fileReadColumns, fileReadTypes, projectedLayouts, predicateBuilder.build(), start, length, UTC, memoryUsage, INITIAL_BATCH_SIZE, exception -> handleException(orcDataSourceId, exception), new IdBasedFieldMapperFactory(readColumns));
        return new ReaderPageSource(new OrcPageSource(recordReader, columnAdaptations, orcDataSource, Optional.empty(), Optional.empty(), memoryUsage, stats), columnProjections);
    } catch (Exception e) {
        if (orcDataSource != null) {
            try {
                orcDataSource.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 BlockMissingException) {
            throw new TrinoException(ICEBERG_MISSING_DATA, message, e);
        }
        throw new TrinoException(ICEBERG_CANNOT_OPEN_SPLIT, message, e);
    }
}