Examples with HiveDefaultReader org.apache.drill.exec.store.hive.readers.HiveDefaultReader used on opensource projects

Example 1 with HiveDefaultReader

use of org.apache.drill.exec.store.hive.readers.HiveDefaultReader in project drill by axbaretto.

the class HiveDrillNativeScanBatchCreator method getBatch.

@Override
public ScanBatch getBatch(ExecutorFragmentContext context, HiveDrillNativeParquetSubScan config, List<RecordBatch> children) throws ExecutionSetupException {
    final HiveTableWithColumnCache table = config.getTable();
    final List<List<InputSplit>> splits = config.getInputSplits();
    final List<HivePartition> partitions = config.getPartitions();
    final List<SchemaPath> columns = config.getColumns();
    final String partitionDesignator = context.getOptions().getOption(ExecConstants.FILESYSTEM_PARTITION_COLUMN_LABEL).string_val;
    List<Map<String, String>> implicitColumns = Lists.newLinkedList();
    boolean selectAllQuery = Utilities.isStarQuery(columns);
    final boolean hasPartitions = (partitions != null && partitions.size() > 0);
    final List<String[]> partitionColumns = Lists.newArrayList();
    final List<Integer> selectedPartitionColumns = Lists.newArrayList();
    List<SchemaPath> tableColumns = columns;
    if (!selectAllQuery) {
        // Separate out the partition and non-partition columns. Non-partition columns are passed directly to the
        // ParquetRecordReader. Partition columns are passed to ScanBatch.
        tableColumns = Lists.newArrayList();
        Pattern pattern = Pattern.compile(String.format("%s[0-9]+", partitionDesignator));
        for (SchemaPath column : columns) {
            Matcher m = pattern.matcher(column.getRootSegmentPath());
            if (m.matches()) {
                selectedPartitionColumns.add(Integer.parseInt(column.getRootSegmentPath().substring(partitionDesignator.length())));
            } else {
                tableColumns.add(column);
            }
        }
    }
    final OperatorContext oContext = context.newOperatorContext(config);
    int currentPartitionIndex = 0;
    final List<RecordReader> readers = new LinkedList<>();
    final HiveConf conf = config.getHiveConf();
    // TODO: In future we can get this cache from Metadata cached on filesystem.
    final Map<String, ParquetMetadata> footerCache = Maps.newHashMap();
    Map<String, String> mapWithMaxColumns = Maps.newLinkedHashMap();
    try {
        for (List<InputSplit> splitGroups : splits) {
            for (InputSplit split : splitGroups) {
                final FileSplit fileSplit = (FileSplit) split;
                final Path finalPath = fileSplit.getPath();
                final JobConf cloneJob = new ProjectionPusher().pushProjectionsAndFilters(new JobConf(conf), finalPath.getParent());
                final FileSystem fs = finalPath.getFileSystem(cloneJob);
                ParquetMetadata parquetMetadata = footerCache.get(finalPath.toString());
                if (parquetMetadata == null) {
                    parquetMetadata = ParquetFileReader.readFooter(cloneJob, finalPath);
                    footerCache.put(finalPath.toString(), parquetMetadata);
                }
                final List<Integer> rowGroupNums = getRowGroupNumbersFromFileSplit(fileSplit, parquetMetadata);
                for (int rowGroupNum : rowGroupNums) {
                    // DRILL-5009 : Skip the row group if the row count is zero
                    if (parquetMetadata.getBlocks().get(rowGroupNum).getRowCount() == 0) {
                        continue;
                    }
                    // Drill has only ever written a single row group per file, only detect corruption
                    // in the first row group
                    ParquetReaderUtility.DateCorruptionStatus containsCorruptDates = ParquetReaderUtility.detectCorruptDates(parquetMetadata, config.getColumns(), true);
                    if (logger.isDebugEnabled()) {
                        logger.debug(containsCorruptDates.toString());
                    }
                    readers.add(new ParquetRecordReader(context, Path.getPathWithoutSchemeAndAuthority(finalPath).toString(), rowGroupNum, fs, CodecFactory.createDirectCodecFactory(fs.getConf(), new ParquetDirectByteBufferAllocator(oContext.getAllocator()), 0), parquetMetadata, tableColumns, containsCorruptDates));
                    Map<String, String> implicitValues = Maps.newLinkedHashMap();
                    if (hasPartitions) {
                        List<String> values = partitions.get(currentPartitionIndex).getValues();
                        for (int i = 0; i < values.size(); i++) {
                            if (selectAllQuery || selectedPartitionColumns.contains(i)) {
                                implicitValues.put(partitionDesignator + i, values.get(i));
                            }
                        }
                    }
                    implicitColumns.add(implicitValues);
                    if (implicitValues.size() > mapWithMaxColumns.size()) {
                        mapWithMaxColumns = implicitValues;
                    }
                }
                currentPartitionIndex++;
            }
        }
    } catch (final IOException | RuntimeException e) {
        AutoCloseables.close(e, readers);
        throw new ExecutionSetupException("Failed to create RecordReaders. " + e.getMessage(), e);
    }
    // all readers should have the same number of implicit columns, add missing ones with value null
    mapWithMaxColumns = Maps.transformValues(mapWithMaxColumns, Functions.constant((String) null));
    for (Map<String, String> map : implicitColumns) {
        map.putAll(Maps.difference(map, mapWithMaxColumns).entriesOnlyOnRight());
    }
    // create an empty RecordReader to output the schema
    if (readers.size() == 0) {
        readers.add(new HiveDefaultReader(table, null, null, tableColumns, context, conf, ImpersonationUtil.createProxyUgi(config.getUserName(), context.getQueryUserName())));
    }
    return new ScanBatch(context, oContext, readers, implicitColumns);
}