Examples with TypeInfoFactory.getStructTypeInfo org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory.getStructTypeInfo used on opensource projects

Example 1 with TypeInfoFactory.getStructTypeInfo

use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory.getStructTypeInfo in project hive by apache.

the class TestParquetRowGroupFilter method getObjectInspector.

private ArrayWritableObjectInspector getObjectInspector(final String columnNames, final String columnTypes) {
    List<TypeInfo> columnTypeList = createHiveTypeInfoFrom(columnTypes);
    List<String> columnNameList = createHiveColumnsFrom(columnNames);
    StructTypeInfo rowTypeInfo = (StructTypeInfo) TypeInfoFactory.getStructTypeInfo(columnNameList, columnTypeList);
    return new ArrayWritableObjectInspector(rowTypeInfo);
}

Example 2 with TypeInfoFactory.getStructTypeInfo

use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory.getStructTypeInfo in project hive by apache.

the class TestDataWritableWriter method getObjectInspector.

private ArrayWritableObjectInspector getObjectInspector(final String columnNames, final String columnTypes) {
    List<TypeInfo> columnTypeList = createHiveTypeInfoFrom(columnTypes);
    List<String> columnNameList = createHiveColumnsFrom(columnNames);
    StructTypeInfo rowTypeInfo = (StructTypeInfo) TypeInfoFactory.getStructTypeInfo(columnNameList, columnTypeList);
    return new ArrayWritableObjectInspector(rowTypeInfo);
}

Example 3 with TypeInfoFactory.getStructTypeInfo

use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory.getStructTypeInfo in project hive by apache.

the class TestColumnPrunerProcCtx method setup.

@BeforeClass
public static void setup() {
    List<String> ns = new ArrayList<>();
    ns.add("a");
    ns.add("b");
    List<TypeInfo> tis = new ArrayList<>();
    TypeInfo aType = TypeInfoFactory.booleanTypeInfo;
    TypeInfo bType = TypeInfoFactory.doubleTypeInfo;
    tis.add(aType);
    tis.add(bType);
    col1Type = TypeInfoFactory.getStructTypeInfo(ns, tis);
    col2Type = TypeInfoFactory.doubleTypeInfo;
    List<String> names = new ArrayList<>();
    names.add("col1");
    names.add("col2");
    List<TypeInfo> typeInfos = new ArrayList<>();
    typeInfos.add(col1Type);
    typeInfos.add(col2Type);
    col3Type = TypeInfoFactory.getStructTypeInfo(names, typeInfos);
}

Example 4 with TypeInfoFactory.getStructTypeInfo

use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory.getStructTypeInfo in project hive by apache.

the class TestAccumuloSerDe method testStructOfMapSerialization.

@Test
public void testStructOfMapSerialization() throws IOException, SerDeException {
    List<String> columns = Arrays.asList("row", "col");
    List<String> structColNames = Arrays.asList("map1", "map2");
    TypeInfo mapTypeInfo = TypeInfoFactory.getMapTypeInfo(TypeInfoFactory.stringTypeInfo, TypeInfoFactory.stringTypeInfo);
    // struct<map1:map<string,string>,map2:map<string,string>>,string
    List<TypeInfo> types = Arrays.<TypeInfo>asList(TypeInfoFactory.getStructTypeInfo(structColNames, Arrays.asList(mapTypeInfo, mapTypeInfo)), TypeInfoFactory.stringTypeInfo);
    Properties tableProperties = new Properties();
    tableProperties.setProperty(AccumuloSerDeParameters.COLUMN_MAPPINGS, ":rowid,cf:cq");
    // Use the default separators [0, 1, 2, 3, ..., 7]
    tableProperties.setProperty(serdeConstants.LIST_COLUMNS, Joiner.on(',').join(columns));
    tableProperties.setProperty(serdeConstants.LIST_COLUMN_TYPES, Joiner.on(',').join(types));
    AccumuloSerDeParameters accumuloSerDeParams = new AccumuloSerDeParameters(new Configuration(), tableProperties, AccumuloSerDe.class.getSimpleName());
    LazySerDeParameters serDeParams = accumuloSerDeParams.getSerDeParameters();
    byte[] seps = serDeParams.getSeparators();
    // struct<map<k:v,k:v>_map<k:v,k:v>>>
    TypeInfo stringTypeInfo = TypeInfoFactory.getPrimitiveTypeInfo(serdeConstants.STRING_TYPE_NAME);
    LazyStringObjectInspector stringOI = (LazyStringObjectInspector) LazyFactory.createLazyObjectInspector(stringTypeInfo, new byte[] { 0 }, 0, serDeParams.getNullSequence(), serDeParams.isEscaped(), serDeParams.getEscapeChar());
    LazyMapObjectInspector mapOI = LazyObjectInspectorFactory.getLazySimpleMapObjectInspector(stringOI, stringOI, seps[3], seps[4], serDeParams.getNullSequence(), serDeParams.isEscaped(), serDeParams.getEscapeChar());
    LazySimpleStructObjectInspector rowStructOI = (LazySimpleStructObjectInspector) LazyObjectInspectorFactory.getLazySimpleStructObjectInspector(structColNames, Arrays.<ObjectInspector>asList(mapOI, mapOI), (byte) seps[2], serDeParams.getNullSequence(), serDeParams.isLastColumnTakesRest(), serDeParams.isEscaped(), serDeParams.getEscapeChar());
    LazySimpleStructObjectInspector structOI = (LazySimpleStructObjectInspector) LazyObjectInspectorFactory.getLazySimpleStructObjectInspector(columns, Arrays.asList(rowStructOI, stringOI), seps[1], serDeParams.getNullSequence(), serDeParams.isLastColumnTakesRest(), serDeParams.isEscaped(), serDeParams.getEscapeChar());
    AccumuloRowSerializer serializer = new AccumuloRowSerializer(0, serDeParams, accumuloSerDeParams.getColumnMappings(), new ColumnVisibility(), accumuloSerDeParams.getRowIdFactory());
    Map<String, String> map1 = new HashMap<String, String>(), map2 = new HashMap<String, String>();
    map1.put("key10", "value10");
    map1.put("key11", "value11");
    map2.put("key20", "value20");
    map2.put("key21", "value21");
    ByteArrayRef byteRef = new ByteArrayRef();
    // Default separators are 1-indexed (instead of 0-indexed), thus the separator at offset 1 is
    // (byte) 2
    // The separator for the hive row is \x02, for the row Id struct, \x03, and the maps \x04 and
    // \x05
    String accumuloRow = "key10\5value10\4key11\5value11\3key20\5value20\4key21\5value21";
    LazyStruct entireStruct = (LazyStruct) LazyFactory.createLazyObject(structOI);
    byteRef.setData((accumuloRow + "\2foo").getBytes());
    entireStruct.init(byteRef, 0, byteRef.getData().length);
    Mutation m = serializer.serialize(entireStruct, structOI);
    Assert.assertArrayEquals(accumuloRow.getBytes(), m.getRow());
    Assert.assertEquals(1, m.getUpdates().size());
    ColumnUpdate update = m.getUpdates().get(0);
    Assert.assertEquals("cf", new String(update.getColumnFamily()));
    Assert.assertEquals("cq", new String(update.getColumnQualifier()));
    Assert.assertEquals("foo", new String(update.getValue()));
    AccumuloHiveRow haRow = new AccumuloHiveRow(new String(m.getRow()));
    haRow.add("cf", "cq", "foo".getBytes());
    LazyAccumuloRow lazyAccumuloRow = new LazyAccumuloRow(structOI);
    lazyAccumuloRow.init(haRow, accumuloSerDeParams.getColumnMappings(), accumuloSerDeParams.getRowIdFactory());
    List<Object> objects = lazyAccumuloRow.getFieldsAsList();
    Assert.assertEquals(2, objects.size());
    Assert.assertEquals("foo", objects.get(1).toString());
    LazyStruct rowStruct = (LazyStruct) objects.get(0);
    List<Object> rowObjects = rowStruct.getFieldsAsList();
    Assert.assertEquals(2, rowObjects.size());
    LazyMap rowMap = (LazyMap) rowObjects.get(0);
    Map<?, ?> actualMap = rowMap.getMap();
    System.out.println("Actual map 1: " + actualMap);
    Map<String, String> actualStringMap = new HashMap<String, String>();
    for (Entry<?, ?> entry : actualMap.entrySet()) {
        actualStringMap.put(entry.getKey().toString(), entry.getValue().toString());
    }
    Assert.assertEquals(map1, actualStringMap);
    rowMap = (LazyMap) rowObjects.get(1);
    actualMap = rowMap.getMap();
    System.out.println("Actual map 2: " + actualMap);
    actualStringMap = new HashMap<String, String>();
    for (Entry<?, ?> entry : actualMap.entrySet()) {
        actualStringMap.put(entry.getKey().toString(), entry.getValue().toString());
    }
    Assert.assertEquals(map2, actualStringMap);
}

Example 5 with TypeInfoFactory.getStructTypeInfo

use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory.getStructTypeInfo in project hive by apache.

the class VectorMapOperator method internalSetChildren.

/*
   * Create information for vector map operator.
   * The member oneRootOperator has been set.
   */
private void internalSetChildren(Configuration hconf) throws Exception {
    // The setupPartitionContextVars uses the prior read type to flush the prior deserializerBatch,
    // so set it here to none.
    currentReadType = VectorMapOperatorReadType.NONE;
    batchContext = conf.getVectorizedRowBatchCtx();
    /*
     * Use a different batch for vectorized Input File Format readers so they can do their work
     * overlapped with work of the row collection that vector/row deserialization does.  This allows
     * the partitions to mix modes (e.g. for us to flush the previously batched rows on file change).
     */
    vectorizedInputFileFormatBatch = batchContext.createVectorizedRowBatch();
    conf.setVectorizedRowBatch(vectorizedInputFileFormatBatch);
    /*
     * This batch is used by vector/row deserializer readers.
     */
    deserializerBatch = batchContext.createVectorizedRowBatch();
    batchCounter = 0;
    dataColumnCount = batchContext.getDataColumnCount();
    partitionColumnCount = batchContext.getPartitionColumnCount();
    partitionValues = new Object[partitionColumnCount];
    dataColumnNums = batchContext.getDataColumnNums();
    Preconditions.checkState(dataColumnNums != null);
    // Form a truncated boolean include array for our vector/row deserializers.
    determineDataColumnsToIncludeTruncated();
    /*
     * Create table related objects
     */
    final String[] rowColumnNames = batchContext.getRowColumnNames();
    final TypeInfo[] rowColumnTypeInfos = batchContext.getRowColumnTypeInfos();
    tableStructTypeInfo = TypeInfoFactory.getStructTypeInfo(Arrays.asList(rowColumnNames), Arrays.asList(rowColumnTypeInfos));
    tableStandardStructObjectInspector = (StandardStructObjectInspector) TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(tableStructTypeInfo);
    tableRowTypeInfos = batchContext.getRowColumnTypeInfos();
    /*
     * NOTE: We do not alter the projectedColumns / projectionSize of the batches to just be
     * the included columns (+ partition columns).
     *
     * For now, we need to model the object inspector rows because there are still several
     * vectorized operators that use them.
     *
     * We need to continue to model the Object[] as having null objects for not included columns
     * until the following has been fixed:
     *    o When we have to output a STRUCT for AVG we switch to row GroupBy operators.
     *    o Some variations of VectorMapOperator, VectorReduceSinkOperator, VectorFileSinkOperator
     *      use the row super class to process rows.
     */
    /*
     * The Vectorizer class enforces that there is only one TableScanOperator, so
     * we don't need the more complicated multiple root operator mapping that MapOperator has.
     */
    fileToPartitionContextMap = new HashMap<String, VectorPartitionContext>();
    // Temporary map so we only create one partition context entry.
    HashMap<PartitionDesc, VectorPartitionContext> partitionContextMap = new HashMap<PartitionDesc, VectorPartitionContext>();
    for (Map.Entry<Path, ArrayList<String>> entry : conf.getPathToAliases().entrySet()) {
        Path path = entry.getKey();
        PartitionDesc partDesc = conf.getPathToPartitionInfo().get(path);
        VectorPartitionContext vectorPartitionContext;
        if (!partitionContextMap.containsKey(partDesc)) {
            vectorPartitionContext = createAndInitPartitionContext(partDesc, hconf);
            partitionContextMap.put(partDesc, vectorPartitionContext);
        } else {
            vectorPartitionContext = partitionContextMap.get(partDesc);
        }
        fileToPartitionContextMap.put(path.toString(), vectorPartitionContext);
    }
    // Create list of one.
    List<Operator<? extends OperatorDesc>> children = new ArrayList<Operator<? extends OperatorDesc>>();
    children.add(oneRootOperator);
    setChildOperators(children);
}