Examples with BigIntType org.apache.flink.table.types.logical.BigIntType used on opensource projects

Example 11 with BigIntType

use of org.apache.flink.table.types.logical.BigIntType in project flink by apache.

the class RowDataSerializerTest method createSerializer.

@Override
protected TypeSerializer<RowData> createSerializer() {
    TypeSerializer<?>[] fieldTypeSerializers = { LongSerializer.INSTANCE, LongSerializer.INSTANCE };
    LogicalType[] fieldTypes = { new BigIntType(), new BigIntType() };
    return new org.apache.flink.table.runtime.typeutils.serializers.python.RowDataSerializer(fieldTypes, fieldTypeSerializers);
}

Example 12 with BigIntType

use of org.apache.flink.table.types.logical.BigIntType in project flink by apache.

the class PythonTableFunctionOperatorTestBase method getTestHarness.

private OneInputStreamOperatorTestHarness<IN, OUT> getTestHarness(Configuration config, JoinRelType joinRelType) throws Exception {
    RowType inputType = new RowType(Arrays.asList(new RowType.RowField("f1", new VarCharType()), new RowType.RowField("f2", new VarCharType()), new RowType.RowField("f3", new BigIntType())));
    RowType outputType = new RowType(Arrays.asList(new RowType.RowField("f1", new VarCharType()), new RowType.RowField("f2", new VarCharType()), new RowType.RowField("f3", new BigIntType()), new RowType.RowField("f4", new BigIntType())));
    PythonTableFunctionOperator operator = getTestOperator(config, new PythonFunctionInfo(PythonScalarFunctionOperatorTestBase.DummyPythonFunction.INSTANCE, new Integer[] { 0 }), inputType, outputType, new int[] { 2 }, joinRelType);
    OneInputStreamOperatorTestHarness<IN, OUT> testHarness = new OneInputStreamOperatorTestHarness(operator);
    testHarness.getStreamConfig().setManagedMemoryFractionOperatorOfUseCase(ManagedMemoryUseCase.PYTHON, 0.5);
    return testHarness;
}

Example 13 with BigIntType

use of org.apache.flink.table.types.logical.BigIntType in project flink by apache.

the class PythonTypeUtilsTest method testLogicalTypetoInternalSerializer.

@Test
public void testLogicalTypetoInternalSerializer() {
    List<RowType.RowField> rowFields = new ArrayList<>();
    rowFields.add(new RowType.RowField("f1", new BigIntType()));
    RowType rowType = new RowType(rowFields);
    TypeSerializer baseSerializer = PythonTypeUtils.toInternalSerializer(rowType);
    assertTrue(baseSerializer instanceof RowDataSerializer);
    assertEquals(1, ((RowDataSerializer) baseSerializer).getArity());
}

Example 14 with BigIntType

use of org.apache.flink.table.types.logical.BigIntType in project flink by apache.

the class ParquetSplitReaderUtil method createVectorFromConstant.

public static ColumnVector createVectorFromConstant(LogicalType type, Object value, int batchSize) {
    switch(type.getTypeRoot()) {
        case CHAR:
        case VARCHAR:
        case BINARY:
        case VARBINARY:
            HeapBytesVector bsv = new HeapBytesVector(batchSize);
            if (value == null) {
                bsv.fillWithNulls();
            } else {
                bsv.fill(value instanceof byte[] ? (byte[]) value : value.toString().getBytes(StandardCharsets.UTF_8));
            }
            return bsv;
        case BOOLEAN:
            HeapBooleanVector bv = new HeapBooleanVector(batchSize);
            if (value == null) {
                bv.fillWithNulls();
            } else {
                bv.fill((boolean) value);
            }
            return bv;
        case TINYINT:
            HeapByteVector byteVector = new HeapByteVector(batchSize);
            if (value == null) {
                byteVector.fillWithNulls();
            } else {
                byteVector.fill(((Number) value).byteValue());
            }
            return byteVector;
        case SMALLINT:
            HeapShortVector sv = new HeapShortVector(batchSize);
            if (value == null) {
                sv.fillWithNulls();
            } else {
                sv.fill(((Number) value).shortValue());
            }
            return sv;
        case INTEGER:
            HeapIntVector iv = new HeapIntVector(batchSize);
            if (value == null) {
                iv.fillWithNulls();
            } else {
                iv.fill(((Number) value).intValue());
            }
            return iv;
        case BIGINT:
            HeapLongVector lv = new HeapLongVector(batchSize);
            if (value == null) {
                lv.fillWithNulls();
            } else {
                lv.fill(((Number) value).longValue());
            }
            return lv;
        case DECIMAL:
            DecimalType decimalType = (DecimalType) type;
            int precision = decimalType.getPrecision();
            int scale = decimalType.getScale();
            DecimalData decimal = value == null ? null : Preconditions.checkNotNull(DecimalData.fromBigDecimal((BigDecimal) value, precision, scale));
            ColumnVector internalVector;
            if (ParquetSchemaConverter.is32BitDecimal(precision)) {
                internalVector = createVectorFromConstant(new IntType(), decimal == null ? null : (int) decimal.toUnscaledLong(), batchSize);
            } else if (ParquetSchemaConverter.is64BitDecimal(precision)) {
                internalVector = createVectorFromConstant(new BigIntType(), decimal == null ? null : decimal.toUnscaledLong(), batchSize);
            } else {
                internalVector = createVectorFromConstant(new VarBinaryType(), decimal == null ? null : decimal.toUnscaledBytes(), batchSize);
            }
            return new ParquetDecimalVector(internalVector);
        case FLOAT:
            HeapFloatVector fv = new HeapFloatVector(batchSize);
            if (value == null) {
                fv.fillWithNulls();
            } else {
                fv.fill(((Number) value).floatValue());
            }
            return fv;
        case DOUBLE:
            HeapDoubleVector dv = new HeapDoubleVector(batchSize);
            if (value == null) {
                dv.fillWithNulls();
            } else {
                dv.fill(((Number) value).doubleValue());
            }
            return dv;
        case DATE:
            if (value instanceof LocalDate) {
                value = Date.valueOf((LocalDate) value);
            }
            return createVectorFromConstant(new IntType(), value == null ? null : toInternal((Date) value), batchSize);
        case TIMESTAMP_WITHOUT_TIME_ZONE:
            HeapTimestampVector tv = new HeapTimestampVector(batchSize);
            if (value == null) {
                tv.fillWithNulls();
            } else {
                tv.fill(TimestampData.fromLocalDateTime((LocalDateTime) value));
            }
            return tv;
        default:
            throw new UnsupportedOperationException("Unsupported type: " + type);
    }
}

Example 15 with BigIntType

use of org.apache.flink.table.types.logical.BigIntType in project flink by apache.

the class ArrowReaderWriterTest method init.

@BeforeClass
public static void init() {
    fieldTypes.add(new TinyIntType());
    fieldTypes.add(new SmallIntType());
    fieldTypes.add(new IntType());
    fieldTypes.add(new BigIntType());
    fieldTypes.add(new BooleanType());
    fieldTypes.add(new FloatType());
    fieldTypes.add(new DoubleType());
    fieldTypes.add(new VarCharType());
    fieldTypes.add(new VarBinaryType());
    fieldTypes.add(new DecimalType(10, 3));
    fieldTypes.add(new DateType());
    fieldTypes.add(new TimeType(0));
    fieldTypes.add(new TimeType(2));
    fieldTypes.add(new TimeType(4));
    fieldTypes.add(new TimeType(8));
    fieldTypes.add(new LocalZonedTimestampType(0));
    fieldTypes.add(new LocalZonedTimestampType(2));
    fieldTypes.add(new LocalZonedTimestampType(4));
    fieldTypes.add(new LocalZonedTimestampType(8));
    fieldTypes.add(new TimestampType(0));
    fieldTypes.add(new TimestampType(2));
    fieldTypes.add(new TimestampType(4));
    fieldTypes.add(new TimestampType(8));
    fieldTypes.add(new ArrayType(new VarCharType()));
    rowFieldType = new RowType(Arrays.asList(new RowType.RowField("a", new IntType()), new RowType.RowField("b", new VarCharType()), new RowType.RowField("c", new ArrayType(new VarCharType())), new RowType.RowField("d", new TimestampType(2)), new RowType.RowField("e", new RowType(Arrays.asList(new RowType.RowField("e1", new IntType()), new RowType.RowField("e2", new VarCharType()))))));
    fieldTypes.add(rowFieldType);
    List<RowType.RowField> rowFields = new ArrayList<>();
    for (int i = 0; i < fieldTypes.size(); i++) {
        rowFields.add(new RowType.RowField("f" + i, fieldTypes.get(i)));
    }
    rowType = new RowType(rowFields);
    allocator = ArrowUtils.getRootAllocator().newChildAllocator("stdout", 0, Long.MAX_VALUE);
}