org.apache.flink.table.types.DataType Java Examples

@Test
public void testComplexDataTypes() throws Exception {
	DataType[] types = new DataType[]{
		DataTypes.ARRAY(DataTypes.DOUBLE()),
		DataTypes.MAP(DataTypes.FLOAT(), DataTypes.BIGINT()),
		DataTypes.ROW(
			DataTypes.FIELD("0", DataTypes.BOOLEAN()),
			DataTypes.FIELD("1", DataTypes.BOOLEAN()),
			DataTypes.FIELD("2", DataTypes.DATE())),

		// nested complex types
		DataTypes.ARRAY(DataTypes.ARRAY(DataTypes.INT())),
		DataTypes.MAP(DataTypes.STRING(), DataTypes.MAP(DataTypes.STRING(), DataTypes.BIGINT())),
		DataTypes.ROW(
			DataTypes.FIELD("3", DataTypes.ARRAY(DataTypes.DECIMAL(5, 3))),
			DataTypes.FIELD("4", DataTypes.MAP(DataTypes.TINYINT(), DataTypes.SMALLINT())),
			DataTypes.FIELD("5", DataTypes.ROW(DataTypes.FIELD("3", DataTypes.TIMESTAMP(9))))
		)
	};

	verifyDataTypes(types);
}
 

private JdbcTableSource(
	JdbcOptions options, JdbcReadOptions readOptions, JdbcLookupOptions lookupOptions,
	TableSchema schema, int[] selectFields) {
	this.options = options;
	this.readOptions = readOptions;
	this.lookupOptions = lookupOptions;
	this.schema = schema;

	this.selectFields = selectFields;

	final DataType[] schemaDataTypes = schema.getFieldDataTypes();
	final String[] schemaFieldNames = schema.getFieldNames();
	if (selectFields != null) {
		DataType[] dataTypes = new DataType[selectFields.length];
		String[] fieldNames = new String[selectFields.length];
		for (int i = 0; i < selectFields.length; i++) {
			dataTypes[i] = schemaDataTypes[selectFields[i]];
			fieldNames[i] = schemaFieldNames[selectFields[i]];
		}
		this.producedDataType =
				TableSchema.builder().fields(fieldNames, dataTypes).build().toRowDataType();
	} else {
		this.producedDataType = schema.toRowDataType();
	}
}
 

@Override
public DataType visit(KeyValueDataType keyValueDataType) {
	DataType newKeyType = keyValueDataType.getKeyDataType().accept(this);
	DataType newValueType = keyValueDataType.getValueDataType().accept(this);
	LogicalType logicalType = keyValueDataType.getLogicalType();
	LogicalType newLogicalType;
	if (logicalType instanceof MapType) {
		newLogicalType = new MapType(
			logicalType.isNullable(),
			newKeyType.getLogicalType(),
			newValueType.getLogicalType());
	} else {
		throw new UnsupportedOperationException("Unsupported logical type : " + logicalType);
	}
	return transformation.transform(new KeyValueDataType(newLogicalType, newKeyType, newValueType));
}
 

@Test
public void testStrategy() {
	if (testSpec.expectedSignature != null) {
		assertThat(
			generateSignature(),
			equalTo(testSpec.expectedSignature));
	}
	if (testSpec.expectedErrorMessage != null) {
		thrown.expect(ValidationException.class);
		thrown.expectCause(containsCause(new ValidationException(testSpec.expectedErrorMessage)));
	}
	for (List<DataType> actualArgumentTypes : testSpec.actualArgumentTypes) {
		TypeInferenceUtil.Result result = runTypeInference(actualArgumentTypes);
		if (testSpec.expectedArgumentTypes != null) {
			assertThat(result.getExpectedArgumentTypes(), equalTo(testSpec.expectedArgumentTypes));
		}
	}
}
 

@Test
public void testAddMonths() throws Exception {
	Assume.assumeTrue(HIVE_110_OR_LATER);
	HiveGenericUDF udf = init(
		Class.forName("org.apache.hadoop.hive.ql.udf.generic.GenericUDFAddMonths"),
		new Object[] {
			null,
			1
		},
		new DataType[] {
			DataTypes.STRING(),
			DataTypes.INT()
		}
	);

	assertEquals("2009-09-30", udf.eval("2009-08-31", 1));
	assertEquals("2009-09-30", udf.eval("2009-08-31 11:11:11", 1));
}
 

public CsvInputFormat(
	Path[] filePaths,
	DataType[] fieldTypes,
	String[] fieldNames,
	CsvSchema csvSchema,
	RowType formatRowType,
	int[] selectFields,
	List<String> partitionKeys,
	String defaultPartValue,
	long limit,
	int[] csvSelectFieldToProjectFieldMapping,
	int[] csvSelectFieldToCsvFieldMapping,
	boolean ignoreParseErrors) {
	super(filePaths, csvSchema);
	this.fieldTypes = fieldTypes;
	this.fieldNames = fieldNames;
	this.formatRowType = formatRowType;
	this.partitionKeys = partitionKeys;
	this.defaultPartValue = defaultPartValue;
	this.selectFields = selectFields;
	this.limit = limit;
	this.emitted = 0;
	this.csvSelectFieldToProjectFieldMapping = csvSelectFieldToProjectFieldMapping;
	this.csvSelectFieldToCsvFieldMapping = csvSelectFieldToCsvFieldMapping;
	this.ignoreParseErrors = ignoreParseErrors;
}
 

private static AdaptedCallContext inferInputTypes(
		TypeInference typeInference,
		CallContext callContext,
		@Nullable DataType outputType,
		boolean throwOnFailure) {

	final AdaptedCallContext adaptedCallContext = new AdaptedCallContext(callContext, outputType);

	// typed arguments have highest priority
	typeInference.getTypedArguments().ifPresent(adaptedCallContext::setExpectedArguments);

	final List<DataType> inferredDataTypes = typeInference.getInputTypeStrategy()
		.inferInputTypes(adaptedCallContext, throwOnFailure)
		.orElse(null);

	if (inferredDataTypes != null) {
		adaptedCallContext.setExpectedArguments(inferredDataTypes);
	} else if (throwOnFailure) {
		throw new ValidationException("Invalid input arguments.");
	}

	return adaptedCallContext;
}
 

/**
 * Returns the names of all registered column qualifiers of a specific column family.
 *
 * @param family The name of the column family for which the column qualifier names are returned.
 * @return The names of all registered column qualifiers of a specific column family.
 */
public String[] getQualifierNames(String family) {
	Map<String, DataType> qualifierMap = familyMap.get(family);

	if (qualifierMap == null) {
		throw new IllegalArgumentException("Family " + family + " does not exist in schema.");
	}

	String[] qualifierNames = new String[qualifierMap.size()];
	int i = 0;
	for (String qualifier: qualifierMap.keySet()) {
		qualifierNames[i] = qualifier;
		i++;
	}
	return qualifierNames;
}
 

public ParquetInputFormat(
		Path[] paths,
		String[] fullFieldNames,
		DataType[] fullFieldTypes,
		int[] selectedFields,
		String partDefaultName,
		long limit,
		Configuration conf,
		boolean utcTimestamp) {
	super.setFilePaths(paths);
	this.limit = limit;
	this.partDefaultName = partDefaultName;
	this.fullFieldNames = fullFieldNames;
	this.fullFieldTypes = fullFieldTypes;
	this.selectedFields = selectedFields;
	this.conf = new SerializableConfiguration(conf);
	this.utcTimestamp = utcTimestamp;
}
 

private TypeInferenceUtil.Result resolveWithCastedAssignment(
		UnresolvedCallExpression unresolvedCall,
		List<ResolvedExpression> args,
		List<TypeInformation<?>> expectedTypes,
		TypeInformation<?> resultType) {

	final List<PlannerExpression> plannerArgs = unresolvedCall.getChildren()
		.stream()
		.map(e -> e.accept(CONVERTER))
		.collect(Collectors.toList());

	final List<DataType> castedArgs = IntStream.range(0, plannerArgs.size())
		.mapToObj(idx -> castIfNeeded(
			args.get(idx),
			plannerArgs.get(idx),
			expectedTypes.get(idx)))
		.collect(Collectors.toList());

	return new TypeInferenceUtil.Result(
		castedArgs,
		null,
		fromLegacyInfoToDataType(resultType));
}
 

@Override
public DataType getProducedDataType() {
    TableSchema fullSchema = getTableSchema();
    DataType type;
    if (projectedFields == null) {
        type = fullSchema.toRowDataType();
    } else {
        String[] fullNames = fullSchema.getFieldNames();
        DataType[] fullTypes = fullSchema.getFieldDataTypes();
        type = TableSchema.builder().fields(
            Arrays.stream(projectedFields).mapToObj(i -> fullNames[i]).toArray(String[]::new),
            Arrays.stream(projectedFields).mapToObj(i -> fullTypes[i]).toArray(DataType[]::new))
            .build().toRowDataType();
    }
    return type.bridgedTo(BaseRow.class);
}
 

private void testField(
		DataType fieldType,
		String csvValue,
		Object value,
		Consumer<CsvRowDataSerializationSchema.Builder> serializationConfig,
		Consumer<CsvRowDataDeserializationSchema.Builder> deserializationConfig,
		String fieldDelimiter) throws Exception {
	RowType rowType = (RowType) ROW(
		FIELD("f0", STRING()),
		FIELD("f1", fieldType),
		FIELD("f2", STRING())
	).getLogicalType();
	String expectedCsv = "BEGIN" + fieldDelimiter + csvValue + fieldDelimiter + "END\n";

	// deserialization
	CsvRowDataDeserializationSchema.Builder deserSchemaBuilder =
		new CsvRowDataDeserializationSchema.Builder(rowType, new RowDataTypeInfo(rowType));
	deserializationConfig.accept(deserSchemaBuilder);
	RowData deserializedRow = deserialize(deserSchemaBuilder, expectedCsv);

	// serialization
	CsvRowDataSerializationSchema.Builder serSchemaBuilder = new CsvRowDataSerializationSchema.Builder(rowType);
	serializationConfig.accept(serSchemaBuilder);
	byte[] serializedRow = serialize(serSchemaBuilder, deserializedRow);
	assertEquals(expectedCsv, new String(serializedRow));
}
 

public Result(
		List<DataType> expectedArgumentTypes,
		@Nullable DataType accumulatorDataType,
		DataType outputDataType) {
	this.expectedArgumentTypes = expectedArgumentTypes;
	this.accumulatorDataType = accumulatorDataType;
	this.outputDataType = outputDataType;
}
 

public CallExpression cast(ResolvedExpression expression, DataType dataType) {
	final FunctionLookup.Result lookupOfCast = functionLookup
		.lookupBuiltInFunction(BuiltInFunctionDefinitions.CAST);

	return new CallExpression(
		lookupOfCast.getObjectIdentifier(),
		lookupOfCast.getFunctionDefinition(),
		Arrays.asList(expression, typeLiteral(dataType)),
		dataType);
}
 

private Function<Object, Object> newStructConverter(FieldsDataType dataType, Schema avroStruct) throws SchemaUtils.IncompatibleSchemaException {
    if (avroStruct.getType() != RECORD ||
            avroStruct.getFields().size() != dataType.getFieldDataTypes().size()) {
        throw new SchemaUtils.IncompatibleSchemaException(
                String.format("Cannot convert Flink type %s to Avro type %s.", dataType.toString(), avroStruct.toString(true)));
    }

    Map<String, DataType> fieldsType = dataType.getFieldDataTypes();
    List<RowType.RowField> fields = ((RowType) dataType.getLogicalType()).getFields();

    List<BiFunction<PositionedGetter, Integer, Object>> fieldConverters = new ArrayList<>();

    for (int i = 0; i < fields.size(); i++) {
        RowType.RowField rf = fields.get(i);
        DataType dt = fieldsType.get(rf.getName());
        Schema.Field at = avroStruct.getFields().get(i);
        fieldConverters.add(newConverter(dt, resolveNullableType(at.schema(), dt.getLogicalType().isNullable())));
    }
    int numFields = fieldsType.size();

    return row -> {
        GenericSchema<GenericRecord> pSchema = SchemaUtils.avroSchema2PulsarSchema(avroStruct);
        GenericRecordBuilder builder = pSchema.newRecordBuilder();
        Row rowX = (Row) row;

        for (int i = 0; i < numFields; i++) {
            if (rowX.getField(i) == null) {
                builder.set(pSchema.getFields().get(i), null);
            } else {
                builder.set(pSchema.getFields().get(i), fieldConverters.get(i).apply(new PositionedGetter(rowX), i));
            }
        }
        return (GenericAvroRecord) builder.build();
    };

}
 

public JacksonRecordParser(DataType schema, JSONOptions options) {
    assert schema instanceof FieldsDataType;
    this.schema = schema;
    this.options = options;

    this.rootConverter = makeStructRootConverter((FieldsDataType) schema);

    this.factory = new JsonFactory();
    options.setJacksonOptions(factory);
}
 

@Test
public void testUDFConv() {
	HiveSimpleUDF udf = init(
		UDFConv.class,
		new DataType[]{
			DataTypes.STRING(),
			DataTypes.INT(),
			DataTypes.INT()
		});

	assertEquals("1", udf.eval("12", 2, 10));
	assertEquals("-16", udf.eval(-10, 16, -10));
}
 

@Test
public void testExpandStructuredType() {
	StructuredType logicalType = StructuredType.newBuilder(ObjectIdentifier.of("catalog", "database", "type"))
		.attributes(Arrays.asList(
			new StructuredType.StructuredAttribute("f0", DataTypes.INT().getLogicalType()),
			new StructuredType.StructuredAttribute("f1", DataTypes.STRING().getLogicalType()),
			new StructuredType.StructuredAttribute("f2", DataTypes.TIMESTAMP(5).getLogicalType()),
			new StructuredType.StructuredAttribute("f3", DataTypes.TIMESTAMP(3).getLogicalType())
		))
		.build();

	List<DataType> dataTypes = Arrays.asList(
		DataTypes.INT(),
		DataTypes.STRING(),
		DataTypes.TIMESTAMP(5).bridgedTo(Timestamp.class),
		DataTypes.TIMESTAMP(3));
	FieldsDataType dataType = new FieldsDataType(logicalType, dataTypes);

	TableSchema schema = DataTypeUtils.expandCompositeTypeToSchema(dataType);

	assertThat(
		schema,
		equalTo(
			TableSchema.builder()
				.field("f0", INT())
				.field("f1", STRING())
				.field("f2", TIMESTAMP(5).bridgedTo(Timestamp.class))
				.field("f3", TIMESTAMP(3).bridgedTo(LocalDateTime.class))
				.build()));
}
 

@Test
public void testIsCompositeTypeSimpleType() {
	DataType dataType = DataTypes.TIMESTAMP();
	boolean isCompositeType = LogicalTypeChecks.isCompositeType(dataType.getLogicalType());

	assertThat(isCompositeType, is(false));
}
 

private static RowType createJsonRowType(DataType databaseSchema) {
	// Canal JSON contains other information, e.g. "database", "ts"
	// but we don't need them
	return (RowType) DataTypes.ROW(
		DataTypes.FIELD("data", DataTypes.ARRAY(databaseSchema)),
		DataTypes.FIELD("old", DataTypes.ARRAY(databaseSchema)),
		DataTypes.FIELD("type", DataTypes.STRING())).getLogicalType();
}
 

public QueryOperation create(
		List<ResolvedExpression> projectList,
		QueryOperation child,
		boolean explicitAlias,
		ExpressionResolver.PostResolverFactory postResolverFactory) {

	final NamingVisitor namingVisitor = new NamingVisitor(postResolverFactory);

	final List<ResolvedExpression> namedExpressions = nameExpressions(namingVisitor, projectList);
	String[] fieldNames = validateAndGetUniqueNames(namedExpressions);

	final List<ResolvedExpression> finalExpression;
	if (explicitAlias) {
		finalExpression = namedExpressions;
	} else {
		finalExpression = namedExpressions.stream()
			.map(expr -> expr.accept(stripAliases))
			.collect(Collectors.toList());
	}

	DataType[] fieldTypes = namedExpressions.stream()
		.map(ResolvedExpression::getOutputDataType)
		.toArray(DataType[]::new);

	TableSchema tableSchema = TableSchema.builder().fields(fieldNames, fieldTypes).build();

	return new ProjectQueryOperation(finalExpression, child, tableSchema);
}
 

/**
 * Declares a list of fields to be rowtime attributes.
 *
 * @param rowtimeAttributeDescriptors The descriptors of the rowtime attributes.
 */
protected void setRowtimeAttributeDescriptors(List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors) {
    // validate that all declared fields exist and are of correct type
    for (RowtimeAttributeDescriptor desc : rowtimeAttributeDescriptors) {
        String rowtimeAttribute = desc.getAttributeName();
        Optional<DataType> tpe = schema.getFieldDataType(rowtimeAttribute);
        if (!tpe.isPresent()) {
            throw new ValidationException("Rowtime attribute " + rowtimeAttribute + " is not present in TableSchema.");
        } else if (tpe.get().getLogicalType().getTypeRoot() != LogicalTypeRoot.TIMESTAMP_WITHOUT_TIME_ZONE) {
            throw new ValidationException("Rowtime attribute " + rowtimeAttribute + " is not of type TIMESTAMP.");
        }
    }
    this.rowtimeAttributeDescriptors = rowtimeAttributeDescriptors;
}
 

private BiFunction<PositionedGetter, Integer, Object> singleValueConverter(DataType dataType, Schema avroType) throws SchemaUtils.IncompatibleSchemaException {
    LogicalTypeRoot tpe = dataType.getLogicalType().getTypeRoot();
    Schema.Type atpe = avroType.getType();
    if (tpe == LogicalTypeRoot.NULL && atpe == Schema.Type.NULL) {
        return (getter, ordinal) -> null;
    } else if ((tpe == LogicalTypeRoot.BOOLEAN && atpe == Schema.Type.BOOLEAN) ||
            (tpe == LogicalTypeRoot.TINYINT && atpe == Schema.Type.INT) ||
            (tpe == LogicalTypeRoot.SMALLINT && atpe == Schema.Type.INT) ||
            (tpe == LogicalTypeRoot.INTEGER && atpe == Schema.Type.INT) ||
            (tpe == LogicalTypeRoot.BIGINT && atpe == Schema.Type.LONG) ||
            (tpe == LogicalTypeRoot.FLOAT && atpe == Schema.Type.FLOAT) ||
            (tpe == LogicalTypeRoot.DOUBLE && atpe == Schema.Type.DOUBLE) ||
            (tpe == LogicalTypeRoot.VARCHAR && atpe == Schema.Type.STRING) ||
            (tpe == LogicalTypeRoot.VARBINARY && atpe == Schema.Type.BYTES) ||
            (tpe == LogicalTypeRoot.DATE && atpe == Schema.Type.INT)) {
        return (getter, ordinal) -> getter.getField(ordinal);
    } else if (tpe == LogicalTypeRoot.TIMESTAMP_WITHOUT_TIME_ZONE && atpe == Schema.Type.LONG) {
        LogicalType altpe = avroType.getLogicalType();
        if (altpe instanceof LogicalTypes.TimestampMillis || altpe instanceof LogicalTypes.TimestampMicros) {
            return (getter, ordinal) -> getter.getField(ordinal);
        } else {
            throw new SchemaUtils.IncompatibleSchemaException(
                    "Cannot convert flink timestamp to avro logical type " + altpe.toString());
        }
    } else {
        throw new SchemaUtils.IncompatibleSchemaException(String.format(
                "Cannot convert flink type %s to avro type %s", dataType.toString(), avroType.toString(true)));
    }
}
 

@Test
public void testUDFToInteger() {
	HiveSimpleUDF udf = init(
		UDFToInteger.class,
		new DataType[]{
			DataTypes.DECIMAL(5, 3)
		});

	assertEquals(1, udf.eval(BigDecimal.valueOf(1.1d)));
}
 

static RelDataType invokeGetResultType(
		Object function, Object[] constantArguments, LogicalType[] argTypes,
		FlinkTypeFactory typeFactory) {
	try {
		// See hive HiveFunction
		Method method = function.getClass()
				.getMethod("getHiveResultType", Object[].class, DataType[].class);
		DataType resultType = (DataType) method.invoke(
				function, constantArguments, TypeConversions.fromLogicalToDataType(argTypes));
		return typeFactory.createFieldTypeFromLogicalType(fromDataTypeToLogicalType(resultType));
	} catch (NoSuchMethodException | IllegalAccessException | InvocationTargetException e) {
		throw new RuntimeException(e);
	}
}
 

@Override
public DataType getProducedDataType() {
	return TableSchema.builder()
		.fields(config.getSelectedFieldNames(), config.getSelectedFieldDataTypes())
		.build()
		.toRowDataType();
}
 

@Test
public void testConversions() {
	if (testSpec.expectedErrorMessage != null) {
		thrown.expect(TableException.class);
		thrown.expectMessage(equalTo(testSpec.expectedErrorMessage));
	}
	for (Map.Entry<Class<?>, Object> from : testSpec.conversions.entrySet()) {
		final DataType fromDataType = testSpec.dataType.bridgedTo(from.getKey());

		final DataStructureConverter<Object, Object> fromConverter =
			simulateSerialization(DataStructureConverters.getConverter(fromDataType));
		fromConverter.open(DataStructureConvertersTest.class.getClassLoader());

		final Object internalValue = fromConverter.toInternalOrNull(from.getValue());

		final Object anotherValue = testSpec.conversionsWithAnotherValue.get(from.getKey());
		if (anotherValue != null) {
			fromConverter.toInternalOrNull(anotherValue);
		}

		for (Map.Entry<Class<?>, Object> to : testSpec.conversions.entrySet()) {
			final DataType toDataType = testSpec.dataType.bridgedTo(to.getKey());

			final DataStructureConverter<Object, Object> toConverter =
				simulateSerialization(DataStructureConverters.getConverter(toDataType));
			toConverter.open(DataStructureConvertersTest.class.getClassLoader());

			assertArrayEquals(
				new Object[]{to.getValue()},
				new Object[]{toConverter.toExternalOrNull(internalValue)});
		}
	}
}
 

private static RexNode convertThrowException(CallExpression call, ConvertContext context) {
	checkArgumentNumber(call, 2);
	DataType type = ((TypeLiteralExpression) call.getChildren().get(1)).getOutputDataType();
	SqlThrowExceptionFunction function = new SqlThrowExceptionFunction(
		context.getTypeFactory().createFieldTypeFromLogicalType(fromDataTypeToLogicalType(type)));
	return context.getRelBuilder().call(function, context.toRexNode(call.getChildren().get(0)));
}
 

public CallExpression get(ResolvedExpression composite, ValueLiteralExpression key, DataType dataType) {
	final FunctionLookup.Result lookupOfGet = functionLookup
		.lookupBuiltInFunction(BuiltInFunctionDefinitions.GET);

	return new CallExpression(
		lookupOfGet.getObjectIdentifier(),
		lookupOfGet.getFunctionDefinition(),
		Arrays.asList(composite, key),
		dataType);
}
 

/**
 * Convert Hive data type to a Flink data type.
 *
 * @param hiveType a Hive data type
 * @return the corresponding Flink data type
 */
public static DataType toFlinkType(TypeInfo hiveType) {
	checkNotNull(hiveType, "hiveType cannot be null");

	switch (hiveType.getCategory()) {
		case PRIMITIVE:
			return toFlinkPrimitiveType((PrimitiveTypeInfo) hiveType);
		case LIST:
			ListTypeInfo listTypeInfo = (ListTypeInfo) hiveType;
			return DataTypes.ARRAY(toFlinkType(listTypeInfo.getListElementTypeInfo()));
		case MAP:
			MapTypeInfo mapTypeInfo = (MapTypeInfo) hiveType;
			return DataTypes.MAP(toFlinkType(mapTypeInfo.getMapKeyTypeInfo()), toFlinkType(mapTypeInfo.getMapValueTypeInfo()));
		case STRUCT:
			StructTypeInfo structTypeInfo = (StructTypeInfo) hiveType;

			List<String> names = structTypeInfo.getAllStructFieldNames();
			List<TypeInfo> typeInfos = structTypeInfo.getAllStructFieldTypeInfos();

			DataTypes.Field[] fields = new DataTypes.Field[names.size()];

			for (int i = 0; i < fields.length; i++) {
				fields[i] = DataTypes.FIELD(names.get(i), toFlinkType(typeInfos.get(i)));
			}

			return DataTypes.ROW(fields);
		default:
			throw new UnsupportedOperationException(
				String.format("Flink doesn't support Hive data type %s yet.", hiveType));
	}
}