Examples with StringValue org.apache.flink.types.StringValue used on opensource projects

Example 6 with StringValue

use of org.apache.flink.types.StringValue in project flink by apache.

the class ValueCollectionDataSets method getGroupSortedNestedTupleDataSet2.

public static DataSet<Tuple3<Tuple2<IntValue, IntValue>, StringValue, IntValue>> getGroupSortedNestedTupleDataSet2(ExecutionEnvironment env) {
    List<Tuple3<Tuple2<IntValue, IntValue>, StringValue, IntValue>> data = new ArrayList<>();
    data.add(new Tuple3<>(new Tuple2<IntValue, IntValue>(new IntValue(1), new IntValue(3)), new StringValue("a"), new IntValue(2)));
    data.add(new Tuple3<>(new Tuple2<IntValue, IntValue>(new IntValue(1), new IntValue(2)), new StringValue("a"), new IntValue(1)));
    data.add(new Tuple3<>(new Tuple2<IntValue, IntValue>(new IntValue(2), new IntValue(1)), new StringValue("a"), new IntValue(3)));
    data.add(new Tuple3<>(new Tuple2<IntValue, IntValue>(new IntValue(2), new IntValue(2)), new StringValue("b"), new IntValue(4)));
    data.add(new Tuple3<>(new Tuple2<IntValue, IntValue>(new IntValue(3), new IntValue(3)), new StringValue("c"), new IntValue(5)));
    data.add(new Tuple3<>(new Tuple2<IntValue, IntValue>(new IntValue(3), new IntValue(6)), new StringValue("c"), new IntValue(6)));
    data.add(new Tuple3<>(new Tuple2<IntValue, IntValue>(new IntValue(4), new IntValue(9)), new StringValue("c"), new IntValue(7)));
    TupleTypeInfo<Tuple3<Tuple2<IntValue, IntValue>, StringValue, IntValue>> type = new TupleTypeInfo<>(new TupleTypeInfo<Tuple2<IntValue, IntValue>>(ValueTypeInfo.INT_VALUE_TYPE_INFO, ValueTypeInfo.INT_VALUE_TYPE_INFO), ValueTypeInfo.STRING_VALUE_TYPE_INFO, ValueTypeInfo.INT_VALUE_TYPE_INFO);
    return env.fromCollection(data, type);
}

Example 7 with StringValue

use of org.apache.flink.types.StringValue in project flink by apache.

the class ValueCollectionDataSets method getPojoWithCollection.

public static DataSet<PojoWithCollection> getPojoWithCollection(ExecutionEnvironment env) {
    List<PojoWithCollection> data = new ArrayList<>();
    List<Pojo1> pojosList1 = new ArrayList<>();
    pojosList1.add(new Pojo1("a", "aa"));
    pojosList1.add(new Pojo1("b", "bb"));
    List<Pojo1> pojosList2 = new ArrayList<>();
    pojosList2.add(new Pojo1("a2", "aa2"));
    pojosList2.add(new Pojo1("b2", "bb2"));
    PojoWithCollection pwc1 = new PojoWithCollection();
    pwc1.pojos = pojosList1;
    pwc1.key = new IntValue(0);
    pwc1.bigInt = BigInteger.valueOf(Long.MAX_VALUE).multiply(BigInteger.TEN);
    pwc1.scalaBigInt = BigInt.int2bigInt(10);
    pwc1.bigDecimalKeepItNull = null;
    // use calendar to make it stable across time zones
    GregorianCalendar gcl1 = new GregorianCalendar(2033, 04, 18);
    pwc1.sqlDate = new java.sql.Date(gcl1.getTimeInMillis());
    pwc1.mixed = new ArrayList<Object>();
    Map<StringValue, IntValue> map = new HashMap<>();
    map.put(new StringValue("someKey"), new IntValue(1));
    pwc1.mixed.add(map);
    pwc1.mixed.add(new File("/this/is/wrong"));
    pwc1.mixed.add("uhlala");
    PojoWithCollection pwc2 = new PojoWithCollection();
    pwc2.pojos = pojosList2;
    pwc2.key = new IntValue(0);
    pwc2.bigInt = BigInteger.valueOf(Long.MAX_VALUE).multiply(BigInteger.TEN);
    pwc2.scalaBigInt = BigInt.int2bigInt(31104000);
    pwc2.bigDecimalKeepItNull = null;
    GregorianCalendar gcl2 = new GregorianCalendar(1976, 4, 3);
    // 1976
    pwc2.sqlDate = new java.sql.Date(gcl2.getTimeInMillis());
    data.add(pwc1);
    data.add(pwc2);
    return env.fromCollection(data);
}

Example 8 with StringValue

use of org.apache.flink.types.StringValue in project flink by apache.

the class ValueCollectionDataSets method getSmallNestedTupleDataSet.

public static DataSet<Tuple2<Tuple2<IntValue, IntValue>, StringValue>> getSmallNestedTupleDataSet(ExecutionEnvironment env) {
    List<Tuple2<Tuple2<IntValue, IntValue>, StringValue>> data = new ArrayList<>();
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(1), new IntValue(1)), new StringValue("one")));
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(2), new IntValue(2)), new StringValue("two")));
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(3), new IntValue(3)), new StringValue("three")));
    TupleTypeInfo<Tuple2<Tuple2<IntValue, IntValue>, StringValue>> type = new TupleTypeInfo<>(new TupleTypeInfo<Tuple2<IntValue, IntValue>>(ValueTypeInfo.INT_VALUE_TYPE_INFO, ValueTypeInfo.INT_VALUE_TYPE_INFO), ValueTypeInfo.STRING_VALUE_TYPE_INFO);
    return env.fromCollection(data, type);
}

Example 9 with StringValue

use of org.apache.flink.types.StringValue in project flink by apache.

the class ValueCollectionDataSets method getGroupSortedNestedTupleDataSet.

public static DataSet<Tuple2<Tuple2<IntValue, IntValue>, StringValue>> getGroupSortedNestedTupleDataSet(ExecutionEnvironment env) {
    List<Tuple2<Tuple2<IntValue, IntValue>, StringValue>> data = new ArrayList<>();
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(1), new IntValue(3)), new StringValue("a")));
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(1), new IntValue(2)), new StringValue("a")));
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(2), new IntValue(1)), new StringValue("a")));
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(2), new IntValue(2)), new StringValue("b")));
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(3), new IntValue(3)), new StringValue("c")));
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(3), new IntValue(6)), new StringValue("c")));
    data.add(new Tuple2<>(new Tuple2<>(new IntValue(4), new IntValue(9)), new StringValue("c")));
    TupleTypeInfo<Tuple2<Tuple2<IntValue, IntValue>, StringValue>> type = new TupleTypeInfo<>(new TupleTypeInfo<Tuple2<IntValue, IntValue>>(ValueTypeInfo.INT_VALUE_TYPE_INFO, ValueTypeInfo.INT_VALUE_TYPE_INFO), ValueTypeInfo.STRING_VALUE_TYPE_INFO);
    return env.fromCollection(data, type);
}

Example 10 with StringValue

use of org.apache.flink.types.StringValue in project flink by apache.

the class ReduceTranslationTests method translateGroupedReduceWithkeyExtractor.

@Test
public void translateGroupedReduceWithkeyExtractor() {
    try {
        final int parallelism = 8;
        ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment(parallelism);
        DataSet<Tuple3<Double, StringValue, LongValue>> initialData = getSourceDataSet(env);
        initialData.groupBy(new KeySelector<Tuple3<Double, StringValue, LongValue>, StringValue>() {

            public StringValue getKey(Tuple3<Double, StringValue, LongValue> value) {
                return value.f1;
            }
        }).reduce(new RichReduceFunction<Tuple3<Double, StringValue, LongValue>>() {

            public Tuple3<Double, StringValue, LongValue> reduce(Tuple3<Double, StringValue, LongValue> value1, Tuple3<Double, StringValue, LongValue> value2) {
                return value1;
            }
        }).setParallelism(4).output(new DiscardingOutputFormat<Tuple3<Double, StringValue, LongValue>>());
        Plan p = env.createProgramPlan();
        GenericDataSinkBase<?> sink = p.getDataSinks().iterator().next();
        MapOperatorBase<?, ?, ?> keyProjector = (MapOperatorBase<?, ?, ?>) sink.getInput();
        PlanUnwrappingReduceOperator<?, ?> reducer = (PlanUnwrappingReduceOperator<?, ?>) keyProjector.getInput();
        MapOperatorBase<?, ?, ?> keyExtractor = (MapOperatorBase<?, ?, ?>) reducer.getInput();
        // check the parallelisms
        assertEquals(1, keyExtractor.getParallelism());
        assertEquals(4, reducer.getParallelism());
        assertEquals(4, keyProjector.getParallelism());
        // check types
        TypeInformation<?> keyValueInfo = new TupleTypeInfo<Tuple2<StringValue, Tuple3<Double, StringValue, LongValue>>>(new ValueTypeInfo<StringValue>(StringValue.class), initialData.getType());
        assertEquals(initialData.getType(), keyExtractor.getOperatorInfo().getInputType());
        assertEquals(keyValueInfo, keyExtractor.getOperatorInfo().getOutputType());
        assertEquals(keyValueInfo, reducer.getOperatorInfo().getInputType());
        assertEquals(keyValueInfo, reducer.getOperatorInfo().getOutputType());
        assertEquals(keyValueInfo, keyProjector.getOperatorInfo().getInputType());
        assertEquals(initialData.getType(), keyProjector.getOperatorInfo().getOutputType());
        // check keys
        assertEquals(KeyExtractingMapper.class, keyExtractor.getUserCodeWrapper().getUserCodeClass());
        assertTrue(keyExtractor.getInput() instanceof GenericDataSourceBase<?, ?>);
    } catch (Exception e) {
        System.err.println(e.getMessage());
        e.printStackTrace();
        fail("Test caused an error: " + e.getMessage());
    }
}