Examples with TupleTypeInfo org.apache.flink.api.java.typeutils.TupleTypeInfo used on opensource projects

Example 1 with TupleTypeInfo

use of org.apache.flink.api.java.typeutils.TupleTypeInfo in project flink by apache.

the class PythonPlanBinder method createCsvSource.

@SuppressWarnings("unchecked")
private void createCsvSource(PythonOperationInfo info) throws IOException {
    if (!(info.types instanceof TupleTypeInfo)) {
        throw new RuntimeException("The output type of a csv source has to be a tuple. The derived type is " + info);
    }
    Path path = new Path(info.path);
    String lineD = info.lineDelimiter;
    String fieldD = info.fieldDelimiter;
    TupleTypeInfo<?> types = (TupleTypeInfo) info.types;
    sets.put(info.setID, env.createInput(new TupleCsvInputFormat(path, lineD, fieldD, types), info.types).setParallelism(getParallelism(info)).name("CsvSource").map(new SerializerMap<>()).setParallelism(getParallelism(info)).name("CsvSourcePostStep"));
}

Example 2 with TupleTypeInfo

use of org.apache.flink.api.java.typeutils.TupleTypeInfo 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 3 with TupleTypeInfo

use of org.apache.flink.api.java.typeutils.TupleTypeInfo 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 4 with TupleTypeInfo

use of org.apache.flink.api.java.typeutils.TupleTypeInfo 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 5 with TupleTypeInfo

use of org.apache.flink.api.java.typeutils.TupleTypeInfo in project flink by apache.

the class TableEnvironmentITCase method testAsFromAndToTuple.

@Test
public void testAsFromAndToTuple() throws Exception {
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    BatchTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(env, config());
    Table table = tableEnv.fromDataSet(CollectionDataSets.get3TupleDataSet(env), "a, b, c").select("a, b, c");
    TypeInformation<?> ti = new TupleTypeInfo<Tuple3<Integer, Long, String>>(BasicTypeInfo.INT_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO, BasicTypeInfo.STRING_TYPE_INFO);
    DataSet<?> ds = tableEnv.toDataSet(table, ti);
    List<?> results = ds.collect();
    String expected = "(1,1,Hi)\n" + "(2,2,Hello)\n" + "(3,2,Hello world)\n" + "(4,3,Hello world, how are you?)\n" + "(5,3,I am fine.)\n" + "(6,3,Luke Skywalker)\n" + "(7,4,Comment#1)\n" + "(8,4,Comment#2)\n" + "(9,4,Comment#3)\n" + "(10,4,Comment#4)\n" + "(11,5,Comment#5)\n" + "(12,5,Comment#6)\n" + "(13,5,Comment#7)\n" + "(14,5,Comment#8)\n" + "(15,5,Comment#9)\n" + "(16,6,Comment#10)\n" + "(17,6,Comment#11)\n" + "(18,6,Comment#12)\n" + "(19,6,Comment#13)\n" + "(20,6,Comment#14)\n" + "(21,6,Comment#15)\n";
    compareResultAsText(results, expected);
}