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Java DataStream.keyBy方法代碼示例

本文整理匯總了Java中org.apache.flink.streaming.api.datastream.DataStream.keyBy方法的典型用法代碼示例。如果您正苦於以下問題：Java DataStream.keyBy方法的具體用法？Java DataStream.keyBy怎麽用？Java DataStream.keyBy使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類org.apache.flink.streaming.api.datastream.DataStream的用法示例。


在下文中一共展示了DataStream.keyBy方法的15個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Java代碼示例。

示例1: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple3<K, AnomalyResult, RV>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector , KeySelector<V,Double> valueSelector, PayloadFold<V, RV> valueFold, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Object> foldResultType = TypeExtractor.getUnaryOperatorReturnType(valueFold,
                PayloadFold.class,
                false,
                false,
                ds.getType(),
                "PayloadFold",
                false);

         TypeInformation<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple3.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO), foldResultType});

        Tuple3<K,Tuple4<Double,Double,Long,Long>, RV> init= new Tuple3<>(null,new Tuple4<>(0d,0d,0l,0l), valueFold.getInit());
        KeyedStream<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new ExtCountWindFold<>(keySelector,valueFold, window, resultType),new ExtWindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:26，代碼來源:ExtNormalFreqAnomaly.java

示例2: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple3<K, AnomalyResult, RV>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector , KeySelector<V,Double> valueSelector, PayloadFold<V, RV> valueFold, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Object> foldResultType = TypeExtractor.getUnaryOperatorReturnType(valueFold,
                PayloadFold.class,
                false,
                false,
                ds.getType(),
                "PayloadFold",
                false);

         TypeInformation<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple3.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO), foldResultType});

        Tuple3<K,Tuple4<Double,Double,Long,Long>, RV> init= new Tuple3<>(null,new Tuple4<>(0d,0d,0l,0l), valueFold.getInit());
        KeyedStream<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new ExtCountSumFold<>(keySelector, valueSelector, valueFold, resultType), new ExtWindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:26，代碼來源:ExtNormalValueAnomaly.java

示例3: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple2<K, AnomalyResult>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector , Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

         TypeInformation<Tuple2<K,Tuple4<Double,Double,Long,Long>>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple2.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO)});

        Tuple2<K,Tuple4<Double,Double,Long,Long>> init= new Tuple2<>(null,new Tuple4<>(0d,0d,0l,0l));
        KeyedStream<Tuple2<K,Tuple4<Double,Double,Long,Long>>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new CountWindFold<>(keySelector, window, resultType),new WindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:18，代碼來源:NormalFreqAnomaly.java

示例4: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple2<K, AnomalyResult>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector , KeySelector<V,Double> valueSelector, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

         TypeInformation<Tuple2<K,Tuple4<Double,Double,Long,Long>>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple2.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO)});

        Tuple2<K,Tuple4<Double,Double,Long,Long>> init= new Tuple2<>(null,new Tuple4<>(0d,0d,0l,0l));
        KeyedStream<Tuple2<K,Tuple4<Double,Double,Long,Long>>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new CountSumFold<>(keySelector, valueSelector, resultType), new WindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:18，代碼來源:NormalValueAnomaly.java

示例5: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple2<K, AnomalyResult>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector, KeySelector<V,Double> valueSelector, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Tuple2<K,Tuple4<Double,Double,Long,Long>>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple2.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO)});

        Tuple2<K,Tuple4<Double,Double,Long,Long>> init= new Tuple2<>(null,new Tuple4<>(0d,0d,0l,0l));
        KeyedStream<Tuple2<K,Tuple4<Double,Double,Long,Long>>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new CountSumFold<>(keySelector,valueSelector, resultType),new WindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:18，代碼來源:PoissonValueAnomaly.java

示例6: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple3<K, AnomalyResult, RV>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector, KeySelector<V,Double> valueSelector, PayloadFold<V, RV> valueFold, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Object> foldResultType = TypeExtractor.getUnaryOperatorReturnType(valueFold,
                PayloadFold.class,
                false,
                false,
                ds.getType(),
                "PayloadFold",
                false);


        TypeInformation<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple3.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO), foldResultType});

        Tuple3<K,Tuple4<Double,Double,Long,Long>, RV> init= new Tuple3<>(null,new Tuple4<>(0d,0d,0l,0l), valueFold.getInit());
        KeyedStream<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new ExtCountSumFold<>(keySelector,valueSelector,valueFold, resultType),new ExtWindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:27，代碼來源:ExtPoissonValueAnomaly.java

示例7: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple2<K, AnomalyResult>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector , Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);


        TypeInformation<Tuple2<K,Tuple4<Double,Double,Long,Long>>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple2.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO)});

        Tuple2<K,Tuple4<Double,Double,Long,Long>> init= new Tuple2<>(null,new Tuple4<>(0d,0d,0l,0l));
        KeyedStream<Tuple2<K,Tuple4<Double,Double,Long,Long>>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new CountWindFold<>(keySelector, window, resultType),new WindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:19，代碼來源:PoissonFreqAnomaly.java

示例8: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple3<K, AnomalyResult, RV>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector , PayloadFold<V, RV> valueFold, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Object> foldResultType = TypeExtractor.getUnaryOperatorReturnType(valueFold,
                PayloadFold.class,
                false,
                false,
                ds.getType(),
                "PayloadFold",
                false);
 TypeInformation<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple3.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO), foldResultType});

        Tuple3<K,Tuple4<Double,Double,Long,Long>, RV> init= new Tuple3<>(null,new Tuple4<>(0d,0d,0l,0l), valueFold.getInit());
        KeyedStream<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new ExtCountWindFold<>(keySelector,valueFold, window, resultType),new ExtWindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:25，代碼來源:ExtPoissonFreqAnomaly.java

示例9: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple3<K, AnomalyResult, RV>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector, KeySelector<V,Double> valueSelector, PayloadFold<V, RV> valueFold, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Object> foldResultType = TypeExtractor.getUnaryOperatorReturnType(valueFold,
                PayloadFold.class,
                false,
                false,
                ds.getType(),
                "PayloadFold",
                false);

        TypeInformation<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple3.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO), foldResultType});

        Tuple3<K,Tuple4<Double,Double,Long,Long>, RV> init= new Tuple3<>(null,new Tuple4<>(0d,0d,0l,0l), valueFold.getInit());
        KeyedStream<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new ExtLogCountSumFold<>(keySelector,valueSelector,valueFold, resultType),new ExtWindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:26，代碼來源:ExtLogNormalValueAnomaly.java

示例10: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple3<K, AnomalyResult, RV>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector, KeySelector<V,Double> valueSelector, PayloadFold<V, RV> valueFold, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Object> foldResultType = TypeExtractor.getUnaryOperatorReturnType(valueFold,
                PayloadFold.class,
                false,
                false,
                ds.getType(),
                "PayloadFold",
                false);

        TypeInformation<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple2.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO), foldResultType});

        Tuple3<K,Tuple4<Double,Double,Long,Long>, RV> init= new Tuple3<>(null,new Tuple4<>(0d,0d,0l,0l), valueFold.getInit());
        KeyedStream<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new ExtLogCountSumFold<>(keySelector,valueSelector,valueFold, resultType),new ExtWindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:26，代碼來源:LogNormalValueAnomaly.java

示例11: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple3<K, AnomalyResult, RV>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector, PayloadFold<V, RV> valueFold, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Object> foldResultType = TypeExtractor.getUnaryOperatorReturnType(valueFold,
                PayloadFold.class,
                false,
                false,
                ds.getType(),
                "PayloadFold",
                false);

        TypeInformation<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple3.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO), foldResultType});

        Tuple3<K,Tuple4<Double,Double,Long,Long>, RV> init= new Tuple3<>(null,new Tuple4<>(0d,0d,0l,0l), valueFold.getInit());
        KeyedStream<Tuple3<K,Tuple4<Double,Double,Long,Long>,RV>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new ExtCountWindFold<>(keySelector,valueFold, window, resultType),new ExtWindowTimeExtractor(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:26，代碼來源:ExtExponentialFreqAnomaly.java

示例12: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple2<K, AnomalyResult>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector,  Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Tuple2<K,Tuple4<Double,Double,Long,Long>>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple2.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO)});

        Tuple2<K,Tuple4<Double,Double,Long,Long>> init= new Tuple2<>(null,new Tuple4<>(0d,0d,0l,0l));
        KeyedStream<Tuple2<K,Tuple4<Double,Double,Long,Long>>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new CountWindFold<>(keySelector, window, resultType),new WindowTimeExtractor(resultType))
                .keyBy(0);


        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:19，代碼來源:ExponentialFreqAnomaly.java

示例13: testTupleNestedArrayKeyRejection

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
public void testTupleNestedArrayKeyRejection() {
	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

	DataStream<Tuple2<Integer[], String>> input = env.fromElements(
			new Tuple2<>(new Integer[] {1, 2}, "test-test"));

	TypeInformation<?> expectedTypeInfo = new TupleTypeInfo<Tuple2<Integer[], String>>(
			BasicArrayTypeInfo.INT_ARRAY_TYPE_INFO, BasicTypeInfo.STRING_TYPE_INFO);

	// adjust the rule
	expectedException.expect(InvalidProgramException.class);
	expectedException.expectMessage(new StringStartsWith("Type " + expectedTypeInfo + " cannot be used as key."));

	input.keyBy(new KeySelector<Tuple2<Integer[], String>, Tuple2<Integer[], String>>() {
		@Override
		public Tuple2<Integer[], String> getKey(Tuple2<Integer[], String> value) throws Exception {
			return value;
		}
	});
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:22，代碼來源:DataStreamTest.java

示例14: getAnomalySteam

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
public DataStream<Tuple2<K, AnomalyResult>> getAnomalySteam(DataStream<V> ds, KeySelector<V, K> keySelector, KeySelector<V,Double> valueSelector, Time window) {

        KeyedStream<V, K> keyedInput = ds
                .keyBy(keySelector);

        TypeInformation<Tuple2<K,Tuple4<Double,Double,Long,Long>>> resultType = (TypeInformation) new TupleTypeInfo<>(Tuple2.class,
                new TypeInformation[] {keyedInput.getKeyType(), new TupleTypeInfo(Tuple4.class,
                        BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.DOUBLE_TYPE_INFO, BasicTypeInfo.LONG_TYPE_INFO,BasicTypeInfo.LONG_TYPE_INFO)});

        Tuple2<K,Tuple4<Double,Double,Long,Long>> init= new Tuple2<>(null,new Tuple4<>(0d,0d,0l,0l));
        KeyedStream<Tuple2<K,Tuple4<Double,Double,Long,Long>>, Tuple> kPreStream = keyedInput
                .timeWindow(window)
                .apply(init, new CountSumFold<>(keySelector,valueSelector, resultType),new WindowTimeExtractor<>(resultType))
                .keyBy(0);

        return kPreStream.flatMap(afm);
    }
開發者ID:sics-dna，項目名稱:isc4flink，代碼行數:18，代碼來源:ExponentialValueAnomaly.java

示例15: testPOJOWithNestedArrayNoHashCodeKeyRejection

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
public void testPOJOWithNestedArrayNoHashCodeKeyRejection() {
	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

	DataStream<POJOWithHashCode> input = env.fromElements(
			new POJOWithHashCode(new int[] {1, 2}));

	TypeInformation<?> expectedTypeInfo = new TupleTypeInfo<Tuple1<int[]>>(
			PrimitiveArrayTypeInfo.INT_PRIMITIVE_ARRAY_TYPE_INFO);

	// adjust the rule
	expectedException.expect(InvalidProgramException.class);
	expectedException.expectMessage(new StringStartsWith("Type " + expectedTypeInfo + " cannot be used as key."));

	input.keyBy("id");
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:17，代碼來源:DataStreamTest.java


注：本文中的org.apache.flink.streaming.api.datastream.DataStream.keyBy方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。