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社区首页 >专栏 >聊聊flink DataStream的join操作

聊聊flink DataStream的join操作

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code4it
发布2019-01-10 14:14:11
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发布2019-01-10 14:14:11
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文章被收录于专栏:码匠的流水账码匠的流水账

本文主要研究一下flink DataStream的join操作

实例

代码语言:javascript
复制
stream.join(otherStream)
    .where(<KeySelector>)
    .equalTo(<KeySelector>)
    .window(<WindowAssigner>)
    .apply(<JoinFunction>)
  • 这里首先调用join,与另外一个stream合并,返回的是JoinedStreams,之后就可以调用JoinedStreams的where操作来构建Where对象构造条件;Where有equalTo操作可以构造EqualTo,而EqualTo有window操作可以构造WithWindow,而WithWindow可以设置windowAssigner、trigger、evictor、allowedLateness,它提供apply操作

DataStream.join

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/DataStream.java

代码语言:javascript
复制
@Public
public class DataStream<T> {
    //......
​
    /**
     * Creates a join operation. See {@link JoinedStreams} for an example of how the keys
     * and window can be specified.
     */
    public <T2> JoinedStreams<T, T2> join(DataStream<T2> otherStream) {
        return new JoinedStreams<>(this, otherStream);
    }
​
    //......
}
  • DataStream提供了join方法,用于执行join操作,它返回的是JoinedStreams

JoinedStreams

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/JoinedStreams.java

代码语言:javascript
复制
@Public
public class JoinedStreams<T1, T2> {
​
    /** The first input stream. */
    private final DataStream<T1> input1;
​
    /** The second input stream. */
    private final DataStream<T2> input2;
​
    public JoinedStreams(DataStream<T1> input1, DataStream<T2> input2) {
        this.input1 = requireNonNull(input1);
        this.input2 = requireNonNull(input2);
    }
​
    public <KEY> Where<KEY> where(KeySelector<T1, KEY> keySelector)  {
        requireNonNull(keySelector);
        final TypeInformation<KEY> keyType = TypeExtractor.getKeySelectorTypes(keySelector, input1.getType());
        return where(keySelector, keyType);
    }
​
    public <KEY> Where<KEY> where(KeySelector<T1, KEY> keySelector, TypeInformation<KEY> keyType)  {
        requireNonNull(keySelector);
        requireNonNull(keyType);
        return new Where<>(input1.clean(keySelector), keyType);
    }
​
    //......
}
  • JoinedStreams主要是提供where操作来构建Where对象

Where

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/JoinedStreams.java

代码语言:javascript
复制
    @Public
    public class Where<KEY> {
​
        private final KeySelector<T1, KEY> keySelector1;
        private final TypeInformation<KEY> keyType;
​
        Where(KeySelector<T1, KEY> keySelector1, TypeInformation<KEY> keyType) {
            this.keySelector1 = keySelector1;
            this.keyType = keyType;
        }
​
        public EqualTo equalTo(KeySelector<T2, KEY> keySelector)  {
            requireNonNull(keySelector);
            final TypeInformation<KEY> otherKey = TypeExtractor.getKeySelectorTypes(keySelector, input2.getType());
            return equalTo(keySelector, otherKey);
        }
​
        public EqualTo equalTo(KeySelector<T2, KEY> keySelector, TypeInformation<KEY> keyType)  {
            requireNonNull(keySelector);
            requireNonNull(keyType);
​
            if (!keyType.equals(this.keyType)) {
                throw new IllegalArgumentException("The keys for the two inputs are not equal: " +
                        "first key = " + this.keyType + " , second key = " + keyType);
            }
​
            return new EqualTo(input2.clean(keySelector));
        }
​
        //......
​
    }
  • Where对象主要提供equalTo操作用于构建EqualTo对象

EqualTo

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/JoinedStreams.java

代码语言:javascript
复制
        @Public
        public class EqualTo {
​
            private final KeySelector<T2, KEY> keySelector2;
​
            EqualTo(KeySelector<T2, KEY> keySelector2) {
                this.keySelector2 = requireNonNull(keySelector2);
            }
​
            /**
             * Specifies the window on which the join operation works.
             */
            @PublicEvolving
            public <W extends Window> WithWindow<T1, T2, KEY, W> window(WindowAssigner<? super TaggedUnion<T1, T2>, W> assigner) {
                return new WithWindow<>(input1, input2, keySelector1, keySelector2, keyType, assigner, null, null, null);
            }
        }
  • EqualTo对象提供window操作用于构建WithWindow对象

WithWindow

/flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/JoinedStreams.java

代码语言:javascript
复制
    @Public
    public static class WithWindow<T1, T2, KEY, W extends Window> {
​
        private final DataStream<T1> input1;
        private final DataStream<T2> input2;
​
        private final KeySelector<T1, KEY> keySelector1;
        private final KeySelector<T2, KEY> keySelector2;
        private final TypeInformation<KEY> keyType;
​
        private final WindowAssigner<? super TaggedUnion<T1, T2>, W> windowAssigner;
​
        private final Trigger<? super TaggedUnion<T1, T2>, ? super W> trigger;
​
        private final Evictor<? super TaggedUnion<T1, T2>, ? super W> evictor;
​
        private final Time allowedLateness;
​
        private CoGroupedStreams.WithWindow<T1, T2, KEY, W> coGroupedWindowedStream;
​
        @PublicEvolving
        protected WithWindow(DataStream<T1> input1,
                DataStream<T2> input2,
                KeySelector<T1, KEY> keySelector1,
                KeySelector<T2, KEY> keySelector2,
                TypeInformation<KEY> keyType,
                WindowAssigner<? super TaggedUnion<T1, T2>, W> windowAssigner,
                Trigger<? super TaggedUnion<T1, T2>, ? super W> trigger,
                Evictor<? super TaggedUnion<T1, T2>, ? super W> evictor,
                Time allowedLateness) {
​
            this.input1 = requireNonNull(input1);
            this.input2 = requireNonNull(input2);
​
            this.keySelector1 = requireNonNull(keySelector1);
            this.keySelector2 = requireNonNull(keySelector2);
            this.keyType = requireNonNull(keyType);
​
            this.windowAssigner = requireNonNull(windowAssigner);
​
            this.trigger = trigger;
            this.evictor = evictor;
​
            this.allowedLateness = allowedLateness;
        }
​
        @PublicEvolving
        public WithWindow<T1, T2, KEY, W> trigger(Trigger<? super TaggedUnion<T1, T2>, ? super W> newTrigger) {
            return new WithWindow<>(input1, input2, keySelector1, keySelector2, keyType,
                    windowAssigner, newTrigger, evictor, allowedLateness);
        }
​
        @PublicEvolving
        public WithWindow<T1, T2, KEY, W> evictor(Evictor<? super TaggedUnion<T1, T2>, ? super W> newEvictor) {
            return new WithWindow<>(input1, input2, keySelector1, keySelector2, keyType,
                    windowAssigner, trigger, newEvictor, allowedLateness);
        }
​
        @PublicEvolving
        public WithWindow<T1, T2, KEY, W> allowedLateness(Time newLateness) {
            return new WithWindow<>(input1, input2, keySelector1, keySelector2, keyType,
                windowAssigner, trigger, evictor, newLateness);
        }
​
        public <T> DataStream<T> apply(JoinFunction<T1, T2, T> function) {
            TypeInformation<T> resultType = TypeExtractor.getBinaryOperatorReturnType(
                function,
                JoinFunction.class,
                0,
                1,
                2,
                TypeExtractor.NO_INDEX,
                input1.getType(),
                input2.getType(),
                "Join",
                false);
​
            return apply(function, resultType);
        }
​
        @PublicEvolving
        @Deprecated
        public <T> SingleOutputStreamOperator<T> with(JoinFunction<T1, T2, T> function) {
            return (SingleOutputStreamOperator<T>) apply(function);
        }
​
        public <T> DataStream<T> apply(FlatJoinFunction<T1, T2, T> function, TypeInformation<T> resultType) {
            //clean the closure
            function = input1.getExecutionEnvironment().clean(function);
​
            coGroupedWindowedStream = input1.coGroup(input2)
                .where(keySelector1)
                .equalTo(keySelector2)
                .window(windowAssigner)
                .trigger(trigger)
                .evictor(evictor)
                .allowedLateness(allowedLateness);
​
            return coGroupedWindowedStream
                    .apply(new FlatJoinCoGroupFunction<>(function), resultType);
        }
​
        @PublicEvolving
        @Deprecated
        public <T> SingleOutputStreamOperator<T> with(FlatJoinFunction<T1, T2, T> function, TypeInformation<T> resultType) {
            return (SingleOutputStreamOperator<T>) apply(function, resultType);
        }
​
        public <T> DataStream<T> apply(FlatJoinFunction<T1, T2, T> function) {
            TypeInformation<T> resultType = TypeExtractor.getBinaryOperatorReturnType(
                function,
                FlatJoinFunction.class,
                0,
                1,
                2,
                new int[]{2, 0},
                input1.getType(),
                input2.getType(),
                "Join",
                false);
​
            return apply(function, resultType);
        }
​
        @PublicEvolving
        @Deprecated
        public <T> SingleOutputStreamOperator<T> with(FlatJoinFunction<T1, T2, T> function) {
            return (SingleOutputStreamOperator<T>) apply(function);
        }
​
        public <T> DataStream<T> apply(JoinFunction<T1, T2, T> function, TypeInformation<T> resultType) {
            //clean the closure
            function = input1.getExecutionEnvironment().clean(function);
​
            coGroupedWindowedStream = input1.coGroup(input2)
                .where(keySelector1)
                .equalTo(keySelector2)
                .window(windowAssigner)
                .trigger(trigger)
                .evictor(evictor)
                .allowedLateness(allowedLateness);
​
            return coGroupedWindowedStream
                    .apply(new JoinCoGroupFunction<>(function), resultType);
        }
​
        @PublicEvolving
        @Deprecated
        public <T> SingleOutputStreamOperator<T> with(JoinFunction<T1, T2, T> function, TypeInformation<T> resultType) {
            return (SingleOutputStreamOperator<T>) apply(function, resultType);
        }
​
        @VisibleForTesting
        Time getAllowedLateness() {
            return allowedLateness;
        }
​
        @VisibleForTesting
        CoGroupedStreams.WithWindow<T1, T2, KEY, W> getCoGroupedWindowedStream() {
            return coGroupedWindowedStream;
        }
    }
  • WithWindow可以设置windowAssigner、trigger、evictor、allowedLateness,它提供apply操作(with操作被标记为废弃)
  • apply操作可以接收JoinFunction或者FlatJoinFunction,它内部是使用DataStream的coGroup方法创建CoGroupedStreams,之后将自身的where及equalTo的keySelector、windowAssigner、trigger、evictor、allowedLateness都设置给CoGroupedStreams,最后调用CoGroupedStreams的WithWindow对象的apply方法
  • CoGroupedStreams的WithWindow对象的apply方法与JoinedStreams的WithWindow对象的apply方法参数不同,CoGroupedStreams的WithWindow的apply方法接收的是CoGroupFunction,因而JoinedStreams的WithWindow对象的apply方法内部将JoinFunction或者FlatJoinFunction包装为CoGroupFunction(JoinFunction使用JoinCoGroupFunction包装,FlatJoinFunction使用FlatJoinCoGroupFunction包装)传递给CoGroupedStreams的WithWindow的apply方法

JoinFunction

flink-core-1.7.0-sources.jar!/org/apache/flink/api/common/functions/JoinFunction.java

代码语言:javascript
复制
@Public
@FunctionalInterface
public interface JoinFunction<IN1, IN2, OUT> extends Function, Serializable {
​
    /**
     * The join method, called once per joined pair of elements.
     *
     * @param first The element from first input.
     * @param second The element from second input.
     * @return The resulting element.
     *
     * @throws Exception This method may throw exceptions. Throwing an exception will cause the operation
     *                   to fail and may trigger recovery.
     */
    OUT join(IN1 first, IN2 second) throws Exception;
}
  • JoinFunction继承了Function、Serializable,它定义了join操作,默认是inner join的语义,如果需要outer join,可以使用CoGroupFunction

FlatJoinFunction

flink-core-1.7.0-sources.jar!/org/apache/flink/api/common/functions/FlatJoinFunction.java

代码语言:javascript
复制
@Public
@FunctionalInterface
public interface FlatJoinFunction<IN1, IN2, OUT> extends Function, Serializable {
​
    /**
     * The join method, called once per joined pair of elements.
     *
     * @param first The element from first input.
     * @param second The element from second input.
     * @param out The collector used to return zero, one, or more elements.
     *
     * @throws Exception This method may throw exceptions. Throwing an exception will cause the operation
     *                   to fail and may trigger recovery.
     */
    void join (IN1 first, IN2 second, Collector<OUT> out) throws Exception;
}
  • FlatJoinFunction继承了Function、Serializable,它定义了join操作,默认是inner join的语义,如果需要outer join,可以使用CoGroupFunction;与JoinFunction的join方法不同,FlatJoinFunction的join方法多了Collector参数,可以用来发射0条、1条或者多条数据,所以是Flat命名

CoGroupedStreams

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/CoGroupedStreams.java

代码语言:javascript
复制
@Public
public class CoGroupedStreams<T1, T2> {
    //......
​
@Public
    public static class WithWindow<T1, T2, KEY, W extends Window> {
        private final DataStream<T1> input1;
        private final DataStream<T2> input2;
​
        private final KeySelector<T1, KEY> keySelector1;
        private final KeySelector<T2, KEY> keySelector2;
​
        private final TypeInformation<KEY> keyType;
​
        private final WindowAssigner<? super TaggedUnion<T1, T2>, W> windowAssigner;
​
        private final Trigger<? super TaggedUnion<T1, T2>, ? super W> trigger;
​
        private final Evictor<? super TaggedUnion<T1, T2>, ? super W> evictor;
​
        private final Time allowedLateness;
​
        private WindowedStream<TaggedUnion<T1, T2>, KEY, W> windowedStream;
​
        protected WithWindow(DataStream<T1> input1,
                DataStream<T2> input2,
                KeySelector<T1, KEY> keySelector1,
                KeySelector<T2, KEY> keySelector2,
                TypeInformation<KEY> keyType,
                WindowAssigner<? super TaggedUnion<T1, T2>, W> windowAssigner,
                Trigger<? super TaggedUnion<T1, T2>, ? super W> trigger,
                Evictor<? super TaggedUnion<T1, T2>, ? super W> evictor,
                Time allowedLateness) {
            this.input1 = input1;
            this.input2 = input2;
​
            this.keySelector1 = keySelector1;
            this.keySelector2 = keySelector2;
            this.keyType = keyType;
​
            this.windowAssigner = windowAssigner;
            this.trigger = trigger;
            this.evictor = evictor;
​
            this.allowedLateness = allowedLateness;
        }
​
        @PublicEvolving
        public WithWindow<T1, T2, KEY, W> trigger(Trigger<? super TaggedUnion<T1, T2>, ? super W> newTrigger) {
            return new WithWindow<>(input1, input2, keySelector1, keySelector2, keyType,
                    windowAssigner, newTrigger, evictor, allowedLateness);
        }
​
        @PublicEvolving
        public WithWindow<T1, T2, KEY, W> evictor(Evictor<? super TaggedUnion<T1, T2>, ? super W> newEvictor) {
            return new WithWindow<>(input1, input2, keySelector1, keySelector2, keyType,
                    windowAssigner, trigger, newEvictor, allowedLateness);
        }
​
        @PublicEvolving
        public WithWindow<T1, T2, KEY, W> allowedLateness(Time newLateness) {
            return new WithWindow<>(input1, input2, keySelector1, keySelector2, keyType,
                    windowAssigner, trigger, evictor, newLateness);
        }
​
        public <T> DataStream<T> apply(CoGroupFunction<T1, T2, T> function) {
​
            TypeInformation<T> resultType = TypeExtractor.getCoGroupReturnTypes(
                function,
                input1.getType(),
                input2.getType(),
                "CoGroup",
                false);
​
            return apply(function, resultType);
        }
​
        public <T> DataStream<T> apply(CoGroupFunction<T1, T2, T> function, TypeInformation<T> resultType) {
            //clean the closure
            function = input1.getExecutionEnvironment().clean(function);
​
            UnionTypeInfo<T1, T2> unionType = new UnionTypeInfo<>(input1.getType(), input2.getType());
            UnionKeySelector<T1, T2, KEY> unionKeySelector = new UnionKeySelector<>(keySelector1, keySelector2);
​
            DataStream<TaggedUnion<T1, T2>> taggedInput1 = input1
                    .map(new Input1Tagger<T1, T2>())
                    .setParallelism(input1.getParallelism())
                    .returns(unionType);
            DataStream<TaggedUnion<T1, T2>> taggedInput2 = input2
                    .map(new Input2Tagger<T1, T2>())
                    .setParallelism(input2.getParallelism())
                    .returns(unionType);
​
            DataStream<TaggedUnion<T1, T2>> unionStream = taggedInput1.union(taggedInput2);
​
            // we explicitly create the keyed stream to manually pass the key type information in
            windowedStream =
                    new KeyedStream<TaggedUnion<T1, T2>, KEY>(unionStream, unionKeySelector, keyType)
                    .window(windowAssigner);
​
            if (trigger != null) {
                windowedStream.trigger(trigger);
            }
            if (evictor != null) {
                windowedStream.evictor(evictor);
            }
            if (allowedLateness != null) {
                windowedStream.allowedLateness(allowedLateness);
            }
​
            return windowedStream.apply(new CoGroupWindowFunction<T1, T2, T, KEY, W>(function), resultType);
        }
​
        //......
​
    }
​
    //......
}
  • CoGroupedStreams的整体类结构跟JoinedStreams很像,CoGroupedStreams提供where操作来构建Where对象;Where对象主要提供equalTo操作用于构建EqualTo对象;EqualTo对象提供window操作用于构建WithWindow对象;WithWindow可以设置windowAssigner、trigger、evictor、allowedLateness,它提供apply操作;其中一个不同的地方是CoGroupedStreams定义的WithWindow对象的apply操作接收的Function是CoGroupFunction类型,而JoinedStreams定义的WithWindow对象的apply操作接收的Function类型是JoinFunction或FlatJoinFunction

CoGroupFunction

flink-core-1.7.0-sources.jar!/org/apache/flink/api/common/functions/CoGroupFunction.java

代码语言:javascript
复制
@Public
@FunctionalInterface
public interface CoGroupFunction<IN1, IN2, O> extends Function, Serializable {
​
    /**
     * This method must be implemented to provide a user implementation of a
     * coGroup. It is called for each pair of element groups where the elements share the
     * same key.
     *
     * @param first The records from the first input.
     * @param second The records from the second.
     * @param out A collector to return elements.
     *
     * @throws Exception The function may throw Exceptions, which will cause the program to cancel,
     *                   and may trigger the recovery logic.
     */
    void coGroup(Iterable<IN1> first, Iterable<IN2> second, Collector<O> out) throws Exception;
}
  • CoGroupFunction继承了Function、Serializable,它定义了coGroup操作,可以用来实现outer join,其参数使用的是Iterable,而JoinFunction与FlatJoinFunction的join参数使用的是单个对象类型

WrappingFunction

flink-java-1.7.0-sources.jar!/org/apache/flink/api/java/operators/translation/WrappingFunction.java

代码语言:javascript
复制
@Internal
public abstract class WrappingFunction<T extends Function> extends AbstractRichFunction {
​
    private static final long serialVersionUID = 1L;
​
    protected T wrappedFunction;
​
    protected WrappingFunction(T wrappedFunction) {
        this.wrappedFunction = wrappedFunction;
    }
​
    @Override
    public void open(Configuration parameters) throws Exception {
        FunctionUtils.openFunction(this.wrappedFunction, parameters);
    }
​
    @Override
    public void close() throws Exception {
        FunctionUtils.closeFunction(this.wrappedFunction);
    }
​
    @Override
    public void setRuntimeContext(RuntimeContext t) {
        super.setRuntimeContext(t);
​
        FunctionUtils.setFunctionRuntimeContext(this.wrappedFunction, t);
    }
​
    public T getWrappedFunction () {
        return this.wrappedFunction;
    }
}
  • WrappingFunction继承了AbstractRichFunction,这里它覆盖了父类的open、close、setRuntimeContext方法,用于管理wrappedFunction

JoinCoGroupFunction

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/JoinedStreams.java

代码语言:javascript
复制
    /**
     * CoGroup function that does a nested-loop join to get the join result.
     */
    private static class JoinCoGroupFunction<T1, T2, T>
            extends WrappingFunction<JoinFunction<T1, T2, T>>
            implements CoGroupFunction<T1, T2, T> {
        private static final long serialVersionUID = 1L;
​
        public JoinCoGroupFunction(JoinFunction<T1, T2, T> wrappedFunction) {
            super(wrappedFunction);
        }
​
        @Override
        public void coGroup(Iterable<T1> first, Iterable<T2> second, Collector<T> out) throws Exception {
            for (T1 val1: first) {
                for (T2 val2: second) {
                    out.collect(wrappedFunction.join(val1, val2));
                }
            }
        }
    }
  • JoinCoGroupFunction继承了WrappingFunction,同时实现CoGroupFunction接口定义的coGroup方法,默认是遍历第一个集合,对其每个元素遍历第二个集合,挨个执行wrappedFunction.join,然后发射join数据
  • JoinedStreams定义了私有静态类JoinCoGroupFunction,JoinedStreams的WithWindow对象的apply方法内部使用它将JoinFunction进行包装,然后去调用CoGroupedStreams的WithWindow的apply方法
  • JoinFunction定义的join方法,接收的是两个对象类型参数,而JoinCoGroupFunction定义的coGroup方法,接收的两个Iterable类型参数

FlatJoinCoGroupFunction

flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/datastream/JoinedStreams.java

代码语言:javascript
复制
    /**
     * CoGroup function that does a nested-loop join to get the join result. (FlatJoin version)
     */
    private static class FlatJoinCoGroupFunction<T1, T2, T>
            extends WrappingFunction<FlatJoinFunction<T1, T2, T>>
            implements CoGroupFunction<T1, T2, T> {
        private static final long serialVersionUID = 1L;
​
        public FlatJoinCoGroupFunction(FlatJoinFunction<T1, T2, T> wrappedFunction) {
            super(wrappedFunction);
        }
​
        @Override
        public void coGroup(Iterable<T1> first, Iterable<T2> second, Collector<T> out) throws Exception {
            for (T1 val1: first) {
                for (T2 val2: second) {
                    wrappedFunction.join(val1, val2, out);
                }
            }
        }
    }
  • FlatJoinCoGroupFunction继承了WrappingFunction,同时实现CoGroupFunction接口定义的coGroup方法,默认是遍历第一个集合,对其每个元素遍历第二个集合,挨个执行wrappedFunction.join,然后发射join数据
  • JoinedStreams定义了私有静态类FlatJoinCoGroupFunction,JoinedStreams的WithWindow对象的apply方法内部使用它将FlatJoinFunction进行包装,然后去调用CoGroupedStreams的WithWindow的apply方法
  • FlatJoinFunction定义的join方法,接收的是两个对象类型参数,而FlatJoinCoGroupFunction定义的coGroup方法,接收的两个Iterable类型参数

小结

  • DataStream提供了join方法,用于执行join操作,它返回的是JoinedStreams;JoinedStreams主要是提供where操作来构建Where对象;Where对象主要提供equalTo操作用于构建EqualTo对象;EqualTo对象提供window操作用于构建WithWindow对象;WithWindow可以设置windowAssigner、trigger、evictor、allowedLateness,它提供apply操作
  • apply操作可以接收JoinFunction或者FlatJoinFunction,它内部是使用DataStream的coGroup方法创建CoGroupedStreams,之后将自身的where及equalTo的keySelector、windowAssigner、trigger、evictor、allowedLateness都设置给CoGroupedStreams,最后调用CoGroupedStreams的WithWindow对象的apply方法;JoinFunction及FlatJoinFunction都继承了Function、Serializable,它定义了join操作,默认是inner join的语义,如果需要outer join,可以使用CoGroupFunction;而FlatJoinFunction与JoinFunction的join的不同之处的在于FlatJoinFunction的join方法多了Collector参数,可以用来发射0条、1条或者多条数据,所以是Flat命名
  • CoGroupedStreams的WithWindow对象的apply方法与JoinedStreams的WithWindow对象的apply方法参数不同,CoGroupedStreams的WithWindow的apply方法接收的是CoGroupFunction,因而JoinedStreams的WithWindow对象的apply方法内部将JoinFunction或者FlatJoinFunction包装为CoGroupFunction(JoinFunction使用JoinCoGroupFunction包装,FlatJoinFunction使用FlatJoinCoGroupFunction包装),然后去调用CoGroupedStreams的WithWindow的apply方法;JoinCoGroupFunction与FlatJoinCoGroupFunction都继承了WrappingFunction(它继承了AbstractRichFunction,这里它覆盖了父类的open、close、setRuntimeContext方法,用于管理wrappedFunction),同时实现CoGroupFunction接口定义的coGroup方法,不同的是一个是包装JoinFunction,一个是包装FlatJoinFunction,不同的是后者是包装FlatJoinFunction,因而join方法多传递了out参数

doc

原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。

如有侵权,请联系 cloudcommunity@tencent.com 删除。

原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。

如有侵权,请联系 cloudcommunity@tencent.com 删除。

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目录
  • 实例
  • DataStream.join
  • JoinedStreams
  • Where
  • EqualTo
  • WithWindow
    • JoinFunction
      • FlatJoinFunction
      • CoGroupedStreams
        • CoGroupFunction
          • WrappingFunction
            • JoinCoGroupFunction
              • FlatJoinCoGroupFunction
              • 小结
              • doc
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