Package org.apache.flink.api.common.functions.util

Class AbstractRuntimeUDFContext

    • Method Detail

      • createSerializer

        public <T> TypeSerializer<T> createSerializer​(TypeInformation<T> typeInformation)
        Description copied from interface: RuntimeContext
        Create a serializer for a given type.
        Specified by:
        createSerializer in interface RuntimeContext
        Parameters:
        typeInformation - the type information of the object to be serialized
        Returns:
        the serializer for the given type

      • isObjectReuseEnabled

        public boolean isObjectReuseEnabled()
        Description copied from interface: RuntimeContext
        Check if object reuse is enabled.
        Specified by:
        isObjectReuseEnabled in interface RuntimeContext
        Returns:
        true if object reuse is enabled, false otherwise

      • getMetricGroup

        public org.apache.flink.metrics.groups.OperatorMetricGroup getMetricGroup()
        Description copied from interface: RuntimeContext
        Returns the metric group for this parallel subtask.
        Specified by:
        getMetricGroup in interface RuntimeContext
        Returns:
        The metric group for this parallel subtask.

      • addAccumulator

        public <V,​A extends Serializable> void addAccumulator​(String name,
                                                            Accumulator<V,​A> accumulator)
        Description copied from interface: RuntimeContext
        Add this accumulator. Throws an exception if the accumulator already exists in the same Task. Note that the Accumulator name must have an unique name across the Flink job. Otherwise you will get an error when incompatible accumulators from different Tasks are combined at the JobManager upon job completion.
        Specified by:
        addAccumulator in interface RuntimeContext

      • getAccumulator

        public <V,​A extends Serializable> Accumulator<V,​A> getAccumulator​(String name)
        Description copied from interface: RuntimeContext
        Get an existing accumulator object. The accumulator must have been added previously in this local runtime context.

        Throws an exception if the accumulator does not exist or if the accumulator exists, but with different type.

        Specified by:
        getAccumulator in interface RuntimeContext

      • getUserCodeClassLoader

        public ClassLoader getUserCodeClassLoader()
        Description copied from interface: RuntimeContext
        Gets the ClassLoader to load classes that are not in system's classpath, but are part of the jar file of a user job.
        Specified by:
        getUserCodeClassLoader in interface RuntimeContext
        Returns:
        The ClassLoader for user code classes.

      • registerUserCodeClassLoaderReleaseHookIfAbsent

        public void registerUserCodeClassLoaderReleaseHookIfAbsent​(String releaseHookName,
                                                           Runnable releaseHook)
        Description copied from interface: RuntimeContext
        Registers a custom hook for the user code class loader release.

        The release hook is executed just before the user code class loader is being released. Registration only happens if no hook has been registered under this name already.

        Specified by:
        registerUserCodeClassLoaderReleaseHookIfAbsent in interface RuntimeContext
        Parameters:
        releaseHookName - name of the release hook.
        releaseHook - release hook which is executed just before the user code class loader is being released

      • getState

        @PublicEvolving
public <T> ValueState<T> getState​(ValueStateDescriptor<T> stateProperties)
        Description copied from interface: RuntimeContext
        Gets a handle to the system's key/value state. The key/value state is only accessible if the function is executed on a KeyedStream. On each access, the state exposes the value for the key of the element currently processed by the function. Each function may have multiple partitioned states, addressed with different names.

        Because the scope of each value is the key of the currently processed element, and the elements are distributed by the Flink runtime, the system can transparently scale out and redistribute the state and KeyedStream.

        The following code example shows how to implement a continuous counter that counts how many times elements of a certain key occur, and emits an updated count for that element on each occurrence. 

        
 DataStream<MyType> stream = ...;
 KeyedStream<MyType> keyedStream = stream.keyBy("id");

 keyedStream.map(new RichMapFunction<MyType, Tuple2<MyType, Long>>() {

     private ValueState<Long> state;

     public void open(Configuration cfg) {
         state = getRuntimeContext().getState(
                 new ValueStateDescriptor<Long>("count", LongSerializer.INSTANCE, 0L));
     }

     public Tuple2<MyType, Long> map(MyType value) {
         long count = state.value() + 1;
         state.update(count);
         return new Tuple2<>(value, count);
     }
 });
        Specified by:
        getState in interface RuntimeContext
        Type Parameters:
        T - The type of value stored in the state.
        Parameters:
        stateProperties - The descriptor defining the properties of the stats.
        Returns:
        The partitioned state object.

      • getListState

        @PublicEvolving
public <T> ListState<T> getListState​(ListStateDescriptor<T> stateProperties)
        Description copied from interface: RuntimeContext
        Gets a handle to the system's key/value list state. This state is similar to the state accessed via RuntimeContext.getState(ValueStateDescriptor), but is optimized for state that holds lists. One can add elements to the list, or retrieve the list as a whole.

        This state is only accessible if the function is executed on a KeyedStream. 

        
 DataStream<MyType> stream = ...;
 KeyedStream<MyType> keyedStream = stream.keyBy("id");

 keyedStream.map(new RichFlatMapFunction<MyType, List<MyType>>() {

     private ListState<MyType> state;

     public void open(Configuration cfg) {
         state = getRuntimeContext().getListState(
                 new ListStateDescriptor<>("myState", MyType.class));
     }

     public void flatMap(MyType value, Collector<MyType> out) {
         if (value.isDivider()) {
             for (MyType t : state.get()) {
                 out.collect(t);
             }
         } else {
             state.add(value);
         }
     }
 });
        Specified by:
        getListState in interface RuntimeContext
        Type Parameters:
        T - The type of value stored in the state.
        Parameters:
        stateProperties - The descriptor defining the properties of the stats.
        Returns:
        The partitioned state object.

      • getReducingState

        @PublicEvolving
public <T> ReducingState<T> getReducingState​(ReducingStateDescriptor<T> stateProperties)
        Description copied from interface: RuntimeContext
        Gets a handle to the system's key/value reducing state. This state is similar to the state accessed via RuntimeContext.getState(ValueStateDescriptor), but is optimized for state that aggregates values.

        This state is only accessible if the function is executed on a KeyedStream. 

        
 DataStream<MyType> stream = ...;
 KeyedStream<MyType> keyedStream = stream.keyBy("id");

 keyedStream.map(new RichMapFunction<MyType, List<MyType>>() {

     private ReducingState<Long> state;

     public void open(Configuration cfg) {
         state = getRuntimeContext().getReducingState(
                 new ReducingStateDescriptor<>("sum", (a, b) -> a + b, Long.class));
     }

     public Tuple2<MyType, Long> map(MyType value) {
         state.add(value.count());
         return new Tuple2<>(value, state.get());
     }
 });
        Specified by:
        getReducingState in interface RuntimeContext
        Type Parameters:
        T - The type of value stored in the state.
        Parameters:
        stateProperties - The descriptor defining the properties of the stats.
        Returns:
        The partitioned state object.

      • getAggregatingState

        @PublicEvolving
public <IN,​ACC,​OUT> AggregatingState<IN,​OUT> getAggregatingState​(AggregatingStateDescriptor<IN,​ACC,​OUT> stateProperties)
        Description copied from interface: RuntimeContext
        Gets a handle to the system's key/value aggregating state. This state is similar to the state accessed via RuntimeContext.getState(ValueStateDescriptor), but is optimized for state that aggregates values with different types.

        This state is only accessible if the function is executed on a KeyedStream. 

        
 DataStream<MyType> stream = ...;
 KeyedStream<MyType> keyedStream = stream.keyBy("id");
 AggregateFunction<...> aggregateFunction = ...

 keyedStream.map(new RichMapFunction<MyType, List<MyType>>() {

     private AggregatingState<MyType, Long> state;

     public void open(Configuration cfg) {
         state = getRuntimeContext().getAggregatingState(
                 new AggregatingStateDescriptor<>("sum", aggregateFunction, Long.class));
     }

     public Tuple2<MyType, Long> map(MyType value) {
         state.add(value);
         return new Tuple2<>(value, state.get());
     }
 });
        Specified by:
        getAggregatingState in interface RuntimeContext
        Type Parameters:
        IN - The type of the values that are added to the state.
        ACC - The type of the accumulator (intermediate aggregation state).
        OUT - The type of the values that are returned from the state.
        Parameters:
        stateProperties - The descriptor defining the properties of the stats.
        Returns:
        The partitioned state object.

      • getMapState

        @PublicEvolving
public <UK,​UV> MapState<UK,​UV> getMapState​(MapStateDescriptor<UK,​UV> stateProperties)
        Description copied from interface: RuntimeContext
        Gets a handle to the system's key/value map state. This state is similar to the state accessed via RuntimeContext.getState(ValueStateDescriptor), but is optimized for state that is composed of user-defined key-value pairs

        This state is only accessible if the function is executed on a KeyedStream. 

        
 DataStream<MyType> stream = ...;
 KeyedStream<MyType> keyedStream = stream.keyBy("id");

 keyedStream.map(new RichMapFunction<MyType, List<MyType>>() {

     private MapState<MyType, Long> state;

     public void open(Configuration cfg) {
         state = getRuntimeContext().getMapState(
                 new MapStateDescriptor<>("sum", MyType.class, Long.class));
     }

     public Tuple2<MyType, Long> map(MyType value) {
         return new Tuple2<>(value, state.get(value));
     }
 });
        Specified by:
        getMapState in interface RuntimeContext
        Type Parameters:
        UK - The type of the user keys stored in the state.
        UV - The type of the user values stored in the state.
        Parameters:
        stateProperties - The descriptor defining the properties of the stats.
        Returns:
        The partitioned state object.

      • getAllocationIDAsString

        @Internal
@VisibleForTesting
public String getAllocationIDAsString()