本文主要研究一下flink的ProcessFunction
import org.apache.flink.api.common.state.ValueState; import org.apache.flink.api.common.state.ValueStateDescriptor; import org.apache.flink.api.java.tuple.Tuple2; import org.apache.flink.configuration.Configuration; import org.apache.flink.streaming.api.functions.ProcessFunction; import org.apache.flink.streaming.api.functions.ProcessFunction.Context; import org.apache.flink.streaming.api.functions.ProcessFunction.OnTimerContext; import org.apache.flink.util.Collector; // the source data stream DataStream<Tuple2<String, String>> stream = ...; // apply the process function onto a keyed stream DataStream<Tuple2<String, Long>> result = stream .keyBy(0) .process(new CountWithTimeoutFunction()); /** * The data type stored in the state */ public class CountWithTimestamp { public String key; public long count; public long lastModified; } /** * The implementation of the ProcessFunction that maintains the count and timeouts */ public class CountWithTimeoutFunction extends ProcessFunction<Tuple2<String, String>, Tuple2<String, Long>> { /** The state that is maintained by this process function */ private ValueState<CountWithTimestamp> state; @Override public void open(Configuration parameters) throws Exception { state = getRuntimeContext().getState(new ValueStateDescriptor<>("myState", CountWithTimestamp.class)); } @Override public void processElement(Tuple2<String, String> value, Context ctx, Collector<Tuple2<String, Long>> out) throws Exception { // retrieve the current count CountWithTimestamp current = state.value(); if (current == null) { current = new CountWithTimestamp(); current.key = value.f0; } // update the state's count current.count++; // set the state's timestamp to the record's assigned event time timestamp current.lastModified = ctx.timestamp(); // write the state back state.update(current); // schedule the next timer 60 seconds from the current event time ctx.timerService().registerEventTimeTimer(current.lastModified + 60000); } @Override public void onTimer(long timestamp, OnTimerContext ctx, Collector<Tuple2<String, Long>> out) throws Exception { // get the state for the key that scheduled the timer CountWithTimestamp result = state.value(); // check if this is an outdated timer or the latest timer if (timestamp == result.lastModified + 60000) { // emit the state on timeout out.collect(new Tuple2<String, Long>(result.key, result.count)); } } }
flink-streaming-java_2.11-1.7.0-sources.jar!/org/apache/flink/streaming/api/functions/ProcessFunction.java
@PublicEvolving public abstract class ProcessFunction<I, O> extends AbstractRichFunction { private static final long serialVersionUID = 1L; public abstract void processElement(I value, Context ctx, Collector<O> out) throws Exception; public void onTimer(long timestamp, OnTimerContext ctx, Collector<O> out) throws Exception {} public abstract class Context { public abstract Long timestamp(); public abstract TimerService timerService(); public abstract <X> void output(OutputTag<X> outputTag, X value); } public abstract class OnTimerContext extends Context { public abstract TimeDomain timeDomain(); } }
可以通过RuntimeContext获取keyed state
可以通过RuntimeContext获取keyed state