How to get output of the values that are not matched in filter function in Apache flink

Question

I am newbie to Apache flink i am trying to filter words that starts with letter "N" and i am getting output but how can i get words which don't starts with word "N" below is the code i am using

package DataStream;

import org.apache.flink.api.common.functions.FilterFunction;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;

public class WordStream {

    public static void main(String[] args) throws Exception {

        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        DataStream<String> inputData = env.socketTextStream("localhost", 9999);

        DataStream<String> filterData = inputData.filter(new FilterFunction<String>() {

            /**
             * 
             */
            private static final long serialVersionUID = 1L;

            @Override
            public boolean filter(String value) throws Exception {
                return value.startsWith("N");
            }
        });

        DataStream<Tuple2<String, Integer>> tokenize = filterData
                .flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {

                    @Override
                    public void flatMap(String value, Collector<Tuple2<String, Integer>> out) throws Exception {
                        out.collect(new Tuple2<String, Integer>(value, Integer.valueOf(1)));

                    }
                });

        DataStream<Tuple2<String, Integer>> counts = tokenize.keyBy(0).sum(1);

        counts.print();

        env.execute("WordStream");

    }

}

Can you suggest how to capture not matched words to another stream.

Answer 1

I think you can make use of side-output to achieve this. Just emit the matched elements in actual collector and unmatched element with side-output tag using ProcessFunction, then fetch the side-output elements from the main stream.

For an example, your code can be changed something like this,

package datastream;


import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.ProcessFunction;
import org.apache.flink.util.Collector;
import org.apache.flink.util.OutputTag;

public class WordStream {

    public static void main(String[] args) throws Exception {

        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        DataStream<String> inputData = env.socketTextStream("localhost", 9999);

        // Initialize side-output tag to collect the un-matched elements 
        OutputTag<Tuple2<String, Integer>> unMatchedSideOutput = new OutputTag<Tuple2<String, Integer>>("unmatched-side-output") {};

        SingleOutputStreamOperator<Tuple2<String, Integer>> tokenize = inputData
                .process(new ProcessFunction<String, Tuple2<String, Integer>>() {
                    @Override
                    public void processElement(String value, Context ctx, Collector<Tuple2<String, Integer>> out) {
                        if (value.startsWith("N")) {
                            // Emit the data to actual collector
                            out.collect(new Tuple2<>("Matched=" + value, Integer.valueOf(1)));
                        } else {
                            // Emit the un-matched data to side output
                            ctx.output(unMatchedSideOutput, new Tuple2<>("UnMatched=" + value, Integer.valueOf(1)));
                        }
                    }
                });

        DataStream<Tuple2<String, Integer>> count = tokenize.keyBy(0).sum(1);

        // Fetch the un-matched element using side-output tag and process it
        DataStream<Tuple2<String, Integer>> unMatchedCount = tokenize.getSideOutput(unMatchedSideOutput).keyBy(0).sum(1);

        count.print();

        unMatchedCount.print();

        env.execute("WordStream");

    }
}

Note: I slightly changed the emitted value with prefix Matched= and UnMatched= to get the clear understanding in the output.

For the below input,

Hello
Nevermind
Hello

I get the following output,

3> (UnMatched=Hello,1)
4> (Matched=Nevermind,1)
3> (UnMatched=Hello,2)