Flink 复杂事件处理

Flink Complex Event Processing

我有一个从套接字读取并检测模式的 flink cep 代码。假设模式(单词)是 'alert'。如果单词警报出现五次或更多次,则应创建警报。但是我收到输入不匹配错误。 Flink 版本为 1.3.0。提前致谢!!

package pattern;

import org.apache.flink.cep.CEP;
import org.apache.flink.cep.PatternStream;
import org.apache.flink.cep.pattern.Pattern;
import org.apache.flink.cep.pattern.conditions.IterativeCondition;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;

import java.util.List;
import java.util.Map;

    public class cep {

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


             StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

                DataStreamSource<String> dss = env.socketTextStream("localhost", 3005);

                dss.print();

                Pattern<String,String> pattern = Pattern.<String> begin("first")
                        .where(new IterativeCondition<String>() {
                            @Override
                            public boolean filter(String word, Context<String> context) throws Exception {
                                return word.equals("alert");
                            }
                        })
                        .times(5);


                PatternStream<String> patternstream = CEP.pattern(dss, pattern);

                DataStream<String> alerts = patternstream
                        .flatSelect((Map<String,List<String>> in, Collector<String> out) -> {

                            String first = in.get("first").get(0);

                            for (int i = 0; i < 6; i++ ) {

                                out.collect(first);

                            }


                        });

                alerts.print();

                env.execute();

            }

    }

所以我已经得到了可以工作的代码。这是工作解决方案,

    package pattern;

    import org.apache.flink.cep.CEP;
    import org.apache.flink.cep.PatternSelectFunction;
    import org.apache.flink.cep.PatternStream;
    import org.apache.flink.cep.pattern.Pattern;
    import org.apache.flink.cep.pattern.conditions.IterativeCondition;
    import org.apache.flink.streaming.api.datastream.DataStream;
    import org.apache.flink.streaming.api.datastream.DataStreamSource;
    import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
    import org.apache.flink.util.Collector;

    import java.util.List;
    import java.util.Map;

    public class cep {

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


             StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

                DataStreamSource<String> dss = env.socketTextStream("localhost", 3005);

                dss.print();

                Pattern<String,String> pattern = Pattern.<String> begin("first")
                        .where(new IterativeCondition<String>() {
                            @Override
                            public boolean filter(String word, Context<String> context) throws Exception {
                                return word.equals("alert");
                            }
                        })
                        .times(5);

                PatternStream<String> patternstream = CEP.pattern(dss, pattern);

                DataStream<String> alerts = patternstream
                        .select(new PatternSelectFunction<String, String>() {
                            @Override
                            public String select(Map<String, List<String>> in) throws Exception {

                                String first = in.get("first").get(0);

                                if(first.equals("alert")){

                                    return ("5 or more alerts");
                                }
                                else{

                                    return (" ");
                                }
                            }
                        });

                alerts.print();

                env.execute();

            }

    }

只是对原来的问题做一些澄清。在 1.3.0 中存在一个错误,导致无法使用 lambda 作为 select/flatSelect 的参数。

它已在 1.3.1 中修复,因此您的第一个版本的代码将适用于 1.3.1。


此外,我认为您误解了 times 量词。它匹配确切的次数。因此,在您的情况下,只有当事件恰好匹配 3 次而不是 3 次或更多时,它才会 return。