flink: 自定义表函数的用法

package cn.edu.tju.demo3;

import org.apache.flink.api.common.functions.MapFunction;
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.table.api.*;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.descriptors.*;
import org.apache.flink.table.functions.ScalarFunction;
import org.apache.flink.table.functions.TableFunction;
import org.apache.flink.types.Row;

public class Test49 {
    private static String HOST_NAME = "xx.xx.xx.xx";
    private static int PORT = 9999;
    private static String DELIMITER ="\n";


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

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);



        DataStream<String> socketDataInfo =  env.socketTextStream(HOST_NAME, PORT, DELIMITER);
        SingleOutputStreamOperator<DataInfo> dataInfoStream = socketDataInfo.map(new MapFunction<String, DataInfo>() {
            @Override
            public DataInfo map(String value) throws Exception {

                String[] stringList = value.split(",");
                DataInfo dataInfo = new DataInfo(Long.parseLong(
                        stringList[0]), stringList[1], Double.parseDouble(stringList[2]));
                return dataInfo;
            }
        });

        Table dataTable = tableEnv.fromDataStream(dataInfoStream,"ts,info,val");
        tableEnv.registerFunction("myTableFunction", new MyTableFunction());
        Table resultTable = dataTable.select("ts,info,val")
                .joinLateral("myTableFunction(val) as(a,b)")
                        .select("ts,info,a,b");

        tableEnv.createTemporaryView("dataInfo", dataTable);

        Table resultTableSql = tableEnv.sqlQuery(
                "select ts,info,val,a,b from dataInfo,LATERAL TABLE(myTableFunction(val)) as res (a,b)"

        );
        

        tableEnv.toAppendStream(resultTable, Row.class).print();
        tableEnv.toAppendStream(resultTableSql, Row.class).print("sql");

        env.execute("my job");

    }

    public static class DataInfo{
        private long ts;
        private String info;
        private double val;

        public long getTs() {
            return ts;
        }

        public void setTs(long ts) {
            this.ts = ts;
        }

        public String getInfo() {
            return info;
        }

        public void setInfo(String info) {
            this.info = info;
        }

        public double getVal() {
            return val;
        }

        public void setVal(double val) {
            this.val = val;
        }

        @Override
        public String toString() {
            return "DataInfo{" +
                    "ts=" + ts +
                    ", info='" + info + '\'' +
                    ", val='" + val + '\'' +
                    '}';
        }

        public DataInfo(long ts, String info, double val) {
            this.ts = ts;
            this.info = info;
            this.val = val;
        }

        public DataInfo() {

        }
    }

    //自定义表函数，必须定义一个public的 名字为eval方法
    public static class MyTableFunction extends TableFunction<Tuple2<Double, Double>>{
        public void eval(double d){
            collect(new Tuple2<>(d, Math.floor(d)));
        }
    }
}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118

nc -lk 9999
输入：

1690000001,ffff,87.12

1
2

执行结果