Flink实战之Flink SQL中的Map、Array、Row

Flink sql支持Map、Array、Row类型，这几种类型在DDL中如何定义、如何获取、如何构造，本文做个总结。

以如下数据作为样例：

{
     
    "id":1238123899121,
    "name":"asdlkjasjkdla998y1122",
    "date":"1990-10-14",
    "obj":{
     
        "time1":"12:12:43Z",
        "str":"sfasfafs",
        "lg":2324342345
    },
    "arr":[
        {
     
            "f1":"f1str11",
            "f2":134
        },
        {
     
            "f1":"f1str22",
            "f2":555
        }
    ],
    "time":"12:12:43Z",
    "timestamp":"1990-10-14T12:12:43Z",
    "map":{
     
        "flink":123
    },
    "mapinmap":{
     
        "inner_map":{
     
            "key":234
        }
    }
}

定义

CREATE TABLE json_source (
    id            BIGINT,
    name          STRING,
    `date`        DATE,
    obj           ROW<time1 TIME,str STRING,lg BIGINT>,
    arr           ARRAY<ROW<f1 STRING,f2 INT>>,
    `time`        TIME,
    `timestamp`   TIMESTAMP(3),
    `map`         MAP<STRING,BIGINT>,
    mapinmap      MAP<STRING,MAP<STRING,INT>>,
    proctime as PROCTIME()
 ) WITH (
    'connector.type' = 'kafka',  
    'connector.topic' = 'test',  
    'connector.properties.zookeeper.connect' = 'localhost:2181',
    'connector.properties.bootstrap.servers' = 'localhost:9092',   
    'connector.properties.group.id' = 'testGroup',    
    'connector.version'='universal',  
    'format.type' = 'json',     
    'connector.startup-mode'='latest-offset' 
);

获取

select id, name,`date`,obj.str,arr[1].f1,`map`['flink'],mapinmap['inner_map']['key'] from json_source;
//注意数组index从1开始

构造

insert into json_source select 111 as id,'name' as name,Row(CURRENT_TIME,'ss',123) as obj,Array[Row('f',1),Row('s',2)] as arr,Map['k1','v1','k2','v2'] as `map`,Map['inner_map',Map['k','v']] as mapinmap;