flink-format_小练习

2、format

1、json

json格式表结构按照字段名和类型进行映射

• 增加依赖

<dependency>
  <groupId>org.apache.flink</groupId>
  <artifactId>flink-json</artifactId>
  <version>1.15.0</version>
</dependency>

• 读取json格式的数据

-- source 表 
CREATE TABLE student_file_json (
    id STRINg,
    name STRING,
    age INT,
    gender STRING,
    clazz STRING
)  WITH (
  'connector' = 'filesystem',           -- 必选：指定连接器类型
  'path' = 'data/students.json',  -- 必选：指定路径
  'format' = 'json' ,                    -- 必选：文件系统连接器指定 format
  'json.ignore-parse-errors' = 'true'
)
-- sink 表
CREATE TABLE print_table 
WITH ('connector' = 'print')
LIKE student_file_json (EXCLUDING ALL)

--执行sql
insert into print_table
select * from student_file_json

• 将数据保存为json格式

-- source 表 
CREATE TABLE student_file_json (
    id STRINg,
    name STRING,
    age INT,
    gender STRING,
    clazz STRING
)  WITH (
  'connector' = 'filesystem',           -- 必选：指定连接器类型
  'path' = 'data/students.json',  -- 必选：指定路径
  'format' = 'json' ,                    -- 必选：文件系统连接器指定 format
  'json.ignore-parse-errors' = 'true'
)


-- kafka sink 
CREATE TABLE student_kafka_sink (
    id STRING,
    name STRING,
    age INT,
    gender STRING,
    clazz STRING
) WITH (
  'connector' = 'kafka',-- 只支持追加的流
  'topic' = 'student_flink_json',
  'properties.bootstrap.servers' = 'master:9092,node1:9092,node2:9092',
  'format' = 'json'
)

-- 执行sql
insert into student_kafka_sink
select * from student_file_json

3、练习

-- 1、使用flink sql 统计每个城市总的车流量
-- 2、source 使用文件source cars_sample.json
-- 3、将统计好的结果保存到mysql中，mysql中只保留最新的结果

• 代码

{"car":"皖A9A7N2",
"city_code":"340500",
"county_code":"340522",
"card":117988031603010,
"camera_id":"00001",
"orientation":"西南",
"road_id":34052055,
"time":1614711895,
"speed":36.38}

-- 1、创建卡口过车source表
CREATE TABLE cars (
    car STRING,
    city_code STRING,
    county_code STRING,
    card BIGINT,
    camera_id STRING,
    orientation STRING,
    road_id BIGINT,
    `time` STRING,
    speed DOUBLE
)  WITH (
  'connector' = 'filesystem',           -- 必选：指定连接器类型
  'path' = 'data/cars_sample.json',  -- 必选：指定路径
  'format' = 'json'                     -- 必选：文件系统连接器指定 format
)

-- 2、创建 mysql sink表

CREATE TABLE city_flow (
  city_code STRING,
  flow BIGINT,
  PRIMARY KEY (city_code) NOT ENFORCED -- 按照主键更新数据
) WITH (
   'connector' = 'jdbc',
   'url' = 'jdbc:mysql://master:3306/bigdata?useUnicode=true&characterEncoding=UTF-8',
   'table-name' = 'city_flow', -- 需要手动到数据库中创建表
   'username' = 'root',
   'password' = '123456'
)
-- 3、在数据库中创建表
CREATE TABLE `city_flow` (
  `city_code` varchar(255) NOT NULL,
  `flow` bigint(20) DEFAULT NULL,
  PRIMARY KEY (`city_code`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

-- 4、统计数据的sql
insert into city_flow
select 
city_code,
count(distinct car) as flow
from 
cars
group by city_code

标签：city,练习,STRING,format,--,flink,json,code
来源： https://www.cnblogs.com/atao-BigData/p/16536898.html