MySQL？Flink实时流处理的核心技术之窗口机制（flink实时写入doris）真没想到

🌐 经济型：买域名、轻量云服务器、用途：游戏网站等《腾讯云》特点：特价机便宜适合初学者用点我优惠购买

🚀 拓展型：买域名、轻量云服务器、用途：游戏网站等《阿里云》特点：中档服务器便宜域名备案事多点我优惠购买

🛡️ 稳定型：买域名、轻量云服务器、用途：游戏网站等《西部数码》特点：比上两家略贵但是稳定性超好事也少点我优惠购买

#1.创建source表
CREATE TABLE source_table (
user_id STRING,
price BIGINT,
`timestamp` bigint,
row_time AS TO_TIMESTAMP(FROM_UNIXTIME(`timestamp`)),
watermark for row_time as row_time – interval ‘0’ second
) WITH (
‘connector’=’socket’,
‘hostname’=’node1’,
‘port’=’9999’,
‘format’=’csv’
);
#2.语法
tumble(事件时间列,窗口大小)
窗口大小是用户自定义的。比如30分钟、1小时等。
直接把tumble窗口放在group by语句后即可。
比如：tumble(row_time,interval ‘5’ second)
含义：定义一个5秒大小的滚动窗口。
#3.数据处理
select
user_id,
count(*) as pv,
sum(price) as sum_price,
UNIX_TIMESTAMP(CAST(tumble_start(row_time, interval ‘5’ second) AS STRING)) * 1000 as window_start,
UNIX_TIMESTAMP(CAST(tumble_end(row_time, interval ‘5’ second) AS STRING)) * 1000 as window_end
from source_table
group by
user_id,
tumble(row_time, interval ‘5’ second);