基于docker安装flink
注意:当你在流式查询上使用这种模式时,Flink 会将结果持续的打印在当前的控制台上。如果流式查询的输入是有限数据集,那么 Flink 在处理完所有的输入数据之后,作业会自动停止,同时控制台上的打印也会自动停止。滚动窗口可以定义在事件时间(批处理、流处理)或处理时间(流处理)上。Tableau模式(tableau mode)更接近传统的数据库,会将执行的结果以制表的形式直接打在屏幕之上。表格模式(
文章目录
- 环境准备
- Flink
- docker-compose方式
- 二进制部署
- Kafka
- Mysql
- Flink 执行 SQL命令
- 进入SQL客户端CLI
- 执行SQL查询
- 表格模式
- 变更日志模式
- Tableau模式
- 窗口计算
- 窗口计算
- 滚动窗口demo
- 滑动窗口
- 踩坑
环境准备
Flink
docker-compose方式
version: "3"
services:
jobmanager:
image: flink:latest
expose:
- "6123"
ports:
- "8081:8081"
command: jobmanager
environment:
- JOB_MANAGER_RPC_ADDRESS=jobmanager
taskmanager:
image: flink:latest
expose:
- "6121"
- "6122"
depends_on:
- jobmanager
command: taskmanager
links:
- "jobmanager:jobmanager"
environment:
- JOB_MANAGER_RPC_ADDRESS=jobmanager
前端访问地址: http://192.168.56.112:8081/#/overview
二进制部署
wget https://archive.apache.org/dist/flink/flink-1.13.3/flink-1.13.3-bin-scala_2.11.tgz
vim conf/flink-conf.yaml
jobmanager.rpc.address: 192.168.56.112 # 修改为本机ip
./bin/start-cluster.sh
Kafka
version: '2'
services:
zookeeper:
image: wurstmeister/zookeeper ## 镜像
ports:
- "2181:2181" ## 对外暴露的端口号
kafka:
image: wurstmeister/kafka ## 镜像
volumes:
- /etc/localtime:/etc/localtime ## 挂载位置(kafka镜像和宿主机器之间时间保持一直)
ports:
- "9092:9092"
environment:
KAFKA_ADVERTISED_HOST_NAME: 192.168.56.112 ## 修改:宿主机IP
KAFKA_ZOOKEEPER_CONNECT: 192.168.56.112:2181 ## 卡夫卡运行是基于zookeeper的
kafka-manager:
image: sheepkiller/kafka-manager ## 镜像:开源的web管理kafka集群的界面
environment:
ZK_HOSTS: ## 修改:宿主机IP
ports:
- "9000:9000"
Mysql
docker run -d -p3306:3306 --name=mysql57 -e MYSQL_ROOT_PASSWORD=111111 mysql:5.7
Flink 执行 SQL命令
进入SQL客户端CLI
docker exec -it flink_jobmanager_1 /bin/bash
./bin/sql-client.sh
执行SQL查询
SELECT 'Hello World';
表格模式
表格模式(table mode)在内存中物化结果,并将结果用规则的分页表格的形式可视化展示出来。执行如下命令启用:
SET sql-client.execution.result-mode = table;
可以使用如下查询语句查看不同模式的的运行结果:
SELECT name, COUNT(*) AS cnt FROM (VALUES ('Bob'), ('Alice'), ('Greg'), ('Bob')) AS NameTable(name) GROUP BY name;
变更日志模式
变更日志模式(changelog mode)不会物化结果。可视化展示由插入(+)和撤销(-)组成的持续查询结果流。
SET sql-client.execution.result-mode = changelog;
Tableau模式
Tableau模式(tableau mode)更接近传统的数据库,会将执行的结果以制表的形式直接打在屏幕之上。具体显示的内容取决于作业执行模式(execution.type):
SET sql-client.execution.result-mode = tableau;
注意:当你在流式查询上使用这种模式时,Flink 会将结果持续的打印在当前的控制台上。如果流式查询的输入是有限数据集,那么 Flink 在处理完所有的输入数据之后,作业会自动停止,同时控制台上的打印也会自动停止。如果你想提前结束这个查询,那么可以直接使用 CTRL-C 按键,这个会停止作业同时停止在控制台上的打印。
窗口计算
TUMBLE(time_attr, interval) 定义一个滚动窗口。滚动窗口把行分配到有固定持续时间( interval )的不重叠的连续窗口。比如,5 分钟的滚动窗口以 5 分钟为间隔对行进行分组。滚动窗口可以定义在事件时间(批处理、流处理)或处理时间(流处理)上。
窗口计算
TUMBLE(time_attr, interval) 定义一个滚动窗口。滚动窗口把行分配到有固定持续时间( interval )的不重叠的连续窗口。比如,5 分钟的滚动窗口以 5 分钟为间隔对行进行分组。滚动窗口可以定义在事件时间(批处理、流处理)或处理时间(流处理)上。
滚动窗口demo
根据订单信息使用kafka作为数据源表,JDBC作为数据结果表统计用户在5秒内的订单数量,并根据窗口的订单id和窗口开启时间作为主键,将结果实时统计到JDBC中:
- 在MySQL的flink数据库下创建表order_count,创建语句如下:
CREATE TABLE `flink`.`order_count` (
`user_id` VARCHAR(32) NOT NULL,
`window_start` TIMESTAMP NOT NULL,
`window_end` TIMESTAMP NULL,
`total_num` BIGINT UNSIGNED NULL,
PRIMARY KEY (`user_id`, `window_start`)
) ENGINE = InnoDB
DEFAULT CHARACTER SET = utf8mb4
COLLATE = utf8mb4_general_ci;
- 创建flink opensource sql作业,并提交运行作业
CREATE TABLE orders (
order_id string,
order_channel string,
order_time timestamp(3),
pay_amount double,
real_pay double,
pay_time string,
user_id string,
user_name string,
area_id string,
watermark for order_time as order_time - INTERVAL '3' SECOND
) WITH (
'connector' = 'kafka',
'topic' = 'order_topic',
'properties.bootstrap.servers' = '192.168.56.112:9092',
'properties.group.id' = 'order_group',
'scan.startup.mode' = 'latest-offset',
'format' = 'json'
);
CREATE TABLE jdbcSink (
user_id string,
window_start timestamp(3),
window_end timestamp(3),
total_num BIGINT,
primary key (user_id, window_start) not enforced
) WITH (
'connector' = 'jdbc',
'url' = 'jdbc:mysql://192.168.56.112:3306/flink',
'table-name' = 'order_count',
'username' = 'root',
'password' = '111111',
'sink.buffer-flush.max-rows' = '1'
);
SELECT
'WINDOW',-- window_start,window_end,
group_key,record_num,create_time,
SUM(record_num) OVER w AS sum_amount
FROM temp
WINDOW w AS (
PARTITION BY group_key
ORDER BY rowtime
RANGE BETWEEN INTERVAL '10' SECOND PRECEDING AND CURRENT ROW)
select
user_id,
TUMBLE_START(order_time, INTERVAL '5' SECOND),
TUMBLE_END(order_time, INTERVAL '5' SECOND),
COUNT(*) from orders
GROUP BY user_id, TUMBLE(order_time, INTERVAL '5' SECOND) having count(*) > 3;
SELECT
'WINDOW',
user_id,order_id,real_pay,order_time
COUNT(*) OVER w AS sum_amount
FROM orders
WINDOW w AS (
PARTITION BY user_id
ORDER BY order_time
RANGE BETWEEN INTERVAL '60' SECOND PRECEDING AND CURRENT ROW)
insert into jdbcSink select
user_id,
TUMBLE_START(order_time, INTERVAL '5' SECOND),
TUMBLE_END(order_time, INTERVAL '5' SECOND),
COUNT(*) from orders
GROUP BY user_id, TUMBLE(order_time, INTERVAL '5' SECOND) having count(*) > 3;
- Kafka 相关操作
bin/kafka-topics.sh --zookeeper 192.168.56.112:2181 --list
bin/kafka-topics.sh --zookeeper 192.168.56.112:2181 --create --replication-factor 1 --partitions 1 --topic order_topic
bin/kafka-console-producer.sh --broker-list 192.168.56.112:9092 --topic order_topic
bin/kafka-console-consumer.sh --bootstrap-server 192.168.56.112:9092 --topic order_topic --from-beginning
bin/kafka-topics.sh --zookeeper 192.168.56.112:2181 --describe --topic order_topic
bin/kafka-topics.sh --zookeeper 192.168.56.112:2181 --delete --topic order_topic
发送数据样例
{"order_id":"202103241000000001", "order_channel":"webShop", "order_time":"2023-09-26 15:20:11", "pay_amount":"100.00", "real_pay":"100.00", "pay_time":"2021-03-24 10:02:03", "user_id":"0001", "user_name":"Alice", "area_id":"330106"}
{"order_id":"202103241000000001", "order_channel":"webShop", "order_time":"2023-08-10 17:28:10", "pay_amount":"100.00", "real_pay":"100.00", "pay_time":"2021-03-24 10:02:03", "user_id":"0001", "user_name":"Alice", "area_id":"330106"}
{"order_id":"202103241000000001", "order_channel":"webShop", "order_time":"2023-08-10 17:29:10", "pay_amount":"100.00", "real_pay":"100.00", "pay_time":"2021-03-24 10:02:03", "user_id":"0001", "user_name":"Alice", "area_id":"330106"}
{"order_id":"202103241000000001", "order_channel":"webShop", "order_time":"2023-08-10 17:29:10", "pay_amount":"100.00", "real_pay":"100.00", "pay_time":"2021-03-24 10:02:03", "user_id":"0001", "user_name":"Alice", "area_id":"330106"}
{"order_id":"202103241000000001", "order_channel":"webShop", "order_time":"2023-08-10 17:29:10", "pay_amount":"100.00", "real_pay":"100.00", "pay_time":"2021-03-24 10:02:03", "user_id":"0001", "user_name":"Alice", "area_id":"330106"}
{"order_id":"202103241000000001", "order_channel":"webShop", "order_time":"2023-08-10 17:30:10", "pay_amount":"100.00", "real_pay":"100.00", "pay_time":"2021-03-24 10:02:03", "user_id":"0001", "user_name":"Alice", "area_id":"330106"}
{"order_id":"202103241000000001", "order_channel":"webShop", "order_time":"2023-08-10 17:30:10", "pay_amount":"100.00", "real_pay":"100.00", "pay_time":"2021-03-24 10:02:03", "user_id":"0001", "user_name":"Alice", "area_id":"330106"}
滑动窗口
SELECT * FROM TABLE(
HOP(TABLE orders, DESCRIPTOR(order_time), INTERVAL '2' SECOND, INTERVAL '10' SECOND));
SELECT * FROM TABLE(
HOP(
DATA => TABLE orders,
TIMECOL => DESCRIPTOR(order_time),
SLIDE => INTERVAL '5' MINUTES,
SIZE => INTERVAL '10' MINUTES));
SELECT window_start, window_end, SUM(pay_amount)
FROM TABLE(
HOP(TABLE orders, DESCRIPTOR(order_time), INTERVAL '2' SECOND, INTERVAL '10' SECOND))
GROUP BY window_start, window_end;
踩坑
- Could not find any factory for identifier ‘kafka’ that implements ‘org.apache.flink.table.factories.DynamicTableFactory’ in the classpath.
查看flink version
flink-sql-connector-kafka-1.17.1.jar
https://mvnrepository.com/artifact/org.apache.flink/flink-sql-connector-kafka/1.17.1
下载对应版本jar,放到lib目录下,重启
-
Could not find any factory for identifier ‘jdbc’ that implements 'org.apache.flink.table.factories.DynamicTableFactory
flink-connector-jdbc-3.1.0-1.17.jar
https://repo1.maven.org/maven2/org/apache/flink/flink-connector-jdbc/3.1.0-1.17/flink-connector-jdbc-3.1.0-1.17.jar -
Caused by: java.lang.ClassNotFoundException: com.mysql.jdbc.Driver
https://mvnrepository.com/artifact/com.mysql/mysql-connector-j/8.0.31
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