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README
Apache-2.0

flinkStreamSQL

  • 基于开源的flink,对其实时sql进行扩展
  • 自定义create table 语法(包括源表,输出表,维表)
  • 自定义create view 语法
  • 自定义create function 语法
  • 实现了流与维表的join
  • 支持原生FLinkSQL所有的语法
  • 扩展了输入和输出的性能指标到promethus

新特性:

  • 1.kafka源表支持not null语法,支持字符串类型的时间转换。
  • 2.rdb维表与DB建立连接时,周期进行连接,防止连接断开。rdbsink写入时,对连接进行检查。
  • 3.异步维表支持非等值连接,比如:<>,<,>。
  • 4.增加kafka数组解析
  • 5.增加kafka1.0以上版本的支持
  • 6.增加postgresql、kudu、clickhouse维表、结果表的支持
  • 7.支持插件的依赖方式,参考pluginLoadMode参数
  • 8.支持cep处理
  • 9.支持udaf
  • 10.支持谓词下移

BUG修复:

  • 1.修复不能解析sql中orderby,union语法。
  • 2.修复yarnPer模式提交失败的异常。
  • 3.一些bug的修复

已支持

  • 源表:kafka 0.9、0.10、0.11、1.x版本
  • 维表:mysql, SQlServer,oracle, hbase, mongo, redis, cassandra, serversocket, kudu, postgresql, clickhouse
  • 结果表:mysql, SQlServer, oracle, hbase, elasticsearch5.x, mongo, redis, cassandra, console, kudu, postgresql, clickhouse

后续开发计划

  • 维表快照
  • kafka avro格式
  • topN

1 快速起步

1.1 运行模式

  • 单机模式:对应Flink集群的单机模式
  • standalone模式:对应Flink集群的分布式模式
  • yarn模式:对应Flink集群的yarn模式

1.2 执行环境

  • Java: JDK8及以上
  • Flink集群: 1.4,1.5,1.8(单机模式不需要安装Flink集群)
  • 操作系统:理论上不限

1.3 打包

进入项目根目录,使用maven打包:

mvn clean package -Dmaven.test.skip

打包结束后,项目根目录下会产生plugins目录,plugins目录下存放编译好的数据同步插件包,在lib目下存放job提交的包

1.4 启动

1.4.1 启动命令

sh submit.sh -sql D:\sideSql.txt  -name xctest -remoteSqlPluginPath /opt/dtstack/150_flinkplugin/sqlplugin   -localSqlPluginPath D:\gitspace\flinkStreamSQL\plugins   -addjar \["udf.jar\"\] -mode yarn -flinkconf D:\flink_home\kudu150etc  -yarnconf D:\hadoop\etc\hadoopkudu -confProp \{\"time.characteristic\":\"EventTime\",\"sql.checkpoint.interval\":10000\} -yarnSessionConf \{\"yid\":\"application_1564971615273_38182\"}

1.4.2 命令行参数选项

  • mode

    • 描述:执行模式,也就是flink集群的工作模式
      • local: 本地模式
      • standalone: 提交到独立部署模式的flink集群
      • yarn: 提交到yarn模式的flink集群(即提交到已有flink集群)
      • yarnPer: yarn per_job模式提交(即创建新flink application)
    • 必选:否
    • 默认值:local
  • name

    • 描述:flink 任务对应名称。
    • 必选:是
    • 默认值:无
  • sql

    • 描述:执行flink sql 的主体语句。
    • 必选:是
    • 默认值:无
  • localSqlPluginPath

    • 描述:本地插件根目录地址,也就是打包后产生的plugins目录。
    • 必选:是
    • 默认值:无
  • remoteSqlPluginPath

    • 描述:flink执行集群上的插件根目录地址(将打包好的插件存放到各个flink节点上,如果是yarn集群需要存放到所有的nodemanager上)。
    • 必选:否
    • 默认值:无
  • addjar

    • 描述:扩展jar路径,当前主要是UDF定义的jar;
    • 格式:json
    • 必选:否
    • 默认值:无
  • confProp

    • 描述:一些参数设置
    • 格式: json
    • 必选:是 (如无参数填写空json即可)
    • 默认值:无
    • 可选参数:
      • sql.env.parallelism: 默认并行度设置
      • sql.max.env.parallelism: 最大并行度设置
      • time.characteristic: 可选值[ProcessingTime|IngestionTime|EventTime]
      • sql.checkpoint.interval: 设置了该参数表明开启checkpoint(ms)
      • sql.checkpoint.mode: 可选值[EXACTLY_ONCE|AT_LEAST_ONCE]
      • sql.checkpoint.timeout: 生成checkpoint的超时时间(ms)
      • sql.max.concurrent.checkpoints: 最大并发生成checkpoint数
      • sql.checkpoint.cleanup.mode: 默认是不会将checkpoint存储到外部存储,[true(任务cancel之后会删除外部存储)|false(外部存储需要手动删除)]
      • flinkCheckpointDataURI: 设置checkpoint的外部存储路径,根据实际的需求设定文件路径,hdfs://, file://
      • jobmanager.memory.mb: per_job模式下指定jobmanager的内存大小(单位MB, 默认值:768)
      • taskmanager.memory.mb: per_job模式下指定taskmanager的内存大小(单位MB, 默认值:768)
      • taskmanager.num: per_job模式下指定taskmanager的实例数(默认1)
      • taskmanager.slots:per_job模式下指定每个taskmanager对应的slot数量(默认1)
      • prometheus 相关参数 per_job可指定metric写入到外部监控组件,以prometheus pushgateway举例
  • flinkconf

    • 描述:flink配置文件所在的目录(单机模式下不需要),如/hadoop/flink-1.4.0/conf
    • 必选:否
    • 默认值:无
  • yarnconf

    • 描述:Hadoop配置文件(包括hdfs和yarn)所在的目录(单机模式下不需要),如/hadoop/etc/hadoop
    • 必选:否
    • 默认值:无
  • savePointPath

    • 描述:任务恢复点的路径
    • 必选:否
    • 默认值:无
  • allowNonRestoredState

    • 描述:指示保存点是否允许非还原状态的标志
    • 必选:否
    • 默认值:false
  • flinkJarPath

    • 描述:per_job 模式提交需要指定本地的flink jar存放路径
    • 必选:否
    • 默认值:false
  • queue

    • 描述:per_job 模式下指定的yarn queue
    • 必选:否
    • 默认值:false
  • pluginLoadMode

    • 描述:per_job 模式下的插件包加载方式。classpath:从每台机器加载插件包,shipfile:将需要插件从提交的节点上传到hdfs,不需要每台安装插件
    • 必选:否
    • 默认值:classpath
  • yarnSessionConf

    • 描述:yarn session 模式下指定的运行的一些参数,可参考,目前只支持指定yid
    • 必选:否
    • 默认值:false

2 结构

2.1 源表插件

2.2 结果表插件

2.3 维表插件

3 性能指标(新增)

kafka插件

  • 业务延迟: flink_taskmanager_job_task_operator_dtEventDelay(单位s)
    数据本身的时间和进入flink的当前时间的差值.

  • 各个输入源的脏数据:flink_taskmanager_job_task_operator_dtDirtyData
    从kafka获取的数据解析失败的视为脏数据

  • 各Source的数据输入TPS: flink_taskmanager_job_task_operator_dtNumRecordsInRate
    kafka接受的记录数(未解析前)/s

  • 各Source的数据输入RPS: flink_taskmanager_job_task_operator_dtNumRecordsInResolveRate
    kafka接受的记录数(解析后)/s

  • 各Source的数据输入BPS: flink_taskmanager_job_task_operator_dtNumBytesInRate
    kafka接受的字节数/s

  • Kafka作为输入源的各个分区的延迟数: flink_taskmanager_job_task_operator_topic_partition_dtTopicPartitionLag
    当前kafka10,kafka11有采集该指标

  • 各个输出源RPS: flink_taskmanager_job_task_operator_dtNumRecordsOutRate
    写入的外部记录数/s

4 样例


CREATE (scala|table|aggregate) FUNCTION CHARACTER_LENGTH WITH com.dtstack.Kun;


CREATE TABLE MyTable(
    name varchar,
    channel varchar,
    pv int,
    xctime bigint,
    CHARACTER_LENGTH(channel) AS timeLeng //自定义的函数
 )WITH(
    type ='kafka09',
    bootstrapServers ='172.16.8.198:9092',
    zookeeperQuorum ='172.16.8.198:2181/kafka',
    offsetReset ='latest',
    topic ='nbTest1',
    parallelism ='1'
 );

CREATE TABLE MyResult(
    channel varchar,
    pv varchar
 )WITH(
    type ='mysql',
    url ='jdbc:mysql://172.16.8.104:3306/test?charset=utf8',
    userName ='dtstack',
    password ='abc123',
    tableName ='pv2',
    parallelism ='1'
 );

CREATE TABLE workerinfo(
    cast(logtime as TIMESTAMP) AS rtime,
    cast(logtime) AS rtime
 )WITH(
    type ='hbase',
    zookeeperQuorum ='rdos1:2181',
    tableName ='workerinfo',
    rowKey ='ce,de',
    parallelism ='1',
    zookeeperParent ='/hbase'
 );

CREATE TABLE sideTable(
    cf:name varchar as name,
    cf:info varchar as info,
    PRIMARY KEY(name),
    PERIOD FOR SYSTEM_TIME //维表标识
 )WITH(
    type ='hbase',
    zookeeperQuorum ='rdos1:2181',
    zookeeperParent ='/hbase',
    tableName ='workerinfo',
    cache ='LRU',
    cacheSize ='10000',
    cacheTTLMs ='60000',
    parallelism ='1'
 );

insert
into
    MyResult
    select
        d.channel,
        d.info
    from
        (      select
            a.*,b.info
        from
            MyTable a
        join
            sideTable b
                on a.channel=b.name
        where
            a.channel = 'xc2'
            and a.pv=10      ) as d

招聘

1.大数据平台开发工程师,想了解岗位详细信息可以添加本人微信号ysqwhiletrue,注明招聘,如有意者发送简历至sishu@dtstack.com

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