FlinkSQL MySQL维表关联

迈不过友情╰ 2021-09-24 21:06 743阅读 0赞

> 需求：消费Kafka数据，进行数据清洗及维表关联补齐字段，结果数据写入Kafka。

import java.time.Duration
    
    import com.sm.function.udf._
    import com.sm.common.conf.PropManager
    import com.sm.constants.Constants
    import com.sm.utils.FlinkUtils
    import org.apache.flink.api.common.restartstrategy.RestartStrategies
    import org.apache.flink.api.common.time.Time
    import org.apache.flink.streaming.api.environment.{CheckpointConfig, ExecutionCheckpointingOptions}
    import org.apache.flink.streaming.api.scala._
    import org.apache.flink.streaming.api.{CheckpointingMode, TimeCharacteristic}
    import org.apache.flink.table.api.bridge.scala.StreamTableEnvironment
    import org.apache.log4j.Level
    import org.slf4j.LoggerFactory
    
    /**
      * flink sql 维表关联
      * 消费kafka, MySQL维表关联, 结果写入kafka
      *
      * create by LiuJinHe 2020/10/22
      */
    object LoginEtlKafka2Kafka {
      private var logger: org.slf4j.Logger = _
    
      def main(args: Array[String]): Unit = {
        logger = LoggerFactory.getLogger(this.getClass.getSimpleName)
        org.apache.log4j.Logger.getLogger("org.apache.hadoop").setLevel(Level.WARN)
        org.apache.log4j.Logger.getLogger("org.apache").setLevel(Level.INFO)
    
        // 初始化 stream 环境
        // 本地测试，需要 flink-runtime-web 依赖
        //   val env = StreamExecutionEnvironment.createLocalEnvironmentWithWebUI()
        val env = StreamExecutionEnvironment.getExecutionEnvironment
        // 本地测试线程 1
        //    env.setParallelism(1)
    
        //    val params = ParameterTool.fromArgs(args)
        //    env.getConfig.setGlobalJobParameters(params)
    
        // 失败重启,固定间隔,每隔3秒重启1次,总尝试重启10次
        env.setRestartStrategy(RestartStrategies.fixedDelayRestart(10, 3))
    
        // 事件处理的时间，由系统时间决定
        env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime)
    
        // 创建 streamTable 环境
        val tableEnv: StreamTableEnvironment = StreamTableEnvironment.create(env, FlinkUtils.getSettings)
        //    tableConfig.setIdleStateRetentionTime(Time.hours(12), Time.hours(24))
    
        // checkpoint 设置
        val tableConfig = tableEnv.getConfig.getConfiguration
        tableConfig.set(ExecutionCheckpointingOptions.CHECKPOINTING_MODE, CheckpointingMode.EXACTLY_ONCE)
        // checkpoint的超时时间周期，1 分钟做一次checkpoint, 每次checkpoint 完成后 sink 才会执行
        tableConfig.set(ExecutionCheckpointingOptions.CHECKPOINTING_INTERVAL, Duration.ofSeconds(60))
        // checkpoint的超时时间, 检查点一分钟内没有完成将被丢弃
        tableConfig.set(ExecutionCheckpointingOptions.CHECKPOINTING_TIMEOUT, Duration.ofSeconds(60))
        // checkpoint 最小间隔，两个检查点之间至少间隔 30 秒
        tableConfig.set(ExecutionCheckpointingOptions.MIN_PAUSE_BETWEEN_CHECKPOINTS, Duration.ofSeconds(30))
        // 同一时间只允许进行一个检查点
        tableConfig.set(ExecutionCheckpointingOptions.MAX_CONCURRENT_CHECKPOINTS, Integer.valueOf(1))
        // 手动cancel时是否保留checkpoint
        tableConfig.set(ExecutionCheckpointingOptions.EXTERNALIZED_CHECKPOINT,
          CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION)
    
        // 设置状态的最小空闲时间和最大的空闲时间
        tableEnv.getConfig.setIdleStateRetentionTime(Time.hours(12), Time.hours(24))
    
        tableConfig.setString("table.exec.mini-batch.enabled", "true")
        tableConfig.setString("table.exec.mini-batch.allow-latency", "2s")
        tableConfig.setString("table.exec.mini-batch.size", "5000")
        tableConfig.setString("table.optimizer.distinct-agg.split.enabled", "true")
    
        // 测试
        //    val odsLoginTopic = "ods_login"
        //    val bootstrapServers = "192.168.100.39:9092"
        //    val groupId = "flink-test-group"
        //    val startMode = "group-offsets"
        //    val dwdSdkUserLogin = "dwd_sdk_user_login"
    
        /**
          * 加载配置
          */
        val odsUserLoginTopic = PropManager.getProp(Constants.ODS_USER_LOGIN_TOPIC)
        val dwdUserLoginTopic = PropManager.getProp(Constants.DWD_USER_LOGIN_TOPIC)
        val bootstrapServers = PropManager.getProp(Constants.BOOTSTRAP_SERVERS)
        val ConsumerGroupId = PropManager.getProp(Constants.CONSUMER_GROUP_ID)
        val ProducerGroupId = PropManager.getProp(Constants.PRODUCER_GROUP_ID)
        val startMode = PropManager.getProp(Constants.STARTUP_MODE)
    
    
        /**
          * kafka source table
          */
        tableEnv.executeSql("drop table if exists login_kafka_Source")
    
        val kafkaSourceDDL =
          s"""
             |create table $odsUserLoginTopic (
             | _game_id int,
             | _login_name string,
             | _time bigint,
             | _time_server bigint,
             | _device_key string,
             | _os string,
             | _imei string,
             | ts as to_timestamp(from_unixtime(_time / 1000, 'yyyy-MM-dd HH:mm:ss')),
             | proc_time as proctime()
             |) with (
             | 'connector' = 'kafka',
             | 'topic' = '$odsUserLoginTopic',
             | 'properties.bootstrap.servers' = '$bootstrapServers',
             | 'properties.group.id' = '$ConsumerGroupId',
             | 'scan.startup.mode' = '$startMode',
             | 'format' = 'json',
             | 'json.fail-on-missing-field' = 'false',
             | 'json.ignore-parse-errors' = 'true'
             |)
          """.stripMargin
        tableEnv.executeSql(kafkaSourceDDL)
    
        /**
          * dwd
          */
        tableEnv.executeSql(s"drop table if exists $dwdUserLoginTopic")
    
        val kafkaSinkDDL =
          s"""
             |create table $dwdUserLoginTopic (
             |  cp_game_id int,
             |  game_id int,
             |  login_account string,
             |  `time` string,
             |  time_server string,
             |  device_key string,
             |  os string,
             |  primary key (`time`, package_id, core_account) not enforced
             |) with (
             | 'connector' = 'kafka',
             | 'topic' = '$dwdUserLoginTopic',
             | 'properties.bootstrap.servers' = '$bootstrapServers',
             | 'properties.group.id' = '$ProducerGroupId',
             | 'sink.partitioner' = 'round-robin',
             | 'format' = 'json',
             | 'json.fail-on-missing-field' = 'false',
             | 'json.ignore-parse-errors' = 'true'
             |)
        """.stripMargin
        tableEnv.executeSql(kafkaSinkDDL)
    
        /**
          * DIM
          */
        val dimSourceDDL =
          """
            |create table dim_mysql_games (
            |  ID bigint,
            |  CP_GAME_ID int
            |) with (
            | 'connector' = 'jdbc',
            | 'url' = 'jdbc:mysql://cdh-slave04:3306/game_platform?useSSL=false&useUnicode=true&characterEncoding=UTF-8&characterSetResults=UTF-8&zeroDateTimeBehavior=CONVERT_TO_NULL&serverTimezone=UTC',
            | 'username' = 'root',
            | 'password' = '123456',
            | 'table-name' = 'games',
            | 'driver' = 'com.mysql.cj.jdbc.Driver',
            | 'scan.fetch-size' = '200',
            | 'lookup.cache.max-rows' = '2000',
            | 'lookup.cache.ttl' = '300s'
            |)
          """.stripMargin
        tableEnv.executeSql(dimSourceDDL)
    
        /**
          * 注册自定义函数
          */
        tableEnv.createTemporarySystemFunction("ParseDeviceCode", classOf[ParseDeviceCode])
        tableEnv.createTemporarySystemFunction("ParseDeviceKey", classOf[ParseDeviceKey])
        tableEnv.createTemporarySystemFunction("ParseOsVersion", classOf[ParseOsVersion])
        tableEnv.createTemporarySystemFunction("ParseDeviceId", classOf[ParseDeviceId])
        tableEnv.createTemporarySystemFunction("ParseMd5DeviceId", classOf[ParseMd5DeviceId])
    
        /**
          * temporal join
          */
        val queryDDL =
          s"""
             |insert into $dwdUserLoginTopic
             |select
             | dim.CP_GAME_ID as cp_game_id,
             | _game_id as game_id,
             | coalesce(_login_name, '') as login_account,
             | from_unixtime(_time / 1000, 'yyyy-MM-dd HH:mm:ss') as `time`,
             | from_unixtime(_time_server / 1000, 'yyyy-MM-dd HH:mm:ss') as time_server,
             | ParseDeviceKey(_device_key, _os, _imei) as device_key,
             | _os as os
             |from $odsUserLoginTopic as login
             | left join dim_mysql_games for system_time as of login.proc_time as dim
             | on dim.ID = login._game_id
          """.stripMargin
        tableEnv.executeSql(queryDDL)
      }
    }

配置加载

默认加载resources下 application.properties

import com.typesafe.config.{Config, ConfigFactory}
    
    /**
      * create by LiuJinHe 2020/3/11
      */
    object PropManager {
      final val config: Config = ConfigFactory.load
      def getProp(key: String): String = config.getString(key).trim
    }

自定义udf

import com.mysql.cj.util.StringUtils
    import com.sm.common.utils.MD5Utils
    import org.apache.flink.table.functions.ScalarFunction
    
    /**
      * 自定义UDF, 解析 Device key
      *
      * create by LiuJinHe 2020/9/22
      */
    class ParseDeviceKey extends ScalarFunction {
      def eval(deviceKey: String, os: String, imei: String): String = {
        if (!StringUtils.isNullOrEmpty(deviceKey)) {
          deviceKey.toLowerCase
        } else if (os == "1") {
          ""
        } else {
          MD5Utils.MD5Encode(imei).toLowerCase
        }
      }
    }

pom

<properties>
            <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
            <maven.compiler.source>1.8</maven.compiler.source>
            <maven.compiler.target>1.8</maven.compiler.target>
            <scala.version>2.11.12</scala.version>
            <scala.binary.version>2.11</scala.binary.version>
            <flink.version>1.11.2</flink.version>
            <hive.version>2.1.1-cdh6.2.0</hive.version>
            <hadoop.version>3.0.0-cdh6.2.0</hadoop.version>
        </properties>
    
        <repositories>
            <repository>
                <id>cloudera</id>
                <url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>
                <releases>
                    <enabled>true</enabled>
                </releases>
                <snapshots>
                    <enabled>false</enabled>
                </snapshots>
            </repository>
        </repositories>
    
        <dependencies>
            <dependency>
                <groupId>com.sm.common</groupId>
                <artifactId>common</artifactId>
                <version>1.0-SNAPSHOT</version>
            </dependency>
            <dependency>
                <groupId>org.scala-lang</groupId>
                <artifactId>scala-library</artifactId>
                <version>${scala.version}</version>
                
            </dependency>
    
            
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-runtime-web_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-core</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
    
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-scala_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-table-common</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-table-api-scala-bridge_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-table-planner-blink_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-clients_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-json</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-connector-kafka_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>org.apache.flink</groupId>
                <artifactId>flink-connector-jdbc_${scala.binary.version}</artifactId>
                <version>${flink.version}</version>
                
            </dependency>
            <dependency>
                <groupId>com.alibaba.ververica</groupId>
                <artifactId>flink-sql-connector-mysql-cdc</artifactId>
                <version>1.1.0</version>
                <scope>provided</scope>
            </dependency>
    
            
            <dependency>
                <groupId>mysql</groupId>
                <artifactId>mysql-connector-java</artifactId>
                <version>8.0.16</version>
                
            </dependency>
        </dependencies>
    
        <build>
            <plugins>
                
                <plugin>
                    <groupId>net.alchim31.maven</groupId>
                    <artifactId>scala-maven-plugin</artifactId>
                    <version>4.2.0</version>
                    <executions>
                        <execution>
                            <goals>
                                
                                <goal>compile</goal>
                            </goals>
                        </execution>
                    </executions>
                </plugin>
                <plugin>
                    <groupId>org.apache.maven.plugins</groupId>
                    <artifactId>maven-assembly-plugin</artifactId>
                    <version>3.0.0</version>
                    <configuration>
                        <descriptorRefs>
                            <descriptorRef>jar-with-dependencies</descriptorRef>
                        </descriptorRefs>
                    </configuration>
                    <executions>
                        <execution>
                            <id>make-assembly</id>
                            <phase>package</phase>
                            <goals>
                                <goal>single</goal>
                            </goals>
                        </execution>
                    </executions>
                </plugin>
            </plugins>
        </build>

提交到集群，$FLINK\_HOME/lib 下放入以下jar，重启集群，打包时全部 <scope>provided</scope>

flink-connector-jdbc_2.11-1.11.2.jar
    flink-sql-connector-kafka_2.11-1.11.2.jar
    flink-sql-connector-mysql-cdc-1.1.0.jar    # mysql cdc,包含mysql-connector-java