Flink 消费 Kafka 数据批量写入 MySQL 多个表

业务场景：
sdk 数据统一入Kafka 的一个 topic（topic_sdk_log），其中包含多种事件类型数据，如：登录，注册，激活等，需要将 Kafka 中数据根据事件类型分别写入 MySQL 多个表。这里使用 Flink 每5秒写入 MySQL 不同表。

数据示例： 

{"key":"login","data":{"_game_version":"","_package_id":"12280200","_core_account":"ysdk_oGFjT0XEjdefIOgd7uApwWUX2ccY","_time":"2020-03-23 15:35:11","_time_server":"2020-03-23 15:35:59","_idfa":"","_imei":"","_mac":null,"_imsi":null,"_device_code":"46e0fd235df0b7c167c0cbe82be02a3c"}}

{"key":"activate","data":{"_game_version":"","_package_id":850030,"_time":"2020-03-23 15:25:56","_time_server":"2020-03-23 15:27:42","_idfa":"","_imei":"866092032174377","_mac":"02:00:00:00:00:00","_imsi":"460001960611910","_device_code":"fc9b4de27db42c94433a02c59cd5e2ff"}}

KafkaToMySQL 主类

import com.alibaba.fastjson.JSON
import com.sm.conf.ConfigurationManager
import com.sm.constants.Constants
import com.sm.sink.MySQLSink
import com.sm.entry.SdkData
import com.sm.util.KafkaUtils
import com.sm.window.SdkWindow
import org.apache.flink.streaming.api.scala._
import org.apache.flink.streaming.api.windowing.time.Time
import org.apache.flink.streaming.api.TimeCharacteristic


/**
  * Flink 读取 Kafka，每分钟聚合一次数据，批量写入 MySQL
  *
  * create by LiuJinHe 2020/3/25
  */
object KafkaToMySQL {
  def main(args: Array[String]): Unit = {
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    // 失败重启
    env.setRestartStrategy(RestartStrategies.fixedDelayRestart(10, 3L))

    //    env.setParallelism(1)

    // checkpoint 周期
    env.enableCheckpointing(10000)
    val config = env.getCheckpointConfig

    // exactly_one 模式
    config.setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE)
    // checkpoint 之间最小间隔
    config.setMinPauseBetweenCheckpoints(1000)
    // checkpoint 超时时间,超时将被丢弃
    config.setCheckpointTimeout(10000)
    // 同一时间只允许进行一次 checkpoint
    config.setMaxConcurrentCheckpoints(1)

    val kafkaProp = ConfigurationManager.load(Constants.KAFKA_PROPERTIES)
    val kafkaConsumer = KafkaUtils.getConsumer(kafkaProp).setStartFromGroupOffsets()

    val dataStream = env.addSource(kafkaConsumer)

    dataStream.map(line => {
      val data = JSON.parseObject(line, classOf[SdkData])
      data
    })
      .filter(line =>
        line.key == "activate" || line.key == "register" || line.key == "start_app" || line.key == "login"
      )
      .keyBy(data => data.key)
      .timeWindowAll(Time.seconds(3))
      .apply(new SdkWindow)
      .addSink(new MySink)

    env.execute("stream job")
  }
}

ConfigurationManager 配置管理

import java.util.Properties

/**
  * 配置文件的管理器，用于加载主要的配置信息，获取对应的配置项
  *
  * create by LiuJinHe 2020/3/25
  */
object ConfigurationManager {
  private val properties = new Properties

  def load(name: String): Properties = {
    if (name != null && name.nonEmpty) {
      properties.load(ConfigurationManager.getClass.getClassLoader.getResourceAsStream(name))
    } 
    properties
  }
}

PropManager 配置加载

配置文件 application.properties 放在 resources 下

import com.typesafe.config.{Config, ConfigFactory}

/**
  * create by LiuJinHe 2020/3/25
  */
object PropManager {
  final val config: Config = ConfigFactory.load
  def getProp(key: String): String = config.getString(key).trim
}

如：

application.properties

driver = com.mysql.jdbc.Driver
url = jdbc:mysql://localhost:3306/test?useSSL=false
username = root
password = 863863

database = test
activate = tb_sdk_active_log
register = tb_sdk_user_reg
start_app = tb_sdk_start_log
login = tb_sdk_user_login

KafkaUtils 自定Source

import java.util.Properties

import org.apache.flink.api.common.serialization.SimpleStringSchema
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer

/**
  * 自定义Source, Kafka Consumer
  *
  * create by LiuJinHe 2020/1/6
  */
object KafkaUtils {
  def getConsumer(prop:Properties): FlinkKafkaConsumer[String] = {
    prop.setProperty("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer")
    prop.setProperty("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer")
    prop.setProperty("auto.offset.reset", "latest")

    val topic = prop.getProperty("regional.topic")
    new FlinkKafkaConsumer[String](topic, new SimpleStringSchema(), prop)
  }
}

 SdkData 输入类

/**
  * 输入类
  * @param key 事件类型
  * @param data 事件内容
  */
case class SdkData(key: String, data: String)

SdkData window function

import com.sm.entry.SdkData
import org.apache.flink.streaming.api.scala.function.AllWindowFunction
import org.apache.flink.streaming.api.windowing.windows.TimeWindow
import org.apache.flink.util.Collector

/**
  * 自定义 window function
  *
  * create by LiuJinHe 2020/3/25
  */
class SdkWindow extends AllWindowFunction[SdkData, Iterable[SdkData], TimeWindow] {
  override def apply(window: TimeWindow, input: Iterable[SdkData], out: Collector[Iterable[SdkData]]): Unit = {
    if (input.nonEmpty) {
      println("5 秒内数据条数：" + input.size)
      out.collect(input)
    }
  }
}

MySQLSink 自定义 Sink

import java.sql.{Connection, PreparedStatement}
import com.sm.entry.SdkData
import com.sm.parse.ParseUtils
import com.sm.util.DBUtils
import org.apache.commons.dbcp2.BasicDataSource
import org.apache.flink.configuration.Configuration
import org.apache.flink.streaming.api.functions.sink.{RichSinkFunction, SinkFunction}

/**
  * 自定义 MySQL Sink,批量写入数据到 MySQL
  *
  * create by LiuJinHe 2020/3/25
  */
class MySQLSink extends RichSinkFunction[Iterable[SdkData]] {
  var conn: Connection = _
  var ps: PreparedStatement = _
  var dataSource: BasicDataSource = _

  /**
    * 建立连接，每分钟调用一次
    */
  override def open(parameters: Configuration): Unit = {
    super.open(parameters)
    dataSource = new BasicDataSource
    conn = DBUtils.getConnection(dataSource)
    conn.setAutoCommit(false)

    println("open: 已连接mysql")
  }

  /**
    * 每次写入调用一次
    */
  override def invoke(value: Iterable[SdkData], context: SinkFunction.Context[_]): Unit = {
    val dataList = value.toList

    ps = conn.prepareStatement("")
    dataList.foreach(sdkData => {
      val category = sdkData.key
      val sql = ParseUtils.getSqlStr(category)

      sql.append(setPreparedStatement(sdkData.data, category))

      ps.addBatch(sql.toString)
    })

    val count = ps.executeBatch()
    conn.commit()

    println("成功写入数据条数: " + count.length)
  }

  /**
    * 关闭连接和释放资源
    */
  override def close(): Unit = {
    super.close()
    if (conn != null) {
      conn.close()
    }

    if (ps != null) {
      ps.close()
    }
  }

  /**
    * preparedStatement 赋值
    */
  def setPreparedStatement(data: String, category: String): StringBuffer = {
    val valueStr = new StringBuffer()
    val json = JSON.parseObject(data)

    val obj = ParseUtils.matchCategory(json: JSONObject, category: String)

    val fields: Array[Field] = obj.getClass.getDeclaredFields

    for (i <- fields.indices) {
      val field = fields(i)
      val colType = field.getType
      field.setAccessible(true)
      val data = field.get(obj)
      if(colType.getName.contains("String")){
        valueStr.append(s"'$data'").append(",")
      }else{
        valueStr.append(data).append(",")
      }
    }

    valueStr.replace(valueStr.length - 1, valueStr.length(), ");")
  }
}

DBUtils 数据库连接池

这里配置了两种（ Druid 和 dbcp2 ）

import java.sql.Connection

import com.alibaba.druid.pool.DruidDataSource
import com.sm.conf.PropManager
import org.apache.commons.dbcp2.BasicDataSource

/**
  *
  * 数据库连接池设置，获取线程
  *
  * create by LiuJinHe 2020/3/25
  */
object DBUtils {

  /**
    * Druid
    */
  def getConnection(dataSource: DruidDataSource): Connection = {
    dataSource.setDriverClassName(PropManager.getProp("driver"))
    dataSource.setUrl(PropManager.getProp("url"))
    dataSource.setUsername(PropManager.getProp("username"))
    dataSource.setPassword(PropManager.getProp("password"))
    //设置初始化连接数，最大连接数，最小闲置数
    dataSource.setInitialSize(10)
    dataSource.setMaxActive(50)
    dataSource.setMinIdle(5)
    //返回连接

    val conn = dataSource.getConnection
    println("创建 Druid 连接池：" + conn)
    conn
  }

  /**
    * dbcp2
    */
  def getConnection(dataSource: BasicDataSource): Connection ={
    dataSource.setDriverClassName(PropManager.getProp("driver"))
    dataSource.setUrl(PropManager.getProp("url"))
    dataSource.setUsername(PropManager.getProp("username"))
    dataSource.setPassword(PropManager.getProp("password"))

    dataSource.setInitialSize(10)
    dataSource.setMaxTotal(50)
    dataSource.setMaxIdle(5)

    val conn = dataSource.getConnection
    println("创建 dbcp2 连接池：" + conn)
    conn
  }
}

ParseUtils 解析事件

import com.alibaba.fastjson.JSONObject
import com.sm.conf.PropManager
import com.sm.entry._

/**
  * 解析事件
  * 
  * create by LiuJinHe 2020/3/30
  */
object ParseUtils {

  def getSqlStr(category: String): StringBuffer = {
    // 构建 insert into table(field1,field2) values(
    val sqlStr = new StringBuffer()
    val database = PropManager.getProp("database")
    val table = PropManager.getProp(category)

    sqlStr.append(s"insert ignore into $database.$table(")

    val sdk = category match {
      case "activate" => classOf[Active].getDeclaredFields // 设备激活
      case "register" => classOf[Reg].getDeclaredFields // 用户注册
      case "login" => classOf[UserLogin].getDeclaredFields // 用户登录
      case "start_app" => classOf[Start].getDeclaredFields // 设备启动
    }

    for (i <- 0 until sdk.length) {
      val field = sdk.toList(i).getName
      sqlStr.append(s"$field,")
    }

    sqlStr.replace(sqlStr.length - 1, sqlStr.length(), ") values(")
  }

  /**
    * 匹配事件
    */
  def matchCategory(json: JSONObject, category: String): AnyRef = category match {
    case "activate" => ParseCategory.activeParse(json, category)
    case "register" => ParseCategory.registerParse(json, category)
    case "login" => ParseCategory.loginParse(json, category)
    case "start_app" => ParseCategory.startParse(json, category)
  }
}

ParseCategory  事件解析类

import com.alibaba.fastjson.JSONObject
import com.mysql.jdbc.StringUtils
import com.sm.entry.{Active, Crash, Payment, Reg, RoleLogin, Start, UserLogin}
import com.sm.util.{DateUtils, MD5Utils}

/**
  * 解析事件,并进行清洗
  *
  * create by LiuJinHe 2020/3/30
  */
object ParseCategory {
  /**
    * 公告字段
    */
  private var package_id: String = _ // 游戏包id
  private var core_account: String = _ // 用户id(核心账号)
  private var time: String = _ // 行为发生时间
  private var time_server: String = _ // 上报到服务器时间
  private var device_code: String = _ // 设备码


 /**
    * 登录事件
    */
  def loginParse(json: JSONObject, category: String): AnyRef = {
    package_id = json.getString("_package_id").trim
    core_account = if(json.containsKey("_core_account")) json.getString("_core_account").trim else ""
    time = json.getString("_time").trim
    time_server = json.getString("_time_server").trim
    device_code = if(json.containsKey("_device_code")) json.getString("_device_code").trim else ""

    UserLogin(
      if (!StringUtils.isNullOrEmpty(package_id) && StringUtils.isStrictlyNumeric(package_id)) package_id.toInt else 0,
      if (!StringUtils.isNullOrEmpty(core_account)) core_account else "",
      if (StringUtils.isStrictlyNumeric(time)) DateUtils.timestampToTime(time.toLong) else if (time != null) time else "",
      if (!StringUtils.isNullOrEmpty(device_code)) device_code.toLowerCase
       else MD5Utils.MD5Encode(json.getString("_mac") + json.getString("_imei") + json.getString("_imsi")).toLowerCase,
    )
  }
}

UserLogin 事件

/**
  * SDK 用户登录日志
  *
  * create by LiuJinHe 2020/3/25
  */
case class UserLogin(
                      package_id: Int, // 游戏包id
                      core_account: String, // 用户id(核心账号)
                      time: String, // 行为发生时间
                      time_server: String, // 上报到服务器时间
                      device_code: String, // 设备码
                    )

KafkaProducer 生产数据

import java.util.Properties

import org.apache.kafka.clients.producer._

/**
  * Kafka Producer 将本地数据发送到 Kafka
  *
  * create by LiuJinHe 2020/3/25
  */
object KafkaProducer {

  def main(args: Array[String]): Unit = {
    loadToKafka("topic_sdk_log")
  }

  def loadToKafka(topic: String): Unit = {
    val prop = new Properties()
    //    prop.put("bootstrap.servers", "cdh-master:9094,cdh-slave01:9094,cdh-slave02:9094")
    prop.put("bootstrap.servers", "hadoop-master:9092")
    prop.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer")
    prop.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer")
    val producer = new KafkaProducer[String, String](prop)

    val bufferSource = io.Source.fromFile("E:\\workspace\\real-time-kafka-to-mysql\\src\\main\\resources\\avtive.txt")
    for (line <- bufferSource.getLines) {
      val record = new ProducerRecord[String, String](topic, line)
//      Thread.sleep(1000)
      producer.send(record)
    }

    producer.close()
  }
}

结果：