[大数据]spark structured打通kafka与tablestore 的连接

spark 连接kafka数据sink到tablestore中

直接上代码, 有不明白的可以留言
pom

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>com.aliyun.tablestore</groupId>
    <artifactId>tablestore-spark</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <spark.version>2.4.5</spark.version>
        <scala.version>2.11.7</scala.version>
        <scala.version.sp>2.11</scala.version.sp>
        <emr.version>2.2.0</emr.version>
        <kafka.version>2.3.0</kafka.version>
        <tablestore.sdk.version>5.10.3</tablestore.sdk.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_${scala.version.sp}</artifactId>
            <version>${spark.version}</version>
            <!--<scope>provided</scope>-->
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_${scala.version.sp}</artifactId>
            <version>${spark.version}</version>
            <!--<scope>provided</scope>-->
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-clients -->
        <!--<dependency>-->
            <!--<groupId>org.apache.kafka</groupId>-->
            <!--<artifactId>kafka-clients</artifactId>-->
            <!--<version>${kafka.version}</version>-->
        <!--</dependency>-->
        <!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka -->
        <!--<dependency>-->
            <!--<groupId>org.apache.kafka</groupId>-->
            <!--<artifactId>kafka_${scala.version.sp}</artifactId>-->
            <!--<version>${kafka.version}</version>-->
            <!--<exclusions>-->
                <!--<exclusion>-->
                    <!--<groupId>org.slf4j</groupId>-->
                    <!--<artifactId>slf4j-log4j12</artifactId>-->
                <!--</exclusion>-->
            <!--</exclusions>-->
        <!--</dependency>-->

        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql-kafka-0-10 -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql-kafka-0-10_2.11</artifactId>
            <version>${spark.version}</version>
            <!--<scope>test</scope>-->
        </dependency>

        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_${scala.version.sp}</artifactId>
            <version>${spark.version}</version>
            <!--<scope>provided</scope>-->
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming-kafka-0-10 -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka-0-10_${scala.version.sp}</artifactId>
            <version>${kafka.version}</version>
            <exclusions>
                <exclusion>
                    <groupId>org.slf4j</groupId>
                    <artifactId>slf4j-log4j12</artifactId>
                </exclusion>
            </exclusions>
        </dependency>

        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka_2.11</artifactId>
            <version>1.5.2</version>
        </dependency>

        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.19</version>
        </dependency>

        <dependency>
            <groupId>com.aliyun.emr</groupId>
            <artifactId>emr-tablestore</artifactId>
            <version>${emr.version}</version>

            <exclusions>
                <exclusion>
                    <groupId>com.fasterxml.jackson.core</groupId>
                    <artifactId>*</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <!-- tablestore -->
        <dependency>
            <groupId>com.aliyun.openservices</groupId>
            <artifactId>tablestore</artifactId>
            <version>${tablestore.sdk.version}</version>
            <classifier>jar-with-dependencies</classifier>
            <exclusions>
                <exclusion>
                    <groupId>com.google.protobuf</groupId>
                    <artifactId>protobuf-java</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>com.google.code.gson</groupId>
                    <artifactId>gson</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>com.fasterxml.jackson.core</groupId>
                    <artifactId>*</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
        </dependency>
        <!-- Scala Library, provided by Flink as well. -->
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>com.aliyun.emr</groupId>
            <artifactId>emr-tablestore</artifactId>
            <version>${emr.version}</version>
        </dependency>

        <dependency>
            <groupId>com.fasterxml.jackson.module</groupId>
            <artifactId>jackson-module-scala_${scala.version.sp}</artifactId>
            <version>2.10.1</version>
        </dependency>
    </dependencies>

</project>

执行代码:

package com.spark
import com.alibaba.fastjson.JSON
import org.apache.spark.sql._
//import org.apache.spark.streaming.kafka010.KafkaUtils
//import org.apache.spark.sql.streaming.Trigger


case class User(id_md5:String, id:String)


object StructuredKafkaToOTS {
  def main(args: Array[String]): Unit = {
    val brokers="localhost:9092"
    val topics="test"
    val groupId ="test"

    val spark = SparkSession.builder.appName("123")
      .master("local[*]")
      .getOrCreate()

    // Create DataSet representing the stream of input lines from kafka
    val dataCatalog: String =
    s"""
       |{"columns": {
       |    "id_md5": {"type":"string"},
       |    "id": {"type":"string"}
       | }
       |}""".stripMargin
    val df = spark
      .readStream
      .format("kafka")

      .option("kafka.bootstrap.servers", "localhost:9092")
      .option("subscribe", "test12")
      .option("group.id", "test11")
//      .option("failOnDataLoss", "false") // 报错数据丢失
      .option("startingOffsets","earliest")
//      .option("spark.sql.parquet.binaryAsString","true")

      .load()

    import spark.implicits._

    val tt = df.selectExpr("CAST(key AS STRING)","CAST(value AS STRING)")
      .as[(String,String)]


    val yy = tt.map(data =>{
      val value = data._2
      println("sec: " + value)

      val user = JSON.parseObject(value,classOf[User])
      user
    })

    /**
      * write ots
      *
      * */
    val ttt = yy
//      .selectExpr("CAST(key AS STRING)", "CAST(value AS STRING)")
      .writeStream
//      .outputMode("complete")
      .format("tablestore")
      .option("endpoint", "https://xxx.aliyuncs.com")
      .option("instance.name", "test-xxx")
      .option("access.key.id", "xxx")
      .option("access.key.secret", "xxx")
      .option("table.name", "xxx")
      .option("catalog", dataCatalog)
      .option("checkpointLocation", "D:\\spark_data\\spark_scala\\logs")
      .option("triggerInterval", 20) // custom
      .start()
      ttt.awaitTermination()


    /**
      * write kafka
      * */
    tt
      .writeStream
      .format("kafka")
      .option("checkpointLocation", "D:\\spark_data\\spark_scala\\logs")
      .option("kafka.bootstrap.servers", "localhost:9092")
      .option("topic", "test0")
      .start().awaitTermination()

    yy.show(false)
  println("kkkkkkkkkkkkkkkkkkkkkkk")



    /**
      * write 控制台
      * */
//    tt.write
//      .format("console")
      .outputMode("complete")
//      .trigger(Trigger.ProcessingTime(0))
//      .start()
//      .awaitTermination()


  }
}