Spark学习笔记——读写MySQL

1.使用Spark读取MySQL中某个表中的信息

build.sbt文件

name := "spark-hbase"version := "1.0"scalaVersion := "2.11.8"libraryDependencies ++= Seq(
  "org.apache.spark" %% "spark-core" % "2.1.0",
  "mysql" % "mysql-connector-java" % "5.1.31",
  "org.apache.spark" %% "spark-sql" % "2.1.0"
)

Mysql.scala文件

import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.sql.{SQLContext, SaveMode}
import java.util.Properties/**
  * Created by mi on 17-4-11.
  */case class resultset(name: String,
                     info: String,
                     summary: String)object MysqlOpt {  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setAppName("WordCount").setMaster("local")
    val sc = new SparkContext(conf)
    val sqlContext = new SQLContext(sc)
    import sqlContext.implicits._    //定义数据库和表信息
    val url = "jdbc:mysql://localhost:3306/baidubaike?useUnicode=true&characterEncoding=UTF-8"
    val table = "baike_pages"    //读MySQL的方法1
    val reader = sqlContext.read.format("jdbc")
    reader.option("url", url)
    reader.option("dbtable", table)
    reader.option("driver", "com.mysql.jdbc.Driver")
    reader.option("user", "root")
    reader.option("password", "XXX")
    val df = reader.load()
    df.show()    //读MySQL的方法2
    //    val jdbcDF = sqlContext.read.format("jdbc").options(
    //      Map("url"->"jdbc:mysql://localhost:3306/baidubaike?useUnicode=true&characterEncoding=UTF-8",
    //        "dbtable"->"(select name,info,summary from baike_pages) as some_alias",
    //        "driver"->"com.mysql.jdbc.Driver",
    //        "user"-> "root",
    //        //"partitionColumn"->"day_id",
    //        "lowerBound"->"0",
    //        "upperBound"-> "1000",
    //        //"numPartitions"->"2",
    //        "fetchSize"->"100",
    //        "password"->"XXX")).load()
    //    jdbcDF.show()  }
}

输出

2.使用Spark写MySQL中某个表中的信息

import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.sql.{SQLContext, SaveMode}
import java.util.Properties/**
  * Created by mi on 17-4-11.
  */case class resultset(name: String,
                     info: String,
                     summary: String)object MysqlOpt {  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setAppName("WordCount").setMaster("local")
    val sc = new SparkContext(conf)
    val sqlContext = new SQLContext(sc)
    import sqlContext.implicits._    //定义数据库和表信息
    val url = "jdbc:mysql://localhost:3306/baidubaike?useUnicode=true&characterEncoding=UTF-8"
    val table = "baike_pages"    //写MySQL的方法1
    val list = List(
      resultset("名字1", "标题1", "简介1"),
      resultset("名字2", "标题2", "简介2"),
      resultset("名字3", "标题3", "简介3"),
      resultset("名字4", "标题4", "简介4")
    )
    val jdbcDF = sqlContext.createDataFrame(list)
    jdbcDF.collect().take(20).foreach(println)
    //    jdbcDF.rdd.saveAsTextFile("/home/mi/coding/coding/Scala/spark-hbase/output")
    val prop = new Properties()
    prop.setProperty("user", "root")
    prop.setProperty("password", "123456")
    //jdbcDF.write.mode(SaveMode.Overwrite).jdbc(url,"baike_pages",prop)
    jdbcDF.write.mode(SaveMode.Append).jdbc(url, "baike_pages", prop)  }
}