1.將$HIVE_HOME/conf/hive-site.xml檔案複製一份到$SPARK_HOME/conf/hive-site.xml

cp $HIVE_HOME/conf/hive-site.xml $SPARK_HOME/conf

2.直接啟動spark-shell就能幫我們自動連線

./spark-shell --master local[2] --jars /usr/local/jar/mysql-connector-java-5.1.47.jar    # --jars:是指定jar包

3.直接啟動spark-shell就能幫我們自動連線

./spark-sql --master local[2] --jars /usr/local/jar/mysql-connector-java-5.1.47.jar --driver-class-path /usr/local/jar/mysql-connector-java-5.1.47.jar

4.我們可以啟動一個啟動thriftserver伺服器server,7*24一直running

cd $SPARK_HOME/sbin
./start-thriftserver.sh --master local --jars /usr/local/jar/mysql-connector-java-5.1.47.jar    # 啟動預設監聽埠10000

5.通過內建了一個客戶端工具連線

cd $SPARK_HOME/bin/beeline
./beeline -u jdbc:hive2://192.168.104.94:10000

6.也可以使用程式碼連線

package com.imooc.bigdata.chapter06

import java.sql.{Connection, DriverManager, PreparedStatement, ResultSet}

object JDBCClientApp {

  def main(args: Array[String]): Unit = {

    // 載入驅動
    Class.forName("org.apache.hive.jdbc.HiveDriver")

    val conn: Connection = DriverManager.getConnection("jdbc:hive2://192.168.104.94:10000")
    val pstmt: PreparedStatement = conn.prepareStatement("show tables")
    val rs: ResultSet = pstmt.executeQuery()

    while(rs.next()) {
      println(rs.getObject(1) + " : " + rs.getObject(2))
    }
  }
}