spark的hive操作和常见的bug

package hive

import org.apache.spark.SparkConf
import org.apache.spark.sql.SparkSession

object HiveDome {
  def fun1(): Unit = {
    val conf = new SparkConf().setAppName("hive")
    val spark = SparkSession.builder().appName("hive").config(conf).enableHiveSupport().getOrCreate()

    import spark.sql
    //创建件hive表
    sql("create table if not exists user(id int,value String) row format delimited fields terminated by ‘,‘")
    sql("load data local inpath ‘/user.log‘ into table user")　　//这里不能写成user.txt文件,会出现乱码

//    sql("select * from user").show()
//    sql("select count(*) from user").show()
//
//    val sqlDF = sql("select key,value from user where key<10 order BY key")
//    import spark.implicits._    //隐式转化
//    val stringDS = sqlDF.map { case org.apache.spark.sql.Row(id: Int, value: String) => s"key:$id,value:$value" }
//    stringDS.show()

    sql("select value,id from user").write.mode("overwrite")
     .saveAsTable("spark_hive_test1")

    spark.stop()
  }

  def main(args: Array[String]): Unit = {
    fun1()
  }
}

写完之后在idea 打成jar包,将jar包写到liunx下的根目录下

然后配置环境

1.把hive的配置 hive-site.xml 复制到 spark/conf
    cp /usr/hive/apache-hive-2.3.3-bin/conf/hive-site.xml   /usr/spark/spark-

2.1.1-bin-hadoop2.7/conf/

2.把mysql的驱动jar放入到 spark/spark-2.1.1-bin-hadoop2.7/jars/
    mysql-connector-java-5.1.38.jar

3.修改spark-env.sh文件
    export SPARK_CLASSPATH=$SPARK_CLASS:$SPARK_HOME/jars/mysql-connector-java-5.1.38.jar

4.在集群上执行
    spark-submit --master spark://zhiyou01:7077 --class 类名的全称    --total-executor-cores 2 --executor-memory 512m /jar包路径

如果不配置环境会出现以下错误

Exception in thread "main" java.lang.UnsupportedOperationException: loadTable is not implemented

常见bug:

1>[code=java]org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.ipc.StandbyException): Operation category READ is not supported in state standby

原因:

2>io错误,说是hdfs下的user.log不存在

原因:我在创建

原文地址：https://www.cnblogs.com/han-guang-xue/p/10041150.html