SparkSQL读取hive数据本地idea运行的方法详解

环境准备：

hadoop版本：2.6.5
spark版本：2.3.0
hive版本：1.2.2
master主机：192.168.100.201
slave1主机：192.168.100.201

pom.xml依赖如下：

 4.0.0
 
 com.spark
 spark_practice
 1.0-SNAPSHOT
 
 
  UTF-8
  1.8
  1.8
  2.3.0
 
 
 
  
   junit
   junit
   4.11
   test
  
  
   org.apache.spark
   spark-core_2.11
   ${spark.core.version}
  
 
  
   org.apache.spark
   spark-sql_2.11
   ${spark.core.version}
  
  
   mysql
   mysql-connector-java
   5.1.38
  
  
   org.apache.spark
   spark-hive_2.11
   2.3.0
  
 
 

注意：一定要将hive-site.xml配置文件放到工程resources目录下

hive-site.xml配置如下： 

 

 
 hive.metastore.uris
 thrift://192.168.100.201:9083
 
 
 hive.server2.thrift.port
 10000
  
   
  javax.jdo.option.ConnectionURL
  jdbc:mysql://node01:3306/hive?createDatabaseIfNotExist=true 
  
   
  javax.jdo.option.ConnectionDriverName
  com.mysql.jdbc.Driver 
  
   
  javax.jdo.option.ConnectionUserName
  root
 
 
  javax.jdo.option.ConnectionPassword
  123456
 
 
  hive.zookeeper.quorum
   node01,node02,node03
  
 
  
  hbase.zookeeper.quorum
   node01,node02,node03
  
  
 
 hive.metastore.warehouse.dir
 /user/hive/warehouse
 
 
 
 fs.defaultFS
 hdfs://192.168.100.201:9000
 
 
 hive.metastore.schema.verification
 false
 
 
 datanucleus.autoCreateSchema
 true
 
 
 datanucleus.autoStartMechanism
 checked
 
 

主类代码：

import org.apache.spark.sql.SparkSession
 
object SparksqlTest2 {
 def main(args: Array[String]): Unit = {
 
 val spark: SparkSession = SparkSession
  .builder
  .master("local[*]")
  .appName("Java Spark Hive Example")
  .enableHiveSupport
  .getOrCreate
 
 spark.sql("show databases").show()
 spark.sql("show tables").show()
 spark.sql("select * from person").show()
 spark.stop()
 }
}

前提：数据库访问的是default,表person中有三条数据。

 测试前先确保hadoop集群正常启动，然后需要启动hive的metastore服务。

./bin/hive --service metastore 

运行，结果如下：

 如果报错：

Exception in thread "main" org.apache.spark.sql.AnalysisException: java.lang.RuntimeException: java.io.IOException: (null) entry in command string: null chmod 0700 C:UsersdellAppDataLocalTempc530fb25-b267-4dd2-b24d-741727a6fbf3_resources;
 at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:106)
 at org.apache.spark.sql.hive.HiveExternalCatalog.databaseExists(HiveExternalCatalog.scala:194)
 at org.apache.spark.sql.internal.SharedState.externalCatalog$lzycompute(SharedState.scala:114)
 at org.apache.spark.sql.internal.SharedState.externalCatalog(SharedState.scala:102)
 at org.apache.spark.sql.hive.HiveSessionStateBuilder.externalCatalog(HiveSessionStateBuilder.scala:39)
 at org.apache.spark.sql.hive.HiveSessionStateBuilder.catalog$lzycompute(HiveSessionStateBuilder.scala:54)
 at org.apache.spark.sql.hive.HiveSessionStateBuilder.catalog(HiveSessionStateBuilder.scala:52)
 at org.apache.spark.sql.hive.HiveSessionStateBuilder$$anon$1.(HiveSessionStateBuilder.scala:69)
 at org.apache.spark.sql.hive.HiveSessionStateBuilder.analyzer(HiveSessionStateBuilder.scala:69)
 at org.apache.spark.sql.internal.baseSessionStateBuilder$$anonfun$build$2.apply(baseSessionStateBuilder.scala:293)
 at org.apache.spark.sql.internal.baseSessionStateBuilder$$anonfun$build$2.apply(baseSessionStateBuilder.scala:293)
 at org.apache.spark.sql.internal.SessionState.analyzer$lzycompute(SessionState.scala:79)
 at org.apache.spark.sql.internal.SessionState.analyzer(SessionState.scala:79)
 at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
 at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
 at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
 at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:74)
 at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:638)
 at com.tongfang.learn.spark.hive.HiveTest.main(HiveTest.java:15)

解决：

1.下载hadoop windows binary包，链接：https://github.com/steveloughran/winutils

2.在启动类的运行参数中设置环境变量，HADOOP_HOME=D:winutilshadoop-2.6.4，后面是hadoop windows 二进制包的目录。

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