hive jdbc连接不成功。。报错org.apache.thrift.transport.TTransportException: Invalid status -128

Posted 2023-05-09

用JDBC 连接hive，不成功。后台报错显示下面的日志。。。

[HiveServer2-Handler-Pool: Thread-28]: server.TThreadPoolServer (TThreadPoolServer.java:run(253)) - Error occurred during processing of message.
java.lang.RuntimeException: org.apache.thrift.transport.TTransportException: Invalid status -128
at org.apache.thrift.transport.TSaslServerTransport$Factory.getTransport(TSaslServerTransport.java:219)
at org.apache.thrift.server.TThreadPoolServer$WorkerProcess.run(TThreadPoolServer.java:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
Caused by: org.apache.thrift.transport.TTransportException: Invalid status -128
at org.apache.thrift.transport.TSaslTransport.sendAndThrowMessage(TSaslTransport.java:230)
at org.apache.thrift.transport.TSaslTransport.receiveSaslMessage(TSaslTransport.java:184)
at org.apache.thrift.transport.TSaslServerTransport.handleSaslStartMessage(TSaslServerTransport.java:125)
at org.apache.thrift.transport.TSaslTransport.open(TSaslTransport.java:262)
at org.apache.thrift.transport.TSaslServerTransport.open(TSaslServerTransport.java:41)
at org.apache.thrift.transport.TSaslServerTransport$Factory.getTransport(TSaslServerTransport.java:216)
... 4 more

参考技术A jdbc和连接池对于你这个场景来说，都足够，既然用spring管理了，建议还是使用连接池，另外，spring自身没有实现连接池，一般都是对第三方连接池的包装，常见的有C3P0，dbcp以及最近比较流行的boneCP等，这几个配置都差不多太多，以boneCP为例：
<bean id="dataSource" class="com.jolbox.bonecp.BoneCPDataSource"
destroy-method="close">
<property name="driverClass" value="$jdbc.driverClass" />
<property name="jdbcUrl" value="$jdbc.url" />
<property name="username" value="$jdbc.user" />
<property name="password" value="$jdbc.password" />
<property name="idleConnectionTestPeriod" value="60" />
<property name="idleMaxAge" value="240" />
<property name="maxConnectionsPerPartition" value="30" />
<property name="minConnectionsPerPartition" value="10" />
<property name="partitionCount" value="2" />
<property name="acquireIncrement" value="5" />
<property name="statementsCacheSize" value="100" />
<property name="releaseHelperThreads" value="3" />
</bean>
<bean id="jdbcTemplate" class="org.springframework.jdbc.core.JdbcTemplate">
<property name="dataSource" ref="dataSource" />
</bean>本回答被提问者和网友采纳

通过远程jdbc方式连接到hive数据仓库

1.启动hiveserver2服务器，监听端口是10000,启动名令：hive --service hiveserver2 &;//将其放在后台进行运行，判断启动是否成功的标志是：jps,是否有RunJar进程，或者netstat -anop |grep 10000查看10000端口是否连接
，如果可以连接，那么就可以使用beeline通过$>hive service hiveserver2这个命令连接进来
2.通过beeline的命令行连接到hiveserver2,可以直接写$>beeline 等价于:$>hive --service beeline，连接到数据库：$beeline>！connect jdbc:hive2://localhost/mydb1连接到数据库hive数据库mydb1
3.!help，打印出帮助汇总
4.beeline下面的命令：！tables

hive命令

//创建表
$hive>create table if not exists t1(name string) comment ‘xx‘ row format delimited fields terminated by ‘,‘ stored as textfile;
//创建外部表

$hive>create external table if not exists t1(name string) comment ‘xx‘ row format delimited fields terminated by ‘,‘ stored as textfile;
//查看数据
$hive>desc t2 ;
$hive>desc formatted t2;
$hive>load data local inpath ‘/home/centos/customers.txt‘ into table t2 ;//从本地文件上传到hive表中,local是上传文件，
//复制表
$mysql>create table tt as select * from users ; //复制表，携带数据和表结构
$mysql>create table tt like users ; //复制表，只携带表结构，不带数据

hive>create table tt as select * from users;
hive>create table tt  like users ;
hive>select count(*) from users;    //这个需要转成mr进行处理，count(*) 查询要转成mr查询
hive>select id,name from t2 order by id desc ;//order by是全排序,要转成mr,以内需要进行聚合

分区表

hive的优化手段之一：创建分区表
在hive中数据库是目录，表是目录，分区表还是目录，表下的分区仍然是目录，从目录层面控制搜索数据的范围
创建分区表
$hive>create table t3(id int,name string ,age int) partitioned by (year int,month int) row format delimited fields terminated by ","
//显示分区表的分区信息
hive>show partitions t5;
//添加分区修改表
$hive>altertable t3 add partition (year=2014,month=1) partition(year =2015,month=2);
hdfs -lsr /;//添加完成之后查看目录
//加载数据到指定分区
$hive>load data local inpath ‘/home/centos/customers.txt‘ into table t5 partition(year=2015,month=3);