我对hive是新手，我使用hbase-1.1.0、hadoop-2.5.1和hive-0.13来满足我的需求。
设置非常好，我可以使用beeline运行配置单元查询。
查询：从x\u表中选择count（*）。
查询以37.848秒完成。
我在maven项目中设置了相同的环境，并尝试使用配置单元客户机执行一些select查询，但效果很好。但是当我尝试执行相同的count查询时，mapreduce作业无法完成。看起来又重新开始了工作。如何解决这个问题？
代码

Connection con = DriverManager.getConnection("jdbc:hive2://abc:10000/default","", "");
    Statement stmt = con.createStatement();               
    String query = "select count(*) from X_Table                                    
    ResultSet res = stmt.executeQuery(query);       
    while (res.next()) {
        //code here
    }

日志详细信息：

Total jobs = 1 
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):  
    set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:  
    set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
    set mapreduce.job.reduces=<number>
Starting Job = job_1429243611915_0030, Tracking URL = http://master:8088/proxy/application_1429243611915_0030/
Kill Command = /usr/local/pcs/hadoop/bin/hadoop job  -kill job_1429243611915_0030
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2015-04-20 09:28:02,616 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:29:02,728 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:30:03,432 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:31:04,054 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:32:04,675 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:33:05,298 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:34:05,866 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:35:06,419 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:36:06,985 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:37:07,551 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:38:08,289 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:39:09,184 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:40:09,780 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:41:10,367 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:42:10,965 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:43:11,595 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:44:12,181 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:45:12,952 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:46:13,590 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:47:14,218 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:48:14,790 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:49:15,378 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:50:16,014 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:51:16,808 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:52:17,378 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:53:17,928 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:54:18,491 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:55:19,049 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:56:19,797 Stage-1 map = 0%,  reduce = 0%
2015-04-20 09:57:20,344 Stage-1 map = 0%,  reduce = 0%
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
    set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
    set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
    set mapreduce.job.reduces=<number>
Starting Job = job_1429243611915_0031, Tracking URL = http://master:8088/proxy/application_1429243611915_0031/
Kill Command = /usr/local/pcs/hadoop/bin/hadoop job  -kill job_1429243611915_0031
2015-04-20 09:58:20,858 Stage-1 map = 0%,  reduce = 0%