hadoop - 配置单元查询因错误 “Execution Error, return code 2 from org.apache.hadoop.hive.ql.exe”而停止

Question

我正在使用CDH-5.14.2-1安装的Hive(带有Yarn)，并制作了一个保存购买历史的数据库。一张具有购买历史的表具有10亿个元组。

我尝试了以下查询来衡量Hive的性能。

SELECT c.gender, 
       g.NAME, 
       i.NAME, 
       Sum(b.num) 
FROM   customers c 
       JOIN boughts_bil b 
         ON ( c.id = b.cus_id 
              AND b.id < $var ) 
       JOIN items i 
         ON ( i.id = b.item_id ) 
       JOIN genres g 
         ON ( g.id = i.gen_id ) 
GROUP  BY c.gender, 
          g.NAME, 
          i.NAME; 

顺便说一句，由于我不想进行任何优化，所以没有分区。

当我设置“$ var = 30,000,000”时，发生错误“执行错误，从org.apache.hadoop.hive.ql.exe返回代码2”。实际上，我三个月前曾使用过相同的查询，但那时效果很好。

我检查了HistoryServer并写成如下

Diagnostics: 
Application failed due to failed ApplicationMaster. 
Only partial information is available; some values may be inaccurate.

Cloudera的计划进展顺利时是Express，但现在该计划仅适用于Enterprise。是原因吗？

还是有其他原因导致内存不足错误。

请给你你的智慧。

谢谢。

添加

尽管我更改了 $var = 50，但任务尚未完成。我在前天设置了 $var = 1,000,000，任务已完全完成。

我以为原因不是数据或查询，而是服务器。

终端消息如下:

Query ID = ..._20180813111111_92d8a1f2-4614-49c6-8833-d7b2e709c79c
Total jobs = 2
Stage-1 is selected by condition resolver.
Launching Job 1 out of 2
Number of reduce tasks not specified. Estimated from input data size: 557
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_1534123434864_0480, Tracking URL = http://...:8088/proxy/application_1534123434864_0480/
Kill Command = /.../hadoop job  -kill job_1534123434864_0480
Hadoop job information for Stage-1: number of mappers: 140; number of reducers: 557
2018-08-13 11:11:49,795 Stage-1 map = 0%,  reduce = 0%
2018-08-13 11:12:39,732 Stage-1 map = 3%,  reduce = 0%, Cumulative CPU 159.56 sec
2018-08-13 11:12:40,808 Stage-1 map = 12%,  reduce = 0%, Cumulative CPU 428.58 sec
2018-08-13 11:12:41,884 Stage-1 map = 20%,  reduce = 0%, Cumulative CPU 649.73 sec
2018-08-13 11:12:42,965 Stage-1 map = 36%,  reduce = 0%, Cumulative CPU 945.71 sec
2018-08-13 11:12:44,040 Stage-1 map = 51%,  reduce = 0%, Cumulative CPU 1089.56 sec
2018-08-13 11:12:45,112 Stage-1 map = 56%,  reduce = 0%, Cumulative CPU 1154.54 sec
2018-08-13 11:12:46,197 Stage-1 map = 58%,  reduce = 0%, Cumulative CPU 1163.98 sec
2018-08-13 11:12:48,336 Stage-1 map = 60%,  reduce = 0%, Cumulative CPU 1195.79 sec
2018-08-13 11:12:50,465 Stage-1 map = 62%,  reduce = 0%, Cumulative CPU 1221.94 sec
2018-08-13 11:12:51,529 Stage-1 map = 65%,  reduce = 0%, Cumulative CPU 1243.78 sec
2018-08-13 11:12:52,628 Stage-1 map = 68%,  reduce = 0%, Cumulative CPU 1250.12 sec
2018-08-13 11:12:54,755 Stage-1 map = 69%,  reduce = 0%, Cumulative CPU 1258.72 sec
2018-08-13 11:12:55,818 Stage-1 map = 73%,  reduce = 0%, Cumulative CPU 1310.93 sec
2018-08-13 11:12:56,878 Stage-1 map = 80%,  reduce = 0%, Cumulative CPU 1402.61 sec
2018-08-13 11:12:57,936 Stage-1 map = 83%,  reduce = 0%, Cumulative CPU 1440.37 sec
2018-08-13 11:12:58,994 Stage-1 map = 88%,  reduce = 0%, Cumulative CPU 1514.14 sec
2018-08-13 11:13:00,049 Stage-1 map = 90%,  reduce = 0%, Cumulative CPU 1545.1 sec
2018-08-13 11:13:02,163 Stage-1 map = 91%,  reduce = 0%, Cumulative CPU 1603.52 sec
2018-08-13 11:13:03,228 Stage-1 map = 94%,  reduce = 0%, Cumulative CPU 1657.94 sec
2018-08-13 11:13:04,283 Stage-1 map = 99%,  reduce = 0%, Cumulative CPU 1717.53 sec
2018-08-13 11:13:05,339 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 1730.17 sec
2018-08-13 11:13:11,744 Stage-1 map = 100%,  reduce = 1%, Cumulative CPU 1752.35 sec
2018-08-13 11:13:13,882 Stage-1 map = 100%,  reduce = 2%, Cumulative CPU 1755.7 sec
2018-08-13 11:13:14,947 Stage-1 map = 100%,  reduce = 3%, Cumulative CPU 1772.27 sec
2018-08-13 11:13:16,005 Stage-1 map = 100%,  reduce = 5%, Cumulative CPU 1818.92 sec
2018-08-13 11:13:17,067 Stage-1 map = 100%,  reduce = 7%, Cumulative CPU 1846.94 sec
2018-08-13 11:13:19,191 Stage-1 map = 100%,  reduce = 9%, Cumulative CPU 1885.14 sec
2018-08-13 11:13:20,251 Stage-1 map = 100%,  reduce = 10%, Cumulative CPU 1909.41 sec
2018-08-13 11:13:21,312 Stage-1 map = 100%,  reduce = 11%, Cumulative CPU 1922.64 sec
2018-08-13 11:13:25,546 Stage-1 map = 100%,  reduce = 13%, Cumulative CPU 1956.43 sec
2018-08-13 11:13:26,614 Stage-1 map = 100%,  reduce = 15%, Cumulative CPU 1995.36 sec
2018-08-13 11:13:27,683 Stage-1 map = 100%,  reduce = 17%, Cumulative CPU 2027.25 sec
2018-08-13 11:13:28,749 Stage-1 map = 100%,  reduce = 19%, Cumulative CPU 2066.51 sec
2018-08-13 11:13:29,819 Stage-1 map = 100%,  reduce = 20%, Cumulative CPU 2093.91 sec
2018-08-13 11:13:30,884 Stage-1 map = 100%,  reduce = 21%, Cumulative CPU 2100.15 sec
2018-08-13 11:13:31,947 Stage-1 map = 100%,  reduce = 23%, Cumulative CPU 2136.57 sec
2018-08-13 11:13:33,017 Stage-1 map = 100%,  reduce = 24%, Cumulative CPU 2168.52 sec
2018-08-13 11:13:34,076 Stage-1 map = 100%,  reduce = 27%, Cumulative CPU 2210.15 sec
2018-08-13 11:13:38,326 Stage-1 map = 100%,  reduce = 28%, Cumulative CPU 2226.99 sec
2018-08-13 11:13:39,389 Stage-1 map = 100%,  reduce = 29%, Cumulative CPU 2246.71 sec
2018-08-13 11:13:40,447 Stage-1 map = 100%,  reduce = 31%, Cumulative CPU 2281.74 sec
2018-08-13 11:13:41,511 Stage-1 map = 100%,  reduce = 33%, Cumulative CPU 2319.49 sec
2018-08-13 11:13:42,570 Stage-1 map = 100%,  reduce = 35%, Cumulative CPU 2350.72 sec
2018-08-13 11:13:45,746 Stage-1 map = 100%,  reduce = 36%, Cumulative CPU 2371.35 sec
2018-08-13 11:13:46,809 Stage-1 map = 100%,  reduce = 37%, Cumulative CPU 2391.87 sec
2018-08-13 11:13:48,924 Stage-1 map = 100%,  reduce = 39%, Cumulative CPU 2428.84 sec
2018-08-13 11:13:49,982 Stage-1 map = 100%,  reduce = 41%, Cumulative CPU 2461.64 sec
2018-08-13 11:13:51,030 Stage-1 map = 100%,  reduce = 42%, Cumulative CPU 2492.05 sec
2018-08-13 11:13:52,075 Stage-1 map = 100%,  reduce = 43%, Cumulative CPU 2512.36 sec
2018-08-13 11:13:53,138 Stage-1 map = 100%,  reduce = 46%, Cumulative CPU 2551.82 sec
2018-08-13 11:13:54,200 Stage-1 map = 100%,  reduce = 48%, Cumulative CPU 2598.15 sec
2018-08-13 11:13:55,262 Stage-1 map = 100%,  reduce = 50%, Cumulative CPU 2626.53 sec
2018-08-13 11:13:56,322 Stage-1 map = 100%,  reduce = 51%, Cumulative CPU 2644.72 sec
2018-08-13 11:13:57,362 Stage-1 map = 100%,  reduce = 52%, Cumulative CPU 2654.88 sec
2018-08-13 11:14:10,109 Stage-1 map = 100%,  reduce = 53%, Cumulative CPU 2670.23 sec
2018-08-13 11:14:11,167 Stage-1 map = 100%,  reduce = 54%, Cumulative CPU 2679.96 sec
2018-08-13 11:14:14,342 Stage-1 map = 100%,  reduce = 56%, Cumulative CPU 2709.52 sec
2018-08-13 11:14:28,034 Stage-1 map = 100%,  reduce = 57%, Cumulative CPU 2728.34 sec
2018-08-13 11:14:35,427 Stage-1 map = 100%,  reduce = 58%, Cumulative CPU 2747.36 sec
2018-08-13 11:14:39,652 Stage-1 map = 100%,  reduce = 59%, Cumulative CPU 2772.93 sec
2018-08-13 11:14:41,763 Stage-1 map = 100%,  reduce = 60%, Cumulative CPU 2788.89 sec
2018-08-13 11:14:48,042 Stage-1 map = 100%,  reduce = 61%, Cumulative CPU 2813.88 sec
2018-08-13 11:14:49,097 Stage-1 map = 100%,  reduce = 62%, Cumulative CPU 2826.24 sec
2018-08-13 11:14:53,335 Stage-1 map = 100%,  reduce = 63%, Cumulative CPU 2847.18 sec
2018-08-13 11:14:56,501 Stage-1 map = 100%,  reduce = 64%, Cumulative CPU 2868.39 sec
2018-08-13 11:14:58,614 Stage-1 map = 100%,  reduce = 65%, Cumulative CPU 2889.34 sec
2018-08-13 11:14:59,673 Stage-1 map = 100%,  reduce = 66%, Cumulative CPU 2889.52 sec
2018-08-13 11:15:01,785 Stage-1 map = 100%,  reduce = 67%, Cumulative CPU 2903.53 sec
2018-08-13 11:15:02,844 Stage-1 map = 100%,  reduce = 68%, Cumulative CPU 2909.72 sec
2018-08-13 11:15:03,903 Stage-1 map = 100%,  reduce = 69%, Cumulative CPU 2915.11 sec
2018-08-13 11:15:04,962 Stage-1 map = 100%,  reduce = 70%, Cumulative CPU 2939.29 sec
2018-08-13 11:15:06,022 Stage-1 map = 100%,  reduce = 73%, Cumulative CPU 2991.99 sec
2018-08-13 11:15:07,088 Stage-1 map = 100%,  reduce = 74%, Cumulative CPU 3008.11 sec
2018-08-13 11:15:08,147 Stage-1 map = 100%,  reduce = 75%, Cumulative CPU 3023.01 sec
2018-08-13 11:15:09,196 Stage-1 map = 100%,  reduce = 76%, Cumulative CPU 3029.96 sec
2018-08-13 11:15:12,359 Stage-1 map = 100%,  reduce = 77%, Cumulative CPU 3053.28 sec
2018-08-13 11:15:14,471 Stage-1 map = 100%,  reduce = 78%, Cumulative CPU 3074.76 sec
2018-08-13 11:15:16,585 Stage-1 map = 100%,  reduce = 79%, Cumulative CPU 3087.69 sec
2018-08-13 11:15:18,709 Stage-1 map = 100%,  reduce = 80%, Cumulative CPU 3104.28 sec
2018-08-13 11:15:20,824 Stage-1 map = 100%,  reduce = 81%, Cumulative CPU 3126.94 sec
2018-08-13 11:15:21,931 Stage-1 map = 100%,  reduce = 83%, Cumulative CPU 3166.12 sec
2018-08-13 11:15:22,979 Stage-1 map = 100%,  reduce = 85%, Cumulative CPU 3209.21 sec
2018-08-13 11:15:24,039 Stage-1 map = 100%,  reduce = 87%, Cumulative CPU 3245.82 sec
2018-08-13 11:15:25,096 Stage-1 map = 100%,  reduce = 88%, Cumulative CPU 3259.57 sec
2018-08-13 11:15:27,211 Stage-1 map = 100%,  reduce = 89%, Cumulative CPU 3275.9 sec
2018-08-13 11:15:29,326 Stage-1 map = 100%,  reduce = 90%, Cumulative CPU 3291.91 sec
2018-08-13 11:15:30,386 Stage-1 map = 100%,  reduce = 91%, Cumulative CPU 3318.16 sec
2018-08-13 11:15:31,441 Stage-1 map = 100%,  reduce = 93%, Cumulative CPU 3357.23 sec
2018-08-13 11:15:32,496 Stage-1 map = 100%,  reduce = 95%, Cumulative CPU 3382.19 sec
2018-08-13 11:15:33,548 Stage-1 map = 100%,  reduce = 96%, Cumulative CPU 3407.15 sec
2018-08-13 11:15:34,598 Stage-1 map = 100%,  reduce = 97%, Cumulative CPU 3419.89 sec
2018-08-13 11:15:37,755 Stage-1 map = 100%,  reduce = 98%, Cumulative CPU 3442.94 sec
2018-08-13 11:15:39,871 Stage-1 map = 100%,  reduce = 99%, Cumulative CPU 3449.41 sec
2018-08-13 11:15:45,128 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 3475.74 sec
MapReduce Total cumulative CPU time: 57 minutes 55 seconds 740 msec
Ended Job = job_1534123434864_0480
Execution log at: /.../..._20180813111111_92d8a1f2-4614-49c6-8833-d7b2e709c79c.log
2018-08-13 11:15:51 Starting to launch local task to process map join;  maximum memory = 1908932608
2018-08-13 11:15:52 Dump the side-table for tag: 1 with group count: 24 into file: file:/.../c33533aa-7637-4034-a3d1-2e8b857c2820/hive_2018-08-13_11-11-38_070_2752807246292956243-1/-local-10006/HashTable-Stage-4/MapJoin-mapfile01--.hashtable
2018-08-13 11:15:52 Uploaded 1 File to: file:/.../c33533aa-7637-4034-a3d1-2e8b857c2820/hive_2018-08-13_11-11-38_070_2752807246292956243-1/-local-10006/HashTable-Stage-4/MapJoin-mapfile01--.hashtable (902 bytes)
2018-08-13 11:15:52 Dump the side-table for tag: 1 with group count: 3500 into file: file:/.../c33533aa-7637-4034-a3d1-2e8b857c2820/hive_2018-08-13_11-11-38_070_2752807246292956243-1/-local-10006/HashTable-Stage-4/MapJoin-mapfile11--.hashtable
2018-08-13 11:15:52 Uploaded 1 File to: file:/.../c33533aa-7637-4034-a3d1-2e8b857c2820/hive_2018-08-13_11-11-38_070_2752807246292956243-1/-local-10006/HashTable-Stage-4/MapJoin-mapfile11--.hashtable (107794 bytes)
2018-08-13 11:15:52 End of local task; Time Taken: 1.54 sec.
Execution completed successfully
MapredLocal task succeeded
Launching Job 2 out of 2
Number of reduce tasks not specified. Estimated from input data size: 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_1534123434864_0536, Tracking URL = http://...:8088/proxy/application_1534123434864_0536/
Kill Command = /.../hadoop job  -kill job_1534123434864_0536
Hadoop job information for Stage-4: number of mappers: 4; number of reducers: 1
2018-08-13 11:16:23,048 Stage-4 map = 0%,  reduce = 0%
2018-08-13 11:16:44,240 Stage-4 map = 25%,  reduce = 0%, Cumulative CPU 2.28 sec
2018-08-13 11:16:46,330 Stage-4 map = 50%,  reduce = 0%, Cumulative CPU 5.06 sec
2018-08-13 11:16:49,473 Stage-4 map = 75%,  reduce = 0%, Cumulative CPU 9.58 sec
2018-08-13 11:16:50,520 Stage-4 map = 100%,  reduce = 0%, Cumulative CPU 15.14 sec
2018-08-13 11:17:12,471 Stage-4 map = 0%,  reduce = 0%
2018-08-13 11:17:42,680 Stage-4 map = 25%,  reduce = 0%, Cumulative CPU 2.2 sec
2018-08-13 11:17:44,779 Stage-4 map = 50%,  reduce = 0%, Cumulative CPU 5.25 sec
2018-08-13 11:17:46,873 Stage-4 map = 100%,  reduce = 0%, Cumulative CPU 15.0 sec
2018-08-13 11:18:12,006 Stage-4 map = 0%,  reduce = 0%
MapReduce Total cumulative CPU time: 15 seconds 0 msec
Ended Job = job_1534123434864_0536 with errors
Error during job, obtaining debugging information...
FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 140  Reduce: 557   Cumulative CPU: 3475.74 sec   HDFS Read: 37355213704 HDFS Write: 56143 SUCCESS
Stage-Stage-4: Map: 4  Reduce: 1   Cumulative CPU: 15.0 sec   HDFS Read: 0 HDFS Write: 0 FAIL
Total MapReduce CPU Time Spent: 58 minutes 10 seconds 740 msec
WARN: The method class org.apache.commons.logging.impl.SLF4JLogFactory#release() was invoked.
WARN: Please see http://www.slf4j.org/codes.html#release for an explanation.

并且我检查了 yarn logs -applicationId application_1534123434864_0480，并且 container_1534123434864_0480_02_000001中存在一些错误。

(1)ERROR [RMCommunicator Allocator] 
org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: 
Container complete event for unknown container container_1534123434864_0480_02_000143


(2)INFO [AsyncDispatcher event handler]
org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl: Diagnostics report from attempt_1534123434864_0480_r_000014_1000: 
Container killed on request. Exit code is 137
Container exited with a non-zero exit code 137
Killed by external signal

(3)INFO [AsyncDispatcher event handler]
org.apache.hadoop.mapreduce.v2.app.job.impl.TaskAttemptImpl:
Diagnostics report from attempt_1534123434864_0480_r_000041_1000:
Container exited with a non-zero exit code 154

(4)ERROR [ContainerLauncher #1] 
org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl: 
Container launch failed for container_1534123434864_0480_02_000241 : 
java.io.IOException: Failed on local exception: java.io.IOException: java.io.IOException: 
Connection reset from partner; Host Details : local host is: "node3"; destination host is: "node2":8041; 
    at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:772)
    at org.apache.hadoop.ipc.Client.call(Client.java:1508)
    at org.apache.hadoop.ipc.Client.call(Client.java:1441)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:230)
    at com.sun.proxy.$Proxy40.startContainers(Unknown Source)
    at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:96)
    at sun.reflect.GeneratedMethodAccessor5.invoke(Unknown Source)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:258)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:104)
    at com.sun.proxy.$Proxy41.startContainers(Unknown Source)
    at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$Container.launch(ContainerLauncherImpl.java:155)
    at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$EventProcessor.run(ContainerLauncherImpl.java:379)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.IOException: java.io.IOException: Connection reset from partner
    at org.apache.hadoop.ipc.Client$Connection$1.run(Client.java:718)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:415)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1920)
    at org.apache.hadoop.ipc.Client$Connection.handleSaslConnectionFailure(Client.java:681)
    at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:769)
    at org.apache.hadoop.ipc.Client$Connection.access$3000(Client.java:396)
    at org.apache.hadoop.ipc.Client.getConnection(Client.java:1557)
    at org.apache.hadoop.ipc.Client.call(Client.java:1480)
    ... 15 more
Caused by: java.io.IOException: Connection reset from partner
    at sun.nio.ch.FileDispatcherImpl.read0(Native Method)
    at sun.nio.ch.SocketDispatcher.read(SocketDispatcher.java:39)
    at sun.nio.ch.IOUtil.readIntoNativeBuffer(IOUtil.java:223)
    at sun.nio.ch.IOUtil.read(IOUtil.java:197)
    at sun.nio.ch.SocketChannelImpl.read(SocketChannelImpl.java:379)
    at org.apache.hadoop.net.SocketInputStream$Reader.performIO(SocketInputStream.java:57)
    at org.apache.hadoop.net.SocketIOWithTimeout.doIO(SocketIOWithTimeout.java:142)
    at org.apache.hadoop.net.SocketInputStream.read(SocketInputStream.java:161)
    at org.apache.hadoop.net.SocketInputStream.read(SocketInputStream.java:131)
    at java.io.FilterInputStream.read(FilterInputStream.java:133)
    at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
    at java.io.BufferedInputStream.read(BufferedInputStream.java:254)
    at java.io.DataInputStream.readInt(DataInputStream.java:387)
    at org.apache.hadoop.security.SaslRpcClient.saslConnect(SaslRpcClient.java:370)
    at org.apache.hadoop.ipc.Client$Connection.setupSaslConnection(Client.java:594)
    at org.apache.hadoop.ipc.Client$Connection.access$2000(Client.java:396)
    at org.apache.hadoop.ipc.Client$Connection$2.run(Client.java:761)
    at org.apache.hadoop.ipc.Client$Connection$2.run(Client.java:757)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:415)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1920)
    at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:756)
    ... 18 more

这些错误已多次显示。我以为node2服务器很麻烦。

Answer 1

我通过引用cloudera manager uninstall卸载Cloudera Manager。

然后，我再次安装Cloudera Manager。 hive 效果很好。