hive1.2.1源码导入eclipse

http://www.aboutyun.com/thread-18338-1-1.html

软件版本:

hive1.2.1 ,eclipse4.5,maven3.2 ,JDK1.7

软件准备:

hive:

 

环境准备:

(1). 安装好的Hadoop集群(伪分布式亦可);

(2) linux 下maven环境;(这里需要说下,maven编译hive,在windows下是不通的,因为里面需要bash的支持,所以直接使用linux编译hive就好)

0. 编译前,建议把maven的local_reposity 配置下,同时配置源如下(开源中国的maven源,相对国外的源较快):

[Java]  纯文本查看  复制代码
?
01
02
03
04
05
06
07
08
09
10
11
12
<mirror>
         <id>nexus-osc</id>
         <mirrorOf>central</mirrorOf>
         <name>Nexus osc</name>
         <url>http: //maven.oschina.net/content/groups/public/</url>
     </mirror>
     <mirror>
         <id>nexus-osc-thirdparty</id>
         <mirrorOf>thirdparty</mirrorOf>
         <name>Nexus osc thirdparty</name>
         <url>http: //maven.oschina.net/content ... dparty/</url>
     </mirror>


1. 编译Hive,下载hive1.2.1的源码,并解压到linux某目录,按照下面的命令进行编译(进入hive源码解压后路径):

(1)mvn clean install -DskipTests -Phadoop-2

[Java]  纯文本查看  复制代码
?
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
[INFO] Reactor Summary:
[INFO]
[INFO] Hive ............................................... SUCCESS [  4.457 s]
[INFO] Hive Shims Common .................................. SUCCESS [  5.047 s]
[INFO] Hive Shims 0 .20S ................................... SUCCESS [  2.017 s]
[INFO] Hive Shims 0.23 .................................... SUCCESS [  7.157 s]
[INFO] Hive Shims Scheduler ............................... SUCCESS [  1.796 s]
[INFO] Hive Shims ......................................... SUCCESS [  1.674 s]
[INFO] Hive Common ........................................ SUCCESS [  5.711 s]
[INFO] Hive Serde ......................................... SUCCESS [  7.577 s]
[INFO] Hive Metastore ..................................... SUCCESS [ 18.044 s]
[INFO] Hive Ant Utilities ................................. SUCCESS [  1.373 s]
[INFO] Spark Remote Client ................................ SUCCESS [ 10.962 s]
[INFO] Hive Query Language ................................ SUCCESS [ 05 : 12 min]
[INFO] Hive Service ....................................... SUCCESS [ 42.408 s]
[INFO] Hive Accumulo Handler .............................. SUCCESS [ 01 : 40 min]
[INFO] Hive JDBC .......................................... SUCCESS [  9.021 s]
[INFO] Hive Beeline ....................................... SUCCESS [ 12.194 s]
[INFO] Hive CLI ........................................... SUCCESS [ 12.576 s]
[INFO] Hive Contrib ....................................... SUCCESS [  3.031 s]
[INFO] Hive HBase Handler ................................. SUCCESS [ 01 : 54 min]
[INFO] Hive HCatalog ...................................... SUCCESS [ 28.797 s]
[INFO] Hive HCatalog Core ................................. SUCCESS [  5.609 s]
[INFO] Hive HCatalog Pig Adapter .......................... SUCCESS [ 23.254 s]
[INFO] Hive HCatalog Server Extensions .................... SUCCESS [ 01 : 15 min]
[INFO] Hive HCatalog Webhcat Java Client .................. SUCCESS [  2.036 s]
[INFO] Hive HCatalog Webhcat .............................. SUCCESS [ 49.390 s]
[INFO] Hive HCatalog Streaming ............................ SUCCESS [  4.387 s]
[INFO] Hive HWI ........................................... SUCCESS [  1.768 s]
[INFO] Hive ODBC .......................................... SUCCESS [  1.053 s]
[INFO] Hive Shims Aggregator .............................. SUCCESS [  0.111 s]
[INFO] Hive TestUtils ..................................... SUCCESS [  0.550 s]
[INFO] Hive Packaging ..................................... SUCCESS [  3.195 s]
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 14 : 31 min
[INFO] Finished at: 2015 - 10 -15T05: 25 : 11 - 07 : 00
[INFO] Final Memory: 89M/416M


(2)清空相关输出:mvn eclipse:clean

(3)编译成eclipse工程:

mvn eclipse:eclipse -DdownloadSources -DdownloadJavadocs -Phadoop-2

[Java]  纯文本查看  复制代码
?
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
[INFO] Reactor Summary:
[INFO]
[INFO] Hive ............................................... SUCCESS [  7.396 s]
[INFO] Hive Shims Common .................................. SUCCESS [  3.983 s]
[INFO] Hive Shims 0 .20S ................................... SUCCESS [  2.734 s]
[INFO] Hive Shims 0.23 .................................... SUCCESS [ 16.801 s]
[INFO] Hive Shims Scheduler ............................... SUCCESS [  2.143 s]
[INFO] Hive Shims ......................................... SUCCESS [  1.958 s]
[INFO] Hive Common ........................................ SUCCESS [  4.495 s]
[INFO] Hive Serde ......................................... SUCCESS [  6.760 s]
[INFO] Hive Metastore ..................................... SUCCESS [  3.512 s]
[INFO] Hive Ant Utilities ................................. SUCCESS [  0.252 s]
[INFO] Spark Remote Client ................................ SUCCESS [  6.719 s]
[INFO] Hive Query Language ................................ SUCCESS [  7.988 s]
[INFO] Hive Service ....................................... SUCCESS [ 55.204 s]
[INFO] Hive Accumulo Handler .............................. SUCCESS [ 11 : 49 min]
[INFO] Hive JDBC .......................................... SUCCESS [  1.607 s]
[INFO] Hive Beeline ....................................... SUCCESS [ 35 : 22 min]
[INFO] Hive CLI ........................................... SUCCESS [ 01 : 28 min]
[INFO] Hive Contrib ....................................... SUCCESS [  1.797 s]
[INFO] Hive HBase Handler ................................. SUCCESS [ 10 : 35 min]
[INFO] Hive HCatalog ...................................... SUCCESS [  5.775 s]
[INFO] Hive HCatalog Core ................................. SUCCESS [ 01 : 23 min]
[INFO] Hive HCatalog Pig Adapter .......................... SUCCESS [ 01 : 10 min]
[INFO] Hive HCatalog Server Extensions .................... SUCCESS [ 07 : 20 min]
[INFO] Hive HCatalog Webhcat Java Client .................. SUCCESS [  1.968 s]
[INFO] Hive HCatalog Webhcat .............................. SUCCESS [ 01 : 53 min]
[INFO] Hive HCatalog Streaming ............................ SUCCESS [  2.089 s]
[INFO] Hive HWI ........................................... SUCCESS [  1.816 s]
[INFO] Hive ODBC .......................................... SUCCESS [  1.284 s]
[INFO] Hive Shims Aggregator .............................. SUCCESS [  0.064 s]
[INFO] Hive TestUtils ..................................... SUCCESS [  2.947 s]
[INFO] Hive Packaging ..................................... SUCCESS [  2.837 s]
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 01 : 13 h
[INFO] Finished at: 2015 - 10 -15T19: 53 : 05 - 07 : 00
[INFO] Final Memory: 68M/306M


这个过程会比较慢;编译后,文件大小大概有:391M左右

hive1.2.1源码导入eclipse_第1张图片 


2. 编译后工程导入eclipse中

这里导入需要分为两种情况,分为导入windows下的eclipse和导入linux下的eclipse中;(因为一般使用机器都是windows的,所以如果可以使用windows,则最好)

2.1 工程导入windows的eclipse中;

打开eclipse,右键-> Import ,选择编译后的文件夹(这里需要把编译后的文件下载到windows上);即可看到如下的界面:

hive1.2.1源码导入eclipse_第2张图片 



当然,这里会有些错误,比如jdk/tool.jar找不到等等,这个是因为编译的jdk和windows的jdk不一样,调整下即可。

(1)运行 hive-cli 工程的CliDriver(当然,要先启动hive相关进行,hive --service metastore & ;  hive --service hiveserver2 &)
         运行后会直接报错,说 driver “hive-site.xml ”not in Classpath 什么的错误,修改方法:

打开hive-common工程的本地目录的target/test-classes路径

hive1.2.1源码导入eclipse_第3张图片 

修改里面的core-site.xml 以及hive-site.xml ,这里面的配置就参考hadoop集群以及hive的配置即可

然后再次运行CliDriver,发现报下面的错误:

[Plain Text]  纯文本查看  复制代码
?
1
2
3
4
Exception in thread "main" java.lang.RuntimeException: org.apache.hadoop.ipc.RemoteException: Server IPC version 9 cannot communicate with client version 4
     at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:522)
     at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:677)
     at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:621)



这个是版本不匹配的错误,通过打印java的classpath,发现hadoop1的jar包在hadoop2的jar包前面

hive1.2.1源码导入eclipse_第4张图片 

这样子肯定是有 问题的,集群都使用的是hadoop2的版本,但是代码却用的hadoop1,这样报这个错就没啥奇怪的了。那问题是出在了哪呢?

通过查看hive-shims-common工程,发现其工程的依赖只有hadoop1,没有hadoop2,而hive-cli工程也是依赖hive-shims-common工程,这也就解释了为什么 Java 的classpath里面hadoop1的jar包在hadoop2前面了。

此路不通!

(2)运行hive-beeline工程的BeeLine

直接运行,进入beeline交互式命令终端,如下图:

hive1.2.1源码导入eclipse_第5张图片 


发现是可以连接hive的,比如mr查询:

hive1.2.1源码导入eclipse_第6张图片 

但是这个不可以调试,即使用debug模式,仍然不能调试。

所以对于阅读源码,查看调用关系来说这种模式也不是很好。

2.2 导入到linux的eclipse工程

   此导入和windows不无差别。

3. 直接新建工程,使用编译后的hive jar包(此处的jar包不是指自己编译的,而是官网直接提供的),就apache-hive-1.2.1-bin.tar.gz文件。

3.1 在windows的eclipse中新建hive工程

hive1.2.1源码导入eclipse_第7张图片 

同时新建一个类,如上图所示。

这里还需要注意:

a. 引入编译后的hive的lib包的所有jar包;

b. 引入 MySQL 的连接jar包;

c. 引入hadoop的相关jar包

hive1.2.1源码导入eclipse_第8张图片 

(1)写一个测试程序,调用CliDriver,出现下面的错误:

[Java]  纯文本查看  复制代码
?
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
2015 - 10 - 22 22 : 25 : 19 , 837  INFO [main] (HiveMetaStoreClient.java: 376 ) - Trying to connect to metastore with URI thrift: //192.168.0.100:9083
Exception in thread "main" java.lang.RuntimeException: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient
     at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java: 522 )
     at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java: 662 )
     at test.MainTest.main(MainTest.java: 8 )
Caused by: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient
     at org.apache.hadoop.hive.metastore.MetaStoreUtils.newInstance(MetaStoreUtils.java: 1523 )
     at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.<init>(RetryingMetaStoreClient.java: 86 )
     at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.getProxy(RetryingMetaStoreClient.java: 132 )
     at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.getProxy(RetryingMetaStoreClient.java: 104 )
     at org.apache.hadoop.hive.ql.metadata.Hive.createMetaStoreClient(Hive.java: 3005 )
     at org.apache.hadoop.hive.ql.metadata.Hive.getMSC(Hive.java: 3024 )
     at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java: 503 )
     ... 2 more
Caused by: java.lang.reflect.InvocationTargetException
     at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
     at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java: 57 )
     at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java: 45 )
     at java.lang.reflect.Constructor.newInstance(Constructor.java: 526 )
     at org.apache.hadoop.hive.metastore.MetaStoreUtils.newInstance(MetaStoreUtils.java: 1521 )
     ... 8 more
Caused by: java.lang.NullPointerException
     at java.lang.ProcessBuilder.start(ProcessBuilder.java: 1010 )
     at org.apache.hadoop.util.Shell.runCommand(Shell.java: 482 )
     at org.apache.hadoop.util.Shell.run(Shell.java: 455 )
     at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java: 715 )
     at org.apache.hadoop.util.Shell.execCommand(Shell.java: 808 )
     at org.apache.hadoop.util.Shell.execCommand(Shell.java: 791 )
     at org.apache.hadoop.security.ShellBasedUnixGroupsMapping.getUnixGroups(ShellBasedUnixGroupsMapping.java: 84 )
     at org.apache.hadoop.security.ShellBasedUnixGroupsMapping.getGroups(ShellBasedUnixGroupsMapping.java: 52 )
     at org.apache.hadoop.security.JniBasedUnixGroupsMappingWithFallback.getGroups(JniBasedUnixGroupsMappingWithFallback.java: 51 )
     at org.apache.hadoop.security.Groups.getGroups(Groups.java: 176 )
     at org.apache.hadoop.security.UserGroupInformation.getGroupNames(UserGroupInformation.java: 1488 )
     at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.open(HiveMetaStoreClient.java: 436 )
     at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.<init>(HiveMetaStoreClient.java: 236 )
     at org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient.<init>(SessionHiveMetaStoreClient.java: 74 )
     ... 13 more


通过跟踪排查,发现是windows中的hadoop没有配置winutils.exe 所致也就是最开始的错误:

[AppleScript]  纯文本查看  复制代码
?
1
Could not locate executable D : \jars\hadoop 2.6 \hadoop -2.6 . 0 \bin\winutils.exe in the Hadoop binarie


(如果只是windows提交mr任务,这个没有配置,也是可以的,但是在hive源码里面有一个检查,如果是windows提交查询的话,需要检查,没有就会报空指针异常);这个错误可以google之来修改,这里不说,下面也就没有再在这条路下面走了。

(2)写一个调用程序,运行BeeLine,这个没有测试。

3.2 linux的eclipse新建hive工程:

建立的工程和windows并无二致,如下:

同样编写程序调用CliDriver,Debug运行,如下所示(需要注意我在这里并没有配置hadoop相关目录):

hive1.2.1源码导入eclipse_第9张图片 

做一个查询,看是否可以启动debug模式:

hive1.2.1源码导入eclipse_第10张图片 

这里看到的确是进入了debug模式。

如何添加源码?看下图

hive1.2.1源码导入eclipse_第11张图片 


4. 总结:

(1) hive1.2.1目前使用源码编译得到的版本,并不支持hadoop2的调试;(就个人所作的工作的结果来看);

(2)hive1.2.1使用eclipse调试源码可以使用新建工程的方式,然后导入官网编译的hive包及hadoop包进行调试,同时需要注意一般需要在linux环境下调试,如果需要在windows下调试,需要安装winutils.exe ;

你可能感兴趣的:(hive1.2.1源码导入eclipse)