从源代码编译构建Hive3.1.3

编译说明

使用Hive官方提供的预编译安装包是最常见和推荐的方式来使用Hive，适用于大多数用户。这些预编译的安装包经过了测试和验证，在许多不同的环境中都能正常运行。

在某些特定情况下，可能需要从源代码编译Hive，而不是使用预编译的安装包。

编译Hive源代码的场景、原因如下：

1.定制配置：

如果希望对Hive进行一些特定的配置定制或修改，例如更改默认的参数设置、添加新的数据存储后端、集成新的执行引擎等，那么编译源代码将能够修改和定制 Hive 的配置。

2.功能扩展：

如果需要扩展Hive的功能，例如添加自定义的 UDF（用户定义函数）、UDAF（用户定义聚合函数）、UDTF（用户定义表生成函数）等，编译源代码将添加和构建这些自定义功能。

3.调试和修改 Bug：

如果在使用Hive过程中遇到了问题，或者发现了bug，并希望进行调试和修复，那么编译源代码将能够获得运行时的源代码，进而进行调试和修改。

4.最新特性和改进：

如果希望使用Hive的最新特性、改进和优化，但这些特性尚未发布到官方的预编译包中，可以从源代码编译最新的版本，以获得并使用这些功能。

5.参与社区贡献：

如果对Hive有兴趣并希望为其开发做贡献，通过编译源代码，可以获取到完整的开发环境，包括构建工具、测试框架和源代码，以便与Hive社区一起开发和贡献代码。

编译Hive3.1.3

当使用Spark作为Hive的执行引擎时，但是Hive3.1.3本身支持的Spark版本是2.3，故此需要重新编译Hive，让Hive支持较新版本的Spark。计划编译Hive支持Spark3.4.0，Hadoop版本3.1.3

更改Maven配置

更改maven的settings.xml文件，看情况决定是否添加如下仓库地址，仅供参考：

        <!-- 阿里云仓库 --><mirror><id>aliyun-central</id><name>阿里云公共仓库</name><url>https://maven.aliyun.com/repository/central</url><mirrorOf>*</mirrorOf></mirror><!-- 中央仓库 --><mirror><id>repo</id><mirrorOf>central</mirrorOf><name>Human Readable Name for this Mirror.</name><url>https://repo.maven.apache.org/maven2</url></mirror>

下载源码

下载需要编译的Hive版本源码，这里打算重新编译Hive3.1.3

wget https://archive.apache.org/dist/hive/hive-3.1.3/pache-hive-3.1.3-src.tar.gz

IDEA打开pache-hive-3.1.3-src项目，打开项目后肯定会各种爆红，不用管

修改项目pom.xml

1.修改Hadoop版本

Hive3.1.3支持的Hadoop版本是3.1.10，但是Hive与Hadoop之间记得有个范围支持，故与Hadoop相关的操作看需求是否更改

<hadoop.version>3.1.0</hadoop.version><hadoop.version>3.1.3</hadoop.version>

清楚的记得Hadoop3.1.3使用日志版本是1.7.25

<slf4j.version>1.7.10</slf4j.version><slf4j.version>1.7.25</slf4j.version>

2.修改guava版本

由于Hive运行时会加载Hadoop依赖，因此需要修改Hive中guava版本为Hadoop中的guava版本。这里即使不更改，实则在使用Hive时也可能会进行更换guava版本操作(版本差异不大可以不用更换)

<guava.version>19.0</guava.version><guava.version>27.0-jre</guava.version>

3.修改spark版本

Hive3.1.3默认支持的Spark是2.3.0，这步也是核心，使其支持Spark3.4.0，使用版本较新，看需求适当降低。另外，明确指定Spark3.4.0使用的是Scala2.13版本，一同修改

<spark.version>2.3.0</spark.version>
<scala.binary.version>2.11</scala.binary.version>
<scala.version>2.11.8</scala.version># 原计划编译spark3.4.0  特么的太多坑了 后面不得不放弃
<spark.version>3.4.0</spark.version>
<scala.binary.version>2.12</scala.binary.version>
<scala.version>2.12.17</scala.version># 掉坑里折腾惨了,降低spark版本
<spark.version>3.2.4</spark.version>
<scala.binary.version>2.12</scala.binary.version>
<scala.version>2.12.17</scala.version>

修改hive源码

修改说明

修改Hive源代码，会对其进行删除、修改、新增操作，下图是Git版本控制对比图，大家应该都能看懂吧。但还是说明一下：-：删除该行代码 +：新增、修改该行代码

修改hive源码这个操作是核心操作，具体修改哪些源代码，参考：https://github.com/gitlbo/hive/commits/3.1.2

修改standalone-metastore模块

具体修改参考：https://github.com/gitlbo/hive/commit/c073e71ef43699b7aa68cad7c69a2e8f487089fd

创建ColumnsStatsUtils类

代码如下：

/** Licensed to the Apache Software Foundation (ASF) under one* or more contributor license agreements.  See the NOTICE file* distributed with this work for additional information* regarding copyright ownership.  The ASF licenses this file* to you under the Apache License, Version 2.0 (the* "License"); you may not use this file except in compliance* with the License.  You may obtain a copy of the License at**     http://www.apache.org/licenses/LICENSE-2.0** Unless required by applicable law or agreed to in writing, software* distributed under the License is distributed on an "AS IS" BASIS,* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.* See the License for the specific language governing permissions and* limitations under the License.*/package org.apache.hadoop.hive.metastore.columnstats;import org.apache.hadoop.hive.metastore.api.ColumnStatisticsObj;
import org.apache.hadoop.hive.metastore.columnstats.cache.DateColumnStatsDataInspector;
import org.apache.hadoop.hive.metastore.columnstats.cache.DecimalColumnStatsDataInspector;
import org.apache.hadoop.hive.metastore.columnstats.cache.DoubleColumnStatsDataInspector;
import org.apache.hadoop.hive.metastore.columnstats.cache.LongColumnStatsDataInspector;
import org.apache.hadoop.hive.metastore.columnstats.cache.StringColumnStatsDataInspector;/*** Utils class for columnstats package.*/
public final class ColumnsStatsUtils {private ColumnsStatsUtils(){}/*** Convertes to DateColumnStatsDataInspector if it's a DateColumnStatsData.* @param cso ColumnStatisticsObj* @return DateColumnStatsDataInspector*/public static DateColumnStatsDataInspector dateInspectorFromStats(ColumnStatisticsObj cso) {DateColumnStatsDataInspector dateColumnStats;if (cso.getStatsData().getDateStats() instanceof DateColumnStatsDataInspector) {dateColumnStats =(DateColumnStatsDataInspector)(cso.getStatsData().getDateStats());} else {dateColumnStats = new DateColumnStatsDataInspector(cso.getStatsData().getDateStats());}return dateColumnStats;}/*** Convertes to StringColumnStatsDataInspector* if it's a StringColumnStatsData.* @param cso ColumnStatisticsObj* @return StringColumnStatsDataInspector*/public static StringColumnStatsDataInspector stringInspectorFromStats(ColumnStatisticsObj cso) {StringColumnStatsDataInspector columnStats;if (cso.getStatsData().getStringStats() instanceof StringColumnStatsDataInspector) {columnStats =(StringColumnStatsDataInspector)(cso.getStatsData().getStringStats());} else {columnStats = new StringColumnStatsDataInspector(cso.getStatsData().getStringStats());}return columnStats;}/*** Convertes to LongColumnStatsDataInspector if it's a LongColumnStatsData.* @param cso ColumnStatisticsObj* @return LongColumnStatsDataInspector*/public static LongColumnStatsDataInspector longInspectorFromStats(ColumnStatisticsObj cso) {LongColumnStatsDataInspector columnStats;if (cso.getStatsData().getLongStats() instanceof LongColumnStatsDataInspector) {columnStats =(LongColumnStatsDataInspector)(cso.getStatsData().getLongStats());} else {columnStats = new LongColumnStatsDataInspector(cso.getStatsData().getLongStats());}return columnStats;}/*** Convertes to DoubleColumnStatsDataInspector* if it's a DoubleColumnStatsData.* @param cso ColumnStatisticsObj* @return DoubleColumnStatsDataInspector*/public static DoubleColumnStatsDataInspector doubleInspectorFromStats(ColumnStatisticsObj cso) {DoubleColumnStatsDataInspector columnStats;if (cso.getStatsData().getDoubleStats() instanceof DoubleColumnStatsDataInspector) {columnStats =(DoubleColumnStatsDataInspector)(cso.getStatsData().getDoubleStats());} else {columnStats = new DoubleColumnStatsDataInspector(cso.getStatsData().getDoubleStats());}return columnStats;}/*** Convertes to DecimalColumnStatsDataInspector* if it's a DecimalColumnStatsData.* @param cso ColumnStatisticsObj* @return DecimalColumnStatsDataInspector*/public static DecimalColumnStatsDataInspector decimalInspectorFromStats(ColumnStatisticsObj cso) {DecimalColumnStatsDataInspector columnStats;if (cso.getStatsData().getDecimalStats() instanceof DecimalColumnStatsDataInspector) {columnStats =(DecimalColumnStatsDataInspector)(cso.getStatsData().getDecimalStats());} else {columnStats = new DecimalColumnStatsDataInspector(cso.getStatsData().getDecimalStats());}return columnStats;}
}

接着修改以下内容，具体修改参考以下截图说明

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/aggr/DateColumnStatsAggregator.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/aggr/DecimalColumnStatsAggregator.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/aggr/DoubleColumnStatsAggregator.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/aggr/LongColumnStatsAggregator.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/aggr/StringColumnStatsAggregator.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/cache/DateColumnStatsDataInspector.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/cache/DecimalColumnStatsDataInspector.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/cache/DoubleColumnStatsDataInspector.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/cache/LongColumnStatsDataInspector.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/cache/StringColumnStatsDataInspector.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/merge/DateColumnStatsMerger.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/merge/DecimalColumnStatsMerger.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/merge/DoubleColumnStatsMerger.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/merge/LongColumnStatsMerger.java

standalone-metastore/src/main/java/org/apache/hadoop/hive/metastore/columnstats/merge/StringColumnStatsMerger.java

修改ql模块

ql/src/test/org/apache/hadoop/hive/ql/stats/TestStatsUtils.java

ql/src/test/org/apache/hadoop/hive/ql/exec/tez/SampleTezSessionState.java

ql/src/java/org/apache/hadoop/hive/ql/exec/tez/WorkloadManager.java

修改spark-client模块

spark-client/src/main/java/org/apache/hive/spark/client/metrics/ShuffleWriteMetrics.java

spark-client/src/main/java/org/apache/hive/spark/counter/SparkCounter.java

修改druid-handler模块

druid-handler/src/java/org/apache/hadoop/hive/druid/serde/DruidScanQueryRecordReader.java

修改llap-server模块

llap-server/src/java/org/apache/hadoop/hive/llap/daemon/impl/AMReporter.java

llap-server/src/java/org/apache/hadoop/hive/llap/daemon/impl/LlapTaskReporter.java

llap-server/src/java/org/apache/hadoop/hive/llap/daemon/impl/TaskExecutorService.java

修改llap-tez模块

llap-tez/src/java/org/apache/hadoop/hive/llap/tezplugins/LlapTaskSchedulerService.java

修改llap-common模块

llap-common/src/java/org/apache/hadoop/hive/llap/AsyncPbRpcProxy.java

编译打包

对Hive源码修改完成后，执行编译打包命令：

mvn clean package -Pdist -DskipTests -Dmaven.javadoc.skip=truemvn clean package -Pdist -DskipTests

在执行编译打包命令过程中，肯定会有各种问题的，这些问题是需要解决的，期间遇到的各种异常请参考下方异常集合对比解决。

注意点

1.有时本地仓库中的缓存可能会引起依赖项解析错误。可以尝试清理该项目依赖的本地仓库中的maven包，这个命令会清理pom.xml中的包，并重新下载，执行以下命令：

mvn dependency:purge-local-repository

2.修改Pom.xml文件版本号，或更改代码、安装Jar到本地仓库后，建议关闭IDEA重新打开进入，防止缓存、或者更新不及时

异常集合

注意：以下异常均是按照编译Hive支持Spark3.4.0过程中产生的异常，后来降低了Spark的版本。

异常1

1.maven会提示无法找到、无法下载某个Jar包、或者下载Jar耗时长(即使开启魔法也是）

例如：maven仓库找不到hive-upgrade-acid-3.1.3.jar与pentaho-aggdesigner-algorithm-5.1.5-jhyde_2.jar

具体异常如下，仅供参考：

[ERROR] Failed to execute goal on project hive-upgrade-acid: Could not resolve dependencies for project org.apache.hive:hive-upgrade-acid:jar:3.1.3: Failure to find org.pentaho:pentaho-aggdesigner-algorithm:jar:5.1.5-jhyde in https://maven.aliyun.com/repository/central was cached in the local repository, resolution will not be reattempted until the update interval of aliyun-central has elapsed or updates are forced -> [Help 1]

解决方案：

到以下仓库搜索需要的Jar包，手动下载，并安装到本地仓库

仓库地址1：https://mvnrepository.com/
仓库地址2：https://central.sonatype.com/
仓库地址3：https://developer.aliyun.com/mvn/search

将一个JAR安装到本地仓库，示例命令的语法：

mvn install:install-file -Dfile=<path-to-jar> -DgroupId=<group-id> -DartifactId=<artifact-id> -Dversion=<version> -Dpackaging=<packaging><path-to-jar>：JAR文件的路径，可以是本地文件系统的绝对路径。
<group-id>：项目组ID，通常采用反向域名格式，例如com.example。
<artifact-id>：项目的唯一标识符，通常是项目名称。
<version>：项目的版本号。
<packaging>：JAR文件的打包类型，例如jar。

mvn install:install-file -Dfile=./hive-upgrade-acid-3.1.3.jar -DgroupId=org.apache.hive -DartifactId=hive-upgrade-acid -Dversion=3.1.3 -Dpackaging=jarmvn install:install-file -Dfile=./pentaho-aggdesigner-algorithm-5.1.5-jhyde.jar -DgroupId=org.pentaho -DartifactId=pentaho-aggdesigner-algorithm -Dversion=5.1.5-jhyde -Dpackaging=jarmvn install:install-file -Dfile=./hive-metastore-2.3.3.jar -DgroupId=org.apache.hive -DartifactId=hive-metastore -Dversion=2.3.3 -Dpackaging=jarmvn install:install-file -Dfile=./hive-exec-3.1.3.jar -DgroupId=org.apache.hive -DartifactId=hive-exec -Dversion=3.1.3 -Dpackaging=jar

异常2

提示bash相关东西，心凉了一大截。由于window下操作，bash不支持。

[ERROR] Failed to execute goal org.apache.maven.plugins:maven-antrun-plugin:1.7:run (generate-version-annotation) on project hive-common: An Ant BuildException has occured: Execute failed: java.io.IOException: Cannot run program "bash" (in directory "C:\Users\JackChen\Desktop\apache-hive-3.1.3-src\common"): CreateProcess error=2, 系统找不到指定的文件。
[ERROR] around Ant part ...<exec failonerror="true" executable="bash">... @ 4:46 in C:\Users\JackChen\Desktop\apache-hive-3.1.3-src\common\target\antrun\build-main.xml

解决方案：

正常来说，作为开发者，肯定有安装Git，Git有bash窗口，即在Git的Bash窗口执行编译打包命令

mvn clean package -Pdist -DskipTests

异常3

当前进度在Hive Llap Server失败

[INFO] Hive Llap Client ................................... SUCCESS [  4.030 s]
[INFO] Hive Llap Tez ...................................... SUCCESS [  4.333 s]
[INFO] Hive Spark Remote Client ........................... SUCCESS [  5.382 s]
[INFO] Hive Query Language ................................ SUCCESS [01:28 min]
[INFO] Hive Llap Server ................................... FAILURE [  7.180 s]
[INFO] Hive Service ....................................... SKIPPED
[INFO] Hive Accumulo Handler .............................. SKIPPED
[INFO] Hive JDBC .......................................... SKIPPED
[INFO] Hive Beeline ....................................... SKIPPED

[ERROR] Failed to execute goal org.apache.maven.plugins:maven-compiler-plugin:3.6.1:compile (default-compile) on project hive-llap-server: Compilation failure
[ERROR] /C:/Users/JackChen/Desktop/apache-hive-3.1.3-src/llap-server/src/java/org/apache/hadoop/hive/llap/daemon/impl/QueryTracker.java:[30,32] org.apache.logging.slf4j.Log4jMarker▒▒org.apache.logging.slf4j▒в▒▒ǹ▒▒▒▒▒; ▒޷▒▒▒▒ⲿ▒▒▒▒▒▒ж▒▒▒▒▒з▒▒▒
[ERROR]
[ERROR] -> [Help 1]
[ERROR]
[ERROR] To see the full stack trace of the errors, re-run Maven with the -e switch.
[ERROR] Re-run Maven using the -X switch to enable full debug logging.
[ERROR]
[ERROR] For more information about the errors and possible solutions, please read the following articles:
[ERROR] [Help 1] http://cwiki.apache.org/confluence/display/MAVEN/MojoFailureException
[ERROR]
[ERROR] After correcting the problems, you can resume the build with the command
[ERROR]   mvn <args> -rf :hive-llap-server

public class QueryTracker extends AbstractService {// private static final Marker QUERY_COMPLETE_MARKER = new Log4jMarker(new Log4jQueryCompleteMarker());private static final Marker QUERY_COMPLETE_MARKER = MarkerFactory.getMarker("MY_CUSTOM_MARKER");}

异常4

编译执行到Hive HCatalog Webhcat模块失败

[INFO] Hive HCatalog ...................................... SUCCESS [ 10.947 s]
[INFO] Hive HCatalog Core ................................. SUCCESS [  7.237 s]
[INFO] Hive HCatalog Pig Adapter .......................... SUCCESS [  2.652 s]
[INFO] Hive HCatalog Server Extensions .................... SUCCESS [  9.255 s]
[INFO] Hive HCatalog Webhcat Java Client .................. SUCCESS [  2.435 s]
[INFO] Hive HCatalog Webhcat .............................. FAILURE [  7.284 s]
[INFO] Hive HCatalog Streaming ............................ SKIPPED
[INFO] Hive HPL/SQL ....................................... SKIPPED
[INFO] Hive Streaming ..................................... SKIPPED

具体异常：

[ERROR] Failed to execute goal org.apache.maven.plugins:maven-compiler-plugin:3.6.1:compile (default-compile) on project hive-webhcat: Compilation failure
[ERROR] /root/apache-hive-3.1.3-src/hcatalog/webhcat/svr/src/main/java/org/apache/hive/hcatalog/templeton/Main.java:[258,31] 对于FilterHolder(java.lang.Class<org.apache.hadoop.hdfs.web.AuthFilter>), 找不到合适的构造器
[ERROR]     构造器 org.eclipse.jetty.servlet.FilterHolder.FilterHolder(org.eclipse.jetty.servlet.BaseHolder.Source)不适用
[ERROR]       (参数不匹配; java.lang.Class<org.apache.hadoop.hdfs.web.AuthFilter>无法转换为org.eclipse.jetty.servlet.BaseHolder.Source)
[ERROR]     构造器 org.eclipse.jetty.servlet.FilterHolder.FilterHolder(java.lang.Class<? extends javax.servlet.Filter>)不适用
[ERROR]       (参数不匹配; java.lang.Class<org.apache.hadoop.hdfs.web.AuthFilter>无法转换为java.lang.Class<? extends javax.servlet.Filter>)
[ERROR]     构造器 org.eclipse.jetty.servlet.FilterHolder.FilterHolder(javax.servlet.Filter)不适用
[ERROR]       (参数不匹配; java.lang.Class<org.apache.hadoop.hdfs.web.AuthFilter>无法转换为javax.servlet.Filter)
[ERROR]
[ERROR] -> [Help 1]
[ERROR]
[ERROR] To see the full stack trace of the errors, re-run Maven with the -e switch.
[ERROR] Re-run Maven using the -X switch to enable full debug logging.
[ERROR]
[ERROR] For more information about the errors and possible solutions, please read the following articles:
[ERROR] [Help 1] http://cwiki.apache.org/confluence/display/MAVEN/MojoFailureException
[ERROR]
[ERROR] After correcting the problems, you can resume the build with the command
[ERROR]   mvn <args> -rf :hive-webhcat

看源码发现AuthFilter是继承AuthenticationFilter，AuthenticationFilter又实现Filter，应该不会出现此异常信息才对，于是手动修改源码进行强制转换试试，发现任然不行。

  public FilterHolder makeAuthFilter() throws IOException {
//    FilterHolder authFilter = new FilterHolder(AuthFilter.class);FilterHolder authFilter = new FilterHolder((Class<? extends Filter>) AuthFilter.class);UserNameHandler.allowAnonymous(authFilter);

解决方案：

在IDEA中单独编译打包此模块，发现是能构建成功的

[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time:  40.755 s
[INFO] Finished at: 2023-08-06T21:39:17+08:00
[INFO] ------------------------------------------------------------------------

于是乎产生了一个想法：

1.因为项目使用Maven进行打包（执行mvn package），再次执行相同的命令将不会重新打包项目

2.所以先针对项目执行clean命令，然后对该Webhcat模块打包，最后在整体编译打包时，不执行clean操作，直接运行 mvn package -Pdist -DskipTests。

注意：后来降低了Spark版本，没有产生该问题

编译打包成功

经过数个小时的解决问题与漫长的编译打包，终于成功，发现这个界面是多么的美好。

[INFO] --- maven-dependency-plugin:2.8:copy (copy) @ hive-packaging ---
[INFO] Configured Artifact: org.apache.hive:hive-jdbc:standalone:3.1.3:jar
[INFO] Copying hive-jdbc-3.1.3-standalone.jar to C:\Users\JackChen\Desktop\apache-hive-3.1.3-src\packaging\target\apache-hive-3.1.3-jdbc.jar
[INFO] ------------------------------------------------------------------------
[INFO] Reactor Summary for Hive 3.1.3:
[INFO]
[INFO] Hive Upgrade Acid .................................. SUCCESS [  5.264 s]
[INFO] Hive ............................................... SUCCESS [  0.609 s]
[INFO] Hive Classifications ............................... SUCCESS [  1.183 s]
[INFO] Hive Shims Common .................................. SUCCESS [  2.239 s]
[INFO] Hive Shims 0.23 .................................... SUCCESS [  2.748 s]
[INFO] Hive Shims Scheduler ............................... SUCCESS [  2.286 s]
[INFO] Hive Shims ......................................... SUCCESS [  1.659 s]
[INFO] Hive Common ........................................ SUCCESS [  9.671 s]
[INFO] Hive Service RPC ................................... SUCCESS [  6.608 s]
[INFO] Hive Serde ......................................... SUCCESS [  6.042 s]
[INFO] Hive Standalone Metastore .......................... SUCCESS [ 42.432 s]
[INFO] Hive Metastore ..................................... SUCCESS [  2.304 s]
[INFO] Hive Vector-Code-Gen Utilities ..................... SUCCESS [  1.150 s]
[INFO] Hive Llap Common ................................... SUCCESS [  3.343 s]
[INFO] Hive Llap Client ................................... SUCCESS [  2.380 s]
[INFO] Hive Llap Tez ...................................... SUCCESS [  2.476 s]
[INFO] Hive Spark Remote Client ........................... SUCCESS [31:34 min]
[INFO] Hive Query Language ................................ SUCCESS [01:09 min]
[INFO] Hive Llap Server ................................... SUCCESS [  7.230 s]
[INFO] Hive Service ....................................... SUCCESS [ 28.343 s]
[INFO] Hive Accumulo Handler .............................. SUCCESS [  6.179 s]
[INFO] Hive JDBC .......................................... SUCCESS [ 19.058 s]
[INFO] Hive Beeline ....................................... SUCCESS [  4.078 s]
[INFO] Hive CLI ........................................... SUCCESS [  3.436 s]
[INFO] Hive Contrib ....................................... SUCCESS [  4.770 s]
[INFO] Hive Druid Handler ................................. SUCCESS [ 17.245 s]
[INFO] Hive HBase Handler ................................. SUCCESS [  6.759 s]
[INFO] Hive JDBC Handler .................................. SUCCESS [  4.202 s]
[INFO] Hive HCatalog ...................................... SUCCESS [  1.757 s]
[INFO] Hive HCatalog Core ................................. SUCCESS [  5.455 s]
[INFO] Hive HCatalog Pig Adapter .......................... SUCCESS [  4.662 s]
[INFO] Hive HCatalog Server Extensions .................... SUCCESS [  4.629 s]
[INFO] Hive HCatalog Webhcat Java Client .................. SUCCESS [  4.652 s]
[INFO] Hive HCatalog Webhcat .............................. SUCCESS [  8.899 s]
[INFO] Hive HCatalog Streaming ............................ SUCCESS [  4.934 s]
[INFO] Hive HPL/SQL ....................................... SUCCESS [  7.684 s]
[INFO] Hive Streaming ..................................... SUCCESS [  4.049 s]
[INFO] Hive Llap External Client .......................... SUCCESS [  3.674 s]
[INFO] Hive Shims Aggregator .............................. SUCCESS [  0.557 s]
[INFO] Hive Kryo Registrator .............................. SUCCESS [03:17 min]
[INFO] Hive TestUtils ..................................... SUCCESS [  1.154 s]
[INFO] Hive Packaging ..................................... SUCCESS [01:58 min]
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time:  38:22 min (Wall Clock)
[INFO] Finished at: 2023-08-08T22:50:15+08:00
[INFO] ------------------------------------------------------------------------

总结

在整个编译、打包过程中，有2点非常重要：

1.相关Jar无法下载或者下载缓慢问题，一定要想方设法解决，因为Jar是构建的核心，缺一不可

2.Jar依赖解决了，但是任然存在可能的兼容性问题，编译问题，遇到问题一定要一一解决，解决一步走一步