从Hive llap特性的出现，分析作用、部署、使用细节问题，总结hive llap使用经验和注意事项。
(From the appearance of the Hive llap feature, analyze the function, deployment, and use details, and summarize the experience and precautions of the hive llap)
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LLAP是hive 2.0.0版本引入的新特性，hive官方称为(Live long and process)，hortonworks公司的CDH称为(low-latency analytical processing)，其实它们都是一样的，都是实现将数据预取、缓存到基于yarn运行的守护进程中，降低和减少系统IO和与HDFS DataNode的交互，具体的特性细节参考官方文档 Hive llap (如果链接未生效，在文章后面的链接中获取)，但是由于版本更新频繁和官方文档的维护不力因素，很多地方和使用上让人概念不清、正确和错误分不清，特别是用CDH这样的集成套件，很多细节被忽略，本文一一来细说和总结各类问题。

1 hive llap该怎么部署

分两种情况：
1. 如果使用的hadoop yarn版本是3.1.0以下(不包含3.1.0)，需要使用 Apache slider 来部署，因为在hadoop yarn 3.1.0之前，yarn本身不支持长时间运行的服务(long running services)，而slider组件是可以打包、管理和部署长时间运行的服务到yarn上运行的。
2. 如果使用的hadoop yarn版本是3.1.0及以上，完全不需要slider组件了，因为从 hadoop yarn 3.1.0 开始，yarn已经合并支持long running services了，slider项目也停止更新了。

因此，部署时要考虑使用的组件版本，再确定部署方案，对于开源项目，使用的版本和环境很重要，如果组件本身已经提供特性和功能，并且一直处于维护状态，建议尽量不要使用其它组件替代，替代成本和异常问题远比想象的高。
当然，如果你使用的是CDH类的集成套件，套件本身已经集成封装，每个套件版本会提供相应的支持，这些内容就无需多虑了。

2 注意事项

  1. llap 目前只支持tez引擎，需要先部署好hive和tez；
  2. 由于llap依赖zookeeper和hadoop组件，如果集群开启了安全认证(比如kerberos)，llap也要进行安全认证相关配置，使用到的配置参数如：
<property>
    <name>hive.llap.daemon.keytab.file</name>
    <value>/etc/security/keytabs/demo.keytab</value>
</property>

<property>
    <name>hive.llap.daemon.service.principal</name>
    <value>demo/sywu@sywukeb</value>
</property>

<property>
    <name>hive.llap.task.scheduler.am.registry.keytab.file</name>
    <value>/etc/security/keytabs/demo.service.keytab</value>
</property>

<property>
    <name>hive.llap.task.scheduler.am.registry.principal</name>
    <value>demo/sywu@sywukeb</value>
</property>

另外随着程序的更新，官方文档上的参数参差不齐，有些参数需要阅读和从代码中查找。

  1. 一些网上资料和CDH文档的部署方式使用hive用户和权限运行llap服务，hive的权限很大，如果集群很大，使用的人很多，对权限控制粒度要求高，不适合使用这种方式，应该考虑多个llap服务，为不同的用户或者项目组开放不同的llap服务。
  2. 由于LLAP所具有的优势(预取、缓存)，对于大的集群，考虑面向不同场景和用户使用不同的llap服务，提高查询命中率，提升性能，我认为是合理的。

3 llap初始化

以下以hadoop 3.1.0，hive 3.1.0，tez 0.9.1，集群无安全认证为例，首先配置llap；

<property>
    <name>hive.llap.execution.mode</name>
    <value>all</value>
</property>
<property>
    <name>hive.execution.mode</name>
    <value>llap</value>
</property>

<property>
    <name>hive.llap.daemon.service.hosts</name>
    <value>@sywu-llap01</value>
</property>

<property>
    <name>hive.llap.daemon.memory.per.instance.mb</name>
    <value>25600</value>
</property>

<property>
    <name>hive.llap.daemon.num.executors</name>
    <value>8</value>
</property>

<property>
    <name>hive.llap.zk.sm.connectionString</name>
    <value>sywu01:2181</value>
</property>

<property>
    <name>hive.llap.zk.registry.namespace</name>
    <value>hive_sywu01</value>
</property>

<property>
    <name>hive.llap.zk.registry.user</name>
    <value>sywu</value>
</property>

hive.llap.daemon.service.hosts 配置llap 实例名称，这个名称和启动的名称相同。然后打包和准备部署llap 服务的文件；

hive --service llap --name sywu-llap01 --instances 4 --size 60g --loglevel info --cache 30g --executors 10 --iothreads 10 --args " -XX:+UseG1GC -XX:+ResizeTLAB -XX:+UseNUMA -XX:-ResizePLAB"

这个命令会在当前目录生成llap 服务文件夹，里面包含启动llap的脚本，llap的相关配置和jar包；

$ ll
total 184M
-rwxr-xr-x 1 sywu01 sywu01 184M Oct 20 15:28 llap-20Oct2020.tar.gz
-rwxr-xr-x 1 sywu01 sywu01  273 Oct 20 15:28 run.sh
-rwxr-xr-x 1 sywu01 sywu01 2.0K Oct 20 15:29 Yarnfile

执行run.sh 文件启动llap服务。到此llap部署到yarn上并运行。

LLAPSTATUS
--------------------------------------------------------------------------------
LLAP Application running with ApplicationId=application_1602234006497_0592
--------------------------------------------------------------------------------
LLAP Application running with ApplicationId=application_1602234006497_0592
--------------------------------------------------------------------------------

{
  "amInfo" : {
    "appName" : "sywu-llap01",
    "appType" : "yarn-service",
    "appId" : "application_1602234006497_0592"
  },
  "state" : "RUNNING_ALL",
  "desiredInstances" : 4,
  "liveInstances" : 4,
  "launchingInstances" : 0,
  "appStartTime" : 0,
  "runningThresholdAchieved" : false,
  "runningInstances" : [ {
    "hostname" : "sywu01",
    "containerId" : "container_e48_1602234006497_0592_01_000013",
    "statusUrl" : "http://sywu01:15002/status",
    "webUrl" : "http://sywu01:15002",
    "rpcPort" : 45795,
    "mgmtPort" : 15004,
    "shufflePort" : 15551,
    "yarnContainerExitStatus" : 0
  }, {
    "hostname" : "sywu02",
    "containerId" : "container_e48_1602234006497_0592_01_000005",
    "statusUrl" : "http://sywu02:15002/status",
    "webUrl" : "http://sywu02:15002",
    "rpcPort" : 46845,
    "mgmtPort" : 15004,
    "shufflePort" : 15551,
    "yarnContainerExitStatus" : 0
  }, {
    "hostname" : "sywu01",
    "containerId" : "container_e48_1602234006497_0592_01_000008",
    "statusUrl" : "http://sywu01:15002/status",
    "webUrl" : "http://sywu01:15002",
    "rpcPort" : 33382,
    "mgmtPort" : 15004,
    "shufflePort" : 15551,
    "yarnContainerExitStatus" : 0
  }, {
    "hostname" : "sywu03",
    "containerId" : "container_e48_1602234006497_0592_01_000010",
    "statusUrl" : "http://sywu03:15002/status",
    "webUrl" : "http://sywu03:15002",
    "rpcPort" : 43520,
    "mgmtPort" : 15004,
    "shufflePort" : 15551,
    "yarnContainerExitStatus" : 0
  } ]
}

4 性能测试

到此，hive已经有mr和tez引擎，并支持llap，使用hortonworks公司开源的 hive-testbench项目 生成1Tb数据；

 $ ./tpcds-setup.sh 1000

用query10.sql 中的关联脚本查询测试；

select  
  cd_gender,cd_marital_status,cd_education_status,count(*) cnt1,cd_purchase_estimate,count(*) cnt2,cd_credit_rating,count(*) cnt3,cd_dep_count,count(*) cnt4,cd_dep_employed_count,count(*) cnt5,cd_dep_college_count,count(*) cnt6
 from
  customer c,customer_address ca,customer_demographics
 where
  c.c_current_addr_sk = ca.ca_address_sk and
  ca_county in ('Fillmore County','McPherson County','Bonneville County','Boone County','Brown County') and
  cd_demo_sk = c.c_current_cdemo_sk and 
  exists (select *
          from store_sales,date_dim
          where c.c_customer_sk = ss_customer_sk and
                ss_sold_date_sk = d_date_sk and
                d_year = 2000 and
                d_moy between 3 and 3+3) and
   (exists (select *
            from web_sales,date_dim
            where c.c_customer_sk = ws_bill_customer_sk and
                  ws_sold_date_sk = d_date_sk and
                  d_year = 2000 and
                  d_moy between 3 ANd 3+3) or 
    exists (select * 
            from catalog_sales,date_dim
            where c.c_customer_sk = cs_ship_customer_sk and
                  cs_sold_date_sk = d_date_sk and
                  d_year = 2000 and
                  d_moy between 3 and 3+3))
 group by cd_gender,
          cd_marital_status,
          cd_education_status,
          cd_purchase_estimate,
          cd_credit_rating,
          cd_dep_count,
          cd_dep_employed_count,
          cd_dep_college_count
 order by cd_gender,
          cd_marital_status,
          cd_education_status,
          cd_purchase_estimate,
          cd_credit_rating,
          cd_dep_count,
          cd_dep_employed_count,
          cd_dep_college_count
limit 100;

mr 引擎执行情况；

INFO  : Query ID = sywu01_20201023113411_add04434-7382-4376-8883-26ab298b1c6f
INFO  : Total jobs = 8
INFO  : Starting task [Stage-24:MAPREDLOCAL] in parallel
INFO  : Starting task [Stage-25:MAPREDLOCAL] in parallel
INFO  : Starting task [Stage-26:MAPREDLOCAL] in parallel
INFO  : Starting task [Stage-27:MAPREDLOCAL] in parallel
INFO  : Launching Job 1 out of 8
INFO  : Starting task [Stage-20:MAPRED] in parallel
INFO  : Launching Job 2 out of 8
INFO  : Starting task [Stage-14:MAPRED] in parallel
INFO  : Launching Job 3 out of 8
INFO  : Starting task [Stage-11:MAPRED] in parallel
INFO  : Launching Job 4 out of 8
INFO  : Starting task [Stage-18:MAPRED] in parallel
INFO  : Starting task [Stage-17:CONDITIONAL] in parallel
INFO  : Launching Job 5 out of 8
INFO  : Starting task [Stage-3:MAPRED] in parallel
INFO  : Launching Job 6 out of 8
INFO  : Starting task [Stage-4:MAPRED] in parallel
INFO  : Launching Job 7 out of 8
INFO  : Starting task [Stage-5:MAPRED] in parallel
INFO  : MapReduce Jobs Launched: 
INFO  : Stage-Stage-18: Map: 3   Cumulative CPU: 779.28 sec   HDFS Read: 77140427 HDFS Write: 5298244 SUCCESS
INFO  : Stage-Stage-20: Map: 350   Cumulative CPU: 4134.07 sec   HDFS Read: 3203667384 HDFS Write: 193140638 SUCCESS
INFO  : Stage-Stage-11: Map: 153  Reduce: 151   Cumulative CPU: 4631.57 sec   HDFS Read: 886558268 HDFS Write: 46326191 SUCCESS
INFO  : Stage-Stage-14: Map: 257  Reduce: 271   Cumulative CPU: 6646.95 sec   HDFS Read: 1049371661 HDFS Write: 106287345 SUCCESS
INFO  : Stage-Stage-3: Map: 19  Reduce: 2   Cumulative CPU: 394.45 sec   HDFS Read: 351370942 HDFS Write: 1399528 SUCCESS
INFO  : Stage-Stage-4: Map: 2  Reduce: 1   Cumulative CPU: 15.71 sec   HDFS Read: 1415039 HDFS Write: 12296 SUCCESS
INFO  : Stage-Stage-5: Map: 1  Reduce: 1   Cumulative CPU: 8.31 sec   HDFS Read: 23606 HDFS Write: 7168 SUCCESS
INFO  : Total MapReduce CPU Time Spent: 0 days 4 hours 36 minutes 50 seconds 340 msec
INFO  : Completed executing command(queryId=sywu01_20201023113411_add04434-7382-4376-8883-26ab298b1c6f); Time taken: 838.106 seconds
INFO  : OK
+------------+--------------------+-----------------------+-------+-----------------------+-------+-------------------+-------+---------------+-------+------------------------+-------+-----------------------+-------+
| cd_gender  | cd_marital_status  |  cd_education_status  | cnt1  | cd_purchase_estimate  | cnt2  | cd_credit_rating  | cnt3  | cd_dep_count  | cnt4  | cd_dep_employed_count  | cnt5  | cd_dep_college_count  | cnt6  |
+------------+--------------------+-----------------------+-------+-----------------------+-------+-------------------+-------+---------------+-------+------------------------+-------+-----------------------+-------+
| F          | D                  | 2 yr Degree           | 1     | 500                   | 1     | Good              | 1     | 0             | 1     | 0                      | 1     | 4                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 500                   | 1     | Good              | 1     | 1             | 1     | 0                      | 1     | 5                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 500                   | 1     | Good              | 1     | 1             | 1     | 1                      | 1     | 1                     | 1     |
....
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 0             | 1     | 4                      | 1     | 4                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 3             | 1     | 2                      | 1     | 1                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 5             | 1     | 4                      | 1     | 0                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 5             | 1     | 6                      | 1     | 6                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | Low Risk          | 1     | 0             | 1     | 3                      | 1     | 4                     | 1     |
+------------+--------------------+-----------------------+-------+-----------------------+-------+-------------------+-------+---------------+-------+------------------------+-------+-----------------------+-------+
100 rows selected (850.686 seconds)

tez 引擎执行情况；

INFO  : Query ID = sywu01_20201023175253_265d5780-7be4-47ad-ad4b-ef8154bb3842
INFO  : Total jobs = 1
INFO  : Launching Job 1 out of 1
INFO  : Starting task [Stage-1:MAPRED] in parallel
----------------------------------------------------------------------------------------------
        VERTICES      MODE        STATUS  TOTAL  COMPLETED  RUNNING  PENDING  FAILED  KILLED  
----------------------------------------------------------------------------------------------
Map 6 .......... container     SUCCEEDED     14         14        0        0       0      10  
Map 7 .......... container     SUCCEEDED      4          4        0        0       3       3  
Map 1 .......... container     SUCCEEDED      6          6        0        0       0       1  
Map 9 .......... container     SUCCEEDED      1          1        0        0       0       1  
Reducer 5 ...... container     SUCCEEDED      1          1        0        0       0       1  
Map 8 .......... container     SUCCEEDED     20         20        0        0       0       0  
Map 10 ......... container     SUCCEEDED      6          6        0        0       0       0  
Reducer 11 ..... container     SUCCEEDED    234        234        0        0       0       0  
Map 12 ......... container     SUCCEEDED     10         10        0        0       0       0  
Reducer 13 ..... container     SUCCEEDED    234        234        0        0       0       0  
Reducer 2 ...... container     SUCCEEDED    234        234        0        0       0       0  
Reducer 3 ...... container     SUCCEEDED    145        145        0        0       0       0  
Reducer 4 ...... container     SUCCEEDED      1          1        0        0       0       0  
----------------------------------------------------------------------------------------------
VERTICES: 13/13  [==========================>>] 100%  ELAPSED TIME: 36.01 s    
----------------------------------------------------------------------------------------------
INFO  : Completed executing command(queryId=sywu01_20201023175253_265d5780-7be4-47ad-ad4b-ef8154bb3842); Time taken: 54.039 seconds
INFO  : OK

- Query Execution Summary
- ----------------------------------------------------------------------------------------------
- OPERATION                            DURATION
- ----------------------------------------------------------------------------------------------
- Compile Query                           0.00s
- Prepare Plan                            0.00s
- Get Query Coordinator (AM)              0.00s
- Submit Plan                         1603446798.35s
- Start DAG                               1.05s
- Run DAG                                34.93s
- ----------------------------------------------------------------------------------------------
- 
- Task Execution Summary
- ----------------------------------------------------------------------------------------------
-   VERTICES      DURATION(ms)   CPU_TIME(ms)    GC_TIME(ms)   INPUT_RECORDS   OUTPUT_RECORDS
- ----------------------------------------------------------------------------------------------
-      Map 1          16546.00        130,790          1,748      13,963,497           82,778
-     Map 10           4568.00         49,540            484      27,755,681           15,784
-     Map 12           3554.00         75,240            987      55,261,069           41,887
-      Map 6          14520.00        131,700          5,584       6,000,000           42,697
-      Map 7          13490.00         34,760            780       1,920,800        1,920,800
-      Map 8           4073.00         80,900            472     106,067,119           73,854
-      Map 9           3146.00         10,200            375          10,000              366
- Reducer 11           1531.00         27,450            623          15,784          157,859
- Reducer 13           1026.00         32,250            697          41,887          261,474
-  Reducer 2           4577.00        267,060          4,652         575,965           22,170
-  Reducer 3           4046.00        263,850          5,876          22,170           61,923
-  Reducer 4            503.00          1,430             20          61,923                0
-  Reducer 5          12877.00          2,360              0          82,778                3
- ----------------------------------------------------------------------------------------------

+------------+--------------------+-----------------------+-------+-----------------------+-------+-------------------+-------+---------------+-------+------------------------+-------+-----------------------+-------+
| cd_gender  | cd_marital_status  |  cd_education_status  | cnt1  | cd_purchase_estimate  | cnt2  | cd_credit_rating  | cnt3  | cd_dep_count  | cnt4  | cd_dep_employed_count  | cnt5  | cd_dep_college_count  | cnt6  |
+------------+--------------------+-----------------------+-------+-----------------------+-------+-------------------+-------+---------------+-------+------------------------+-------+-----------------------+-------+
| F          | D                  | 2 yr Degree           | 1     | 500                   | 1     | Good              | 1     | 0             | 1     | 0                      | 1     | 4                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 500                   | 1     | Good              | 1     | 1             | 1     | 0                      | 1     | 5                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 500                   | 1     | Good              | 1     | 1             | 1     | 1                      | 1     | 1                     | 1     |
....
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 0             | 1     | 4                      | 1     | 4                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 3             | 1     | 2                      | 1     | 1                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 5             | 1     | 4                      | 1     | 0                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 5             | 1     | 6                      | 1     | 6                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | Low Risk          | 1     | 0             | 1     | 3                      | 1     | 4                     | 1     |
+------------+--------------------+-----------------------+-------+-----------------------+-------+-------------------+-------+---------------+-------+------------------------+-------+-----------------------+-------+
100 rows selected (61.765 seconds)

tez引擎 + llap 执行情况；

INFO  : Query ID = sywu01_20201023174916_f4c7d891-7395-4720-9eb1-5bf1fd7c024c
INFO  : Total jobs = 1
INFO  : Launching Job 1 out of 1
INFO  : Starting task [Stage-1:MAPRED] in parallel
----------------------------------------------------------------------------------------------
        VERTICES      MODE        STATUS  TOTAL  COMPLETED  RUNNING  PENDING  FAILED  KILLED  
----------------------------------------------------------------------------------------------
Map 6 ..........      llap     SUCCEEDED      3          3        0        0       0       0  
Map 7 ..........      llap     SUCCEEDED      4          4        0        0       0       0  
Map 1 ..........      llap     SUCCEEDED      6          6        0        0       0       0  
Map 9 ..........      llap     SUCCEEDED      1          1        0        0       0       0  
Reducer 5 ......      llap     SUCCEEDED      1          1        0        0       0       0  
Map 8 ..........      llap     SUCCEEDED      6          6        0        0       0       0  
Map 10 .........      llap     SUCCEEDED      6          6        0        0       0       0  
Reducer 11 .....      llap     SUCCEEDED    234        234        0        0       0       0  
Map 12 .........      llap     SUCCEEDED      7          7        0        0       0       0  
Reducer 13 .....      llap     SUCCEEDED    234        234        0        0       0       0  
Reducer 2 ......      llap     SUCCEEDED    234        234        0        0       0       2  
Reducer 3 ......      llap     SUCCEEDED    145        145        0        0       0       3  
Reducer 4 ......      llap     SUCCEEDED      1          1        0        0       0       0  
----------------------------------------------------------------------------------------------
VERTICES: 13/13  [==========================>>] 100%  ELAPSED TIME: 11.34 s    
----------------------------------------------------------------------------------------------
INFO  : Completed executing command(queryId=sywu01_20201023174916_f4c7d891-7395-4720-9eb1-5bf1fd7c024c); Time taken: 30.035 seconds
INFO  : OK

 - Query Execution Summary
 - ----------------------------------------------------------------------------------------------
 - OPERATION                            DURATION
 - ----------------------------------------------------------------------------------------------
 - Compile Query                           0.00s
 - Prepare Plan                            0.00s
 - Get Query Coordinator (AM)              0.00s
 - Submit Plan                         1603446581.98s
 - Start DAG                               1.00s
 - Run DAG                                11.02s
 - ----------------------------------------------------------------------------------------------
 - 
 - Task Execution Summary
 - ----------------------------------------------------------------------------------------------
 -   VERTICES      DURATION(ms)   CPU_TIME(ms)    GC_TIME(ms)   INPUT_RECORDS   OUTPUT_RECORDS
 - ----------------------------------------------------------------------------------------------
 -      Map 1           2042.00              0              0      13,963,497           82,778
 -     Map 10           1527.00              0              0      27,755,681           15,767
 -     Map 12           1530.00              0              0      55,261,069           40,935
 -      Map 6            514.00              0              0       6,000,000           42,697
 -      Map 7            514.00              0              0       1,920,800        1,920,800
 -      Map 8           3063.00              0              0     106,067,119           59,399
 -      Map 9              0.00              0              0          10,000              366
 - Reducer 11           1536.00              0              0          15,767           14,579
 - Reducer 13           1019.00              0              0          40,935           33,694
 -  Reducer 2           3059.00              0              0         190,450           22,170
 -  Reducer 3           2540.00              0              0          22,170           14,423
 -  Reducer 4            278.00              0              0          14,423                0
 -  Reducer 5           2041.00              0              0          82,778                3
 - ----------------------------------------------------------------------------------------------

+------------+--------------------+-----------------------+-------+-----------------------+-------+-------------------+-------+---------------+-------+------------------------+-------+-----------------------+-------+
| cd_gender  | cd_marital_status  |  cd_education_status  | cnt1  | cd_purchase_estimate  | cnt2  | cd_credit_rating  | cnt3  | cd_dep_count  | cnt4  | cd_dep_employed_count  | cnt5  | cd_dep_college_count  | cnt6  |
+------------+--------------------+-----------------------+-------+-----------------------+-------+-------------------+-------+---------------+-------+------------------------+-------+-----------------------+-------+
| F          | D                  | 2 yr Degree           | 1     | 500                   | 1     | Good              | 1     | 0             | 1     | 0                      | 1     | 4                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 500                   | 1     | Good              | 1     | 1             | 1     | 0                      | 1     | 5                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 500                   | 1     | Good              | 1     | 1             | 1     | 1                      | 1     | 1                     | 1     |
....
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 0             | 1     | 4                      | 1     | 4                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 3             | 1     | 2                      | 1     | 1                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 5             | 1     | 4                      | 1     | 0                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | High Risk         | 1     | 5             | 1     | 6                      | 1     | 6                     | 1     |
| F          | D                  | 2 yr Degree           | 1     | 3500                  | 1     | Low Risk          | 1     | 0             | 1     | 3                      | 1     | 4                     | 1     |
+------------+--------------------+-----------------------+-------+-----------------------+-------+-------------------+-------+---------------+-------+------------------------+-------+-----------------------+-------+
100 rows selected (37.668 seconds)

5 总结

可以看到，mr引擎的执行耗时(850.686 seconds)是tez引擎执行耗时(61.765 seconds)和tez引擎+llap执行耗时(37.668 seconds)的近14倍，资源使用率远远高于后者；tez引擎和tez引擎+llap确实极大的提升了查询性能，也让hive更越进一步，而这一切的代价，仅是对架构、底层的了解和认识以及组件的升级和更新能够获得的。

链接

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本文链接：https://www.cnblogs.com/lanston/p/13868096.html