大数据开发之Hive篇7-Hive临时表

原创只是甲 2020-12-28

7886

备注:
Hive 版本 2.1.1

一.Hive临时表介绍

作为临时表创建的表将只对当前会话可见。数据将存储在用户的scratch目录中，并在会话结束时删除。

如果用数据库中已经存在的永久表的数据库/表名创建了一个临时表，那么在该会话中，对该表的任何引用都将解析为临时表，而不是永久表。如果不删除临时表或将其重命名为不冲突的名称，用户将无法在该会话中访问原始表。

临时表存在如下限制:

不支持分区列
不支持创建索引

Hive的临时表在数据加载的过程中会频繁使用到，对于复杂的业务逻辑，可以将数据先存储在临时表，然后再从临时表取值进行进一步计算。

二.Hive临时表测试

语法:

CREATE TEMPORARY TABLE ...
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2.1 Hive临时表数据存储设置

从Hive1.1开始临时表可以存储在内存或SSD，使用hive.exec.temporary.table.storage参数进行配置，该参数有三种取值：memory、ssd、default。

如果内存足够大，将中间数据一直存储在内存，可以大大提升计算性能。

测试记录:
将hive临时表存储路径改为memory(内存)

hive> 
    > set hive.exec.temporary.table.storage;
hive.exec.temporary.table.storage=default
hive> 
    > set hive.exec.temporary.table.storage = memory;
hive> set hive.exec.temporary.table.storage;
hive.exec.temporary.table.storage=memory
hive> 
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2.1 Hive临时表测试

代码:

set hive.exec.temporary.table.storage = memory;
-- 创建临时表 存储在内存中
create temporary table tmp_fact_sale as
select * from ods_fact_sale limit 1000000;
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测试记录:

hive> set hive.exec.temporary.table.storage = memory;
hive> create temporary table tmp_fact_sale as
    > select * from ods_fact_sale limit 1000000;
Query ID = root_20201211145008_ce21643b-765b-4869-8069-9ef340924fbb
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_1606698967173_0180, Tracking URL = http://hp1:8088/proxy/application_1606698967173_0180/
Kill Command = /opt/cloudera/parcels/CDH-6.3.1-1.cdh6.3.1.p0.1470567/lib/hadoop/bin/hadoop job  -kill job_1606698967173_0180
Hadoop job information for Stage-1: number of mappers: 117; number of reducers: 1
2020-12-11 14:50:17,943 Stage-1 map = 0%,  reduce = 0%
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2020-12-11 14:58:35,129 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 823.71 sec
MapReduce Total cumulative CPU time: 13 minutes 43 seconds 710 msec
Ended Job = job_1606698967173_0180
Moving data to directory hdfs://nameservice1/tmp/hive/root/e6af3fe0-c2f2-4bc5-8d3f-54edbc9af7ac/_tmp_space.db/488a6e38-d7a0-425c-892a-73547bdfec51
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 117  Reduce: 1   Cumulative CPU: 823.71 sec   HDFS Read: 4798139962 HDFS Write: 41066220 HDFS EC Read: 0 SUCCESS
Total MapReduce CPU Time Spent: 13 minutes 43 seconds 710 msec
OK
Time taken: 507.819 seconds


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