hive lateral view 与 explode详解

最新推荐文章于 2025-07-07 22:30:00 发布

bitcarmanlee

最新推荐文章于 2025-07-07 22:30:00 发布

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分类专栏： hive 文章标签： hive explode lateral view

本文链接：https://blog.youkuaiyun.com/bitcarmanlee/article/details/51926530

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本文深入探讨了Hive中的UDTF（如explode）与LateralView的功能及应用实例，详述如何利用这些工具处理复杂数据结构，如数组和映射，并展示如何进行有效的数据拆分和聚合。

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1.explode

hive wiki对于expolde的解释如下：

explode() takes in an array (or a map) as an input and outputs the elements of the array (map) as separate rows. UDTFs can be used in the SELECT expression list and as a part of LATERAL VIEW.

As an example of using explode() in the SELECT expression list, consider a table named myTable that has a single column (myCol) and two rows:

这里写图片描述

Then running the query:

SELECT explode(myCol) AS myNewCol FROM myTable;

will produce:
这里写图片描述
The usage with Maps is similar:

SELECT explode(myMap) AS (myMapKey, myMapValue) FROM myMapTable;

总结起来一句话：explode就是将hive一行中复杂的array或者map结构拆分成多行。

使用实例：
xxx表中有一个字段mvt为string类型，数据格式如下：

[{“eid”:“38”,“ex”:“affirm_time_Android”,“val”:“1”,“vid”:“31”,“vr”:“var1”},{“eid”:“42”,“ex”:“new_comment_Android”,“val”:“1”,“vid”:“34”,“vr”:“var1”},{“eid”:“40”,“ex”:“new_rpname_Android”,“val”:“1”,“vid”:“1”,“vr”:“var1”},{“eid”:“19”,“ex”:“hotellistlpage_Android”,“val”:“1”,“vid”:“1”,“vr”:“var01”},{“eid”:“29”,“ex”:“bookhotelpage_Android”,“val”:“0”,“vid”:“1”,“vr”:“var01”},{“eid”:“17”,“ex”:“trainMode_Android”,“val”:“1”,“vid”:“1”,“vr”:“mode_Android”},{“eid”:“44”,“ex”:“ihotelList_Android”,“val”:“1”,“vid”:“36”,“vr”:“var1”},{“eid”:“47”,“ex”:“ihotelDetail_Android”,“val”:“0”,“vid”:“38”,“vr”:“var1”}]

用explode小试牛刀一下：

select explode(split(regexp_replace(mvt,'\\[|\\]',''),'\\},\\{')) from ods_mvt_hourly where day=20160710 limit 10;

最后出来的结果如下：
{“eid”:“38”,“ex”:“affirm_time_Android”,“val”:“1”,“vid”:“31”,“vr”:“var1”
“eid”:“42”,“ex”:“new_comment_Android”,“val”:“1”,“vid”:“34”,“vr”:“var1”
“eid”:“40”,“ex”:“new_rpname_Android”,“val”:“1”,“vid”:“1”,“vr”:“var1”
“eid”:“19”,“ex”:“hotellistlpage_Android”,“val”:“1”,“vid”:“1”,“vr”:“var01”
“eid”:“29”,“ex”:“bookhotelpage_Android”,“val”:“0”,“vid”:“1”,“vr”:“var01”
“eid”:“17”,“ex”:“trainMode_Android”,“val”:“1”,“vid”:“1”,“vr”:“mode_Android”
“eid”:“44”,“ex”:“ihotelList_Android”,“val”:“1”,“vid”:“36”,“vr”:“var1”
“eid”:“47”,“ex”:“ihotelDetail_Android”,“val”:“0”,“vid”:“38”,“vr”:“var1”}
{“eid”:“38”,“ex”:“affirm_time_Android”,“val”:“1”,“vid”:“31”,“vr”:“var1”
“eid”:“42”,“ex”:“new_comment_Android”,“val”:“1”,“vid”:“34”,“vr”:“var1”

2.lateral view

hive wiki 上的解释如下：

Lateral View Syntax

lateralView: LATERAL VIEW udtf(expression) tableAlias AS columnAlias (’,’ columnAlias)*
fromClause: FROM baseTable (lateralView)*

Description

Lateral view is used in conjunction with user-defined table generating functions such as explode(). As mentioned in Built-in Table-Generating Functions, a UDTF generates zero or more output rows for each input row. A lateral view first applies the UDTF to each row of base table and then joins resulting output rows to the input rows to form a virtual table having the supplied table alias.

Example

Consider the following base table named pageAds. It has two columns: pageid (name of the page) and adid_list (an array of ads appearing on the page)
这里写图片描述

An example table with two rows:
这里写图片描述

and the user would like to count the total number of times an ad appears across all pages.
A lateral view with explode() can be used to convert adid_list into separate rows using the query:

SELECT pageid, adid
FROM pageAds LATERAL VIEW explode(adid_list) adTable AS adid;

The resulting output will be
这里写图片描述
Then in order to count the number of times a particular ad appears, count/group by can be used:

SELECT adid, count(1)
FROM pageAds LATERAL VIEW explode(adid_list) adTable AS adid
GROUP BY adid;

The resulting output will be
这里写图片描述
lateral view用于和split, explode等UDTF一起使用，它能够将一行数据拆成多行数据，在此基础上可以对拆分后的数据进行聚合。lateral view首先为原始表的每行调用UDTF，UDTF会把一行拆分成一或者多行，lateral view再把结果组合，产生一个支持别名表的虚拟表。

由此可见，lateral view与explode等udtf就是天生好搭档，explode将复杂结构一行拆成多行，然后再用lateral view做各种聚合。

3.实例

还是第一部分的例子，上面我们explode出来以后的数据，不是标准的json格式，我们通过lateral view与explode组合解析出标准的json格式数据:

SELECT ecrd, CASE WHEN instr(mvtstr,'{')=0
    AND instr(mvtstr,'}')=0 THEN concat('{',mvtstr,'}') WHEN instr(mvtstr,'{')=0
    AND instr(mvtstr,'}')>0 THEN concat('{',mvtstr) WHEN instr(mvtstr,'}')=0
    AND instr(mvtstr,'{')>0 THEN concat(mvtstr,'}') ELSE mvtstr END AS mvt
      FROM ods.ods_mvt_hourly LATERAL VIEW explode(split(regexp_replace(mvt,'\\[|\\]',''),'\\},\\{')) addTable AS mvtstr
        WHERE DAY='20160710' and ecrd is not null limit 10

查询出来的结果：
xxx
{“eid”:“38”,“ex”:“affirm_time_Android”,“val”:“1”,“vid”:“31”,“vr”:“var1”}
xxx
{“eid”:“42”,“ex”:“new_comment_Android”,“val”:“1”,“vid”:“34”,“vr”:“var1”}
xxx
{“eid”:“40”,“ex”:“new_rpname_Android”,“val”:“1”,“vid”:“1”,“vr”:“var1”}
xxx
{“eid”:“19”,“ex”:“hotellistlpage_Android”,“val”:“1”,“vid”:“1”,“vr”:“var01”}
xxx
{“eid”:“29”,“ex”:“bookhotelpage_Android”,“val”:“0”,“vid”:“1”,“vr”:“var01”
xxx
{“eid”:“17”,“ex”:“trainMode_Android”,“val”:“1”,“vid”:“1”,“vr”:“mode_Android”}
xxx
{“eid”:“44”,“ex”:“ihotelList_Android”,“val”:“1”,“vid”:“36”,“vr”:“var1”}
xxx
{“eid”:“47”,“ex”:“ihotelDetail_Android”,“val”:“1”,“vid”:“38”,“vr”:“var1”}
xxx
{“eid”:“38”,“ex”:“affirm_time_Android”,“val”:“1”,“vid”:“31”,“vr”:“var1”}
xxx
{“eid”:“42”,“ex”:“new_comment_Android”,“val”:“1”,“vid”:“34”,“vr”:“var1”}

4.Ending

Lateral View通常和UDTF一起出现，为了解决UDTF不允许在select字段的问题。
Multiple Lateral View可以实现类似笛卡尔乘积。
Outer关键字可以把不输出的UDTF的空结果，输出成NULL，防止丢失数据。

参考内容：

1.http://blog.youkuaiyun.com/oopsoom/article/details/26001307 lateral view的用法实例
2.https://my.oschina.net/leejun2005/blog/120463 复合函数的用法，比较详细
3.http://blog.youkuaiyun.com/zhaoli081223/article/details/46637517 udtf的介绍