WITH sequences AS
(SELECT [0, 1, 1, 2, 3, 5] AS some_numbers
UNION ALL SELECT [2, 4, 8, 16, 32] AS some_numbers
UNION ALL SELECT [5, 10] AS some_numbers)
SELECT some_numbers,
some_numbers[OFFSET(1)] AS offset_1,
some_numbers[ORDINAL(1)] AS ordinal_1
FROM sequences;
| some_numbers | offset_1 | ordinal_1 |
|---|
| [0, 1, 1, 2, 3, 5] | 1 | 0 |
| [2, 4, 8, 16, 32] | 4 | 2 |
| [5, 10] | 10 | 5 |
WITH sequences AS
(SELECT [0, 1, 1, 2, 3, 5] AS some_numbers
UNION ALL SELECT [2, 4, 8, 16, 32] AS some_numbers
UNION ALL SELECT [5, 10] AS some_numbers)
SELECT some_numbers,
ARRAY_LENGTH(some_numbers) AS len
FROM sequences;
| some_numbers | len |
|---|
| [0, 1, 1, 2, 3, 5] | 6 |
| [2, 4, 8, 16, 32] | 5 |
| [5, 10] | 2 |
SELECT *
FROM UNNEST(['foo', 'bar', 'baz', 'qux', 'corge', 'garply', 'waldo', 'fred'])
AS element
WITH OFFSET AS offset
ORDER BY offset;
| element | offset |
|---|
| foo | 0 |
| bar | 1 |
| baz | 2 |
| qux | 3 |
| corge | 4 |
| garply | 5 |
| waldo | 6 |
| fred | 7 |
访问数组元素WITH sequences AS (SELECT [0, 1, 1, 2, 3, 5] AS some_numbers UNION ALL SELECT [2, 4, 8, 16, 32] AS some_numbers UNION ALL SELECT [5, 10] AS some_numbers)SELECT some_numbers, some_numbers[OFFSET(1)] AS offset_1, some_numbers[OR
向JS对象数组添加类似SQL的查询功能。
包含该库将向对象数组添加where（），select（）和orderBy（）功能。
where（）-接受SQL查询字符串作为参数。 模拟SQL WHERE子句。 处理所有表达式，包括BETWEEN和IN子句。 标量和聚合函数尚不支持。
select（）-模拟SQL SELECT。
orderBy（）-模拟SQL ORDER BY。
joinOn（）-模拟SQL内部联接。 （实验性的）将连接字段（或连接表达式）作为第一个参数，将要连接的数组作为下一个参数。
为了进行测试，在项目中包含
＃＃＃例子
var employee = [ {
empid : 100 ,
ename : "Chuck"
} , {
empid : 101 ,
ename : "Rick"
} , {
查询嵌套数组
如果一个表包含 STRUCT 的 ARRAY，则可展平 ARRAY 以查询 STRUCT 的字段。您也可以展平 STRUCT 值的 ARRAY 类型字段。
查询 ARRAY 中的 STRUCT 元素
以下示例将 UNNEST 与 CROSS JOIN 结合使用，以展平 STRUCT 的 ARRAY。
WITH races AS (
SELECT "800M" AS race,
[STRUCT("Rudisha" as name, [23.4, 26.3, 26.4, 26.1] a
展平数组
SELECT *
FROM UNNEST(['foo', 'bar', 'baz', 'qux', 'corge', 'garply', 'waldo', 'fred'])
AS element
WITH OFFSET AS offset
ORDER BY offset;
语法: map (key1, value1, key2, value2, …)
说明：根据输入的key和value对构建map类型
hive> Create table iteblog as select map(‘100’,‘tom’,‘200’,‘mary’) as t from iteblog;
hive> describe iteblog;
t map<string ,string>
hive> select
<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd" >
<mapper namespace="com.aqin.dao.mapper1.TrmmIndexMapper">
<resultMap id="BaseResu.
select array_length(string_to_array(org.codepath,'.'), 1)-1 as level
,string_to_array(org.codepath,'.')
,org.codepath
from orgs...
HiveSQL如何展开Array/Array格式字段？使用LATERAL VIEW explode() 方法…
目录1、解析Array格式列展开函数**array行展开→explode****array列展开统计各取值出现次数**2、解析Array格式参考网页：
1、解析Array格式
列展开函数
EXPLODE(col)：将hive一列中复杂的array或者map结构拆分成多行。
LATERAL VIEW：用法：LATERAL VIEW udtf(expression) tableAlias AS col
set edate=2019-07-21
SET company=***;
SET recomrecords=ods.ods_${hiveconf:company_RecomRecords;
SET empl...
原文链接（很nice的一篇文章）：https://blog.csdn.net/wang_wbq/article/details/79678168
数组\列表array、字典map这两种数据类型的索引
首先我们还是先构造数据结构与DataFrame：
scala> case class A(a: String, b: Int)
defined class A
获取字符串数组长度
if exists (select 1 from sysobjects where id = object_id('Get_StrArrayLength' ))
drop Function Get_StrArrayLength...
