频繁模式挖掘函数通过分析多维数据，提取显著差异的属性组合并量化其影响，支持多种参数配置以优化挖掘结果。

get_patterns

get_patterns 是频繁集挖掘的算子，除了挖掘频繁项之外，get_patterns还会对挖掘到的频繁项做合并和去重。专指提取表格数据的模板（频繁集）。

语法

get_patterns($TABLE, $HEADER, $PARAM)

参数说明

参数	数据类型	是否必选	说明
$TABLE	row<array<T>, array<E>, ..., array<F>>	是	待挖掘频繁项的输入数据的表格，每一列是一个待挖掘的维度列。
$HEADER	array<varchar>	是	列名，和$TABLE对应，header名字数和table列的数量一致。
$PARAM	varchar	否	参见param参数说明。

param参数说明

参数名	参数解释	参数类型	是否必填	默认值	取值范围
minimum_support_fraction	输出的pattern在测试组的最低的支持度。比如某个pattern在测试组出现的频率是0.1，那么我们说这个pattern的支持度是0.1。这个参数可以通过控制pattern的敏感度控制pattern的数量。	double	否	0.05	(0, 1)

示例

查询分析：

关于"set session enable_remote_functions=true ;set session velox_support_row_constructor_enabled=true; "，目前功能处于公测阶段，需手动添加该 flag。后续版本将移除此要求，实现自动化支持。

(*)| set session enable_remote_functions=true ;set session velox_support_row_constructor_enabled=true; 
with t0 as (select  JSON_EXTRACT_SCALAR(entity, '$.platform') AS platform,  JSON_EXTRACT_SCALAR(entity, '$.region') AS region, cast(value as double) as value, if((value > 100), 'true', 'false') as anomaly_label from log), 
t1 as ( select array_agg(platform) as platform, array_agg(region) as region, array_agg(anomaly_label) as anomaly_label, array_agg(value) as value from t0),
t2 as (select row(platform, region) as table_row from t1),
t3 as (select get_patterns(table_row, ARRAY['platform', 'region']) as ret from t2)
select * from t3

输出结果：

[["platform=eBay","platform=edX","platform=Amazon","platform=Skillshare","platform=Shopify","platform=Khan Academy","platform=Coursera","platform=Udemy","platform=Alibaba","platform=Taobao","platform=Snapchat","platform=Amazon Prime","platform=YouTube","platform=Hulu","platform=Peloton","platform=Twitter","platform=Fitbit","platform=Nike Training","platform=LinkedIn","platform=Instagram","platform=Disney+","platform=Strava","platform=MyFitnessPal","platform=Facebook","platform=Netflix","platform=Console","platform=Samsung SmartThings","platform=Apple HomeKit","platform=Mobile","platform=PC","platform=Google Home","platform=VR"],[156960,149760,148320,148320,146880,145440,139680,136800,133920,133920,96480,95040,92160,90720,90720,89280,89280,87840,84960,83520,83520,82080,82080,77760,70560,46080,41760,41760,34560,33120,31680,30240],null,null]

返回结果说明

参数	类型	说明	对应示例
$RET.patterns	array<varchar>	表格模板，频繁集。每个varchar是一个用 AND 连接的表达式，类似`"\"platform\"='Netflix' AND \"region\"='Asia'"`，不同的varchar之间是并列的关系。	["platform=Coursera","platform=Udemy","platform=Khan Academy","platform=","platform=Shopify","platform=Skillshare","platform=edX","platform=eBay","platform=Console","platform=Square","platform=Taobao","platform=Google Meet","platform=E*TRADE","platform=Skype","platform=PayPal","platform=Robinhood","platform=Microsoft Teams","platform=Webex","platform=Zoom","platform=Mobile","platform=Alibaba","platform=VR","platform=Stripe","platform=PC","platform=Amazon","platform=Snapchat","platform=Instagram","platform=Twitter","platform=LinkedIn","platform=Strava","platform=Facebook","platform=Apple HomeKit","platform=Google Home","platform=Amazon Prime"]
$RET.test_supports	array<bigint>	每一个模板出现的频次。	`[79200,74880,74880,72000,67680,66240,64800,61920,61920,61920,60480,60480,59040,59040,57600,57600,57600,56160,54720,53280,51840,51840,51840,48960,46080,37440,33120,25920,25920,24480,21600,21600,21600,18720]`
$RET.labels	array<bigint>	预留的返回值位置，便于后续自动将数据归类。目前始终为 `null`。	`null`
$RET.error_msg	array<varchar>/null	报错信息。如果没有报错，则返回值为`null`。	`null`