esSql怎么实现row_number

在 Elasticsearch 中，可以使用 Elasticsearch SQL 查询语言来实现 row_number 功能。Elasticsearch SQL 是一种用于查询 Elasticsearch 数据的 SQL 方言。

要使用 Elasticsearch SQL 实现 row_number，可以使用 `RANK()` 函数结合 `ORDER BY` 子句来实现。以下是一个示例查询：

POST /_sql?format=json
{
  "query": "SELECT *, RANK() OVER (ORDER BY your_field) as row_number FROM your_index"
}

在上述查询中，你需要将 `your_index` 替换为你的索引名称，`your_field` 替换为你想要基于其进行排序的字段名称。

这个查询将返回按照指定字段升序排列的文档，并为每个文档分配一个 row_number 值。

注意：要使用 Elasticsearch SQL，你需要安装并配置 Elasticsearch SQL 插件。请参考 Elasticsearch 官方文档了解如何安装和配置 Elasticsearch SQL 插件。

相关问题

es怎么实现row_number

要在ES中实现类似于SQL中的`row_number()`函数，可以使用`rank_feature`查询和聚合功能。

首先，你需要在索引中定义一个`rank_feature`字段。假设你的索引名为`my_index`，你可以使用以下请求来添加一个新的字段：

PUT my_index/_mapping
{
  "properties": {
    "rank": {
      "type": "rank_feature"
    }
  }
}

接下来，你可以使用`rank_feature`字段来为文档计算排名。使用以下请求来更新文档并为每个文档分配排名：

POST my_index/_update_by_query
{
  "script": {
    "source": "ctx._source.rank = ctx._seq_no"
  }
}

现在，如果你想按照排名对文档进行排序，可以使用以下请求：

GET my_index/_search
{
  "query": {
    "match_all": {}
  },
  "sort": [
    {
      "rank": {
        "order": "asc"
      }
    }
  ]
}

这样，你就可以在ES中实现类似于SQL中的`row_number()`功能了。请注意，`row_number()`的实现方式可能因ES版本而异，上述示例适用于ES 7.x版本。在其他版本中，可能需要使用不同的方法来实现类似的功能。

select lot_hs.lot_id as lot_id,lot_type,lot_hs.mainpd_id, created_time,COMPLETE_TIME, value(bank.banktime,0) as banktime , round ( ( 1.00*(days(COMPLETE_TIME)-days(created_time)) + (hour(COMPLETE_TIME)-hour(created_time))*1.00/24 + (minute(COMPLETE_TIME)-minute(created_time))*1.00/24/60 + (second(COMPLETE_TIME)-second(created_time))1.00/24/60/60) - value(bank.banktime,0),3) as use_days, customer_id, coalesce(cc.cust_id_define,lot_hs.customer_id) as cust_id2, cc.cycletime_target as ct_target, date,layer, round(count() over(partition by coalesce(cc.cust_id_define,lot_hs.customer_id),cc.cycletime_target)*0.9,0) cnt, row_number() over(partition by coalesce(cc.cust_id_define,lot_hs.customer_id),cc.cycletime_target order by ( ( days(COMPLETE_TIME)-days(created_time) + (hour(COMPLETE_TIME)-hour(created_time))*1.00/24 + (minute(COMPLETE_TIME)-minute(created_time))*1.00/24/60 + (second(COMPLETE_TIME)-second(created_time))*1.00/24/60/60) - value(bank.banktime,0))/layer) id From (select date(a.claim_time) as date, a.lot_id, a.lot_type,a.mainpd_id,a.prodspec_id,a.custprod_id, case when(date(b.created_time) <= '2009-01-05') then b.created_time + 21 days else b.created_time end as created_time, CASE WHEN A.CUST_id in ('MCA','NPA','SET') THEN a.COMPLETE_TIME ELSE a.COMPLETE_TIME END COMPLETE_TIME, a.cust_id as customer_id, a.ope_category, c.layer From f3rpt.F3_TB_DAILY_FABOUT a, f3rpt.fvlot b, (select mainpd_id, sum(masks)layer from f3rpt.ASMCRPT_VW_MAINPD_MASKS_ALL group by mainpd_id) as c, (select * from (select lot_id, max(claim_time)claim_time, count(case when(ope_category='Ship')then lot_id else null end) as LS, count(case when(ope_category='Unship') then lot_id else null end) as LUS from f3rpt.F3_TB_DAILY_FABOUT where substr(lot_id,1,2) not in('CA','CW','ES','E0','EM') and lot_type = 'Production' AND LOT_ID NOT LIKE 'H%' and substr(lot_id,7,4)='.00F' and ope_category in ('Ship','Unship') and year(claim_time) = year(current date - 1 days) and month(claim_time) = month(current date - 1 days) group by lot_id) as a where LS - LUS > 0 ) as lot Where a.lot_id = b.lot_id and b.mainpd_id = c.mainpd_id and a.lot_id = lot.LOT_ID and a.claim_time = lot.claim_time and a.ope_category = 'Ship' and a.cust_id in ('SM','BOE','GSC','NPA','GTA') ) as lot_hs left outer join (select lot_id,max(bankin_time) banktime from f3rpt.asmc_dpm where bankin_time>0 group by lot_id) bank on (lot_hs.lot_id = bank.lot_id) left join f3cim.f3cim_cfg_cust_rule cc on case when lot_hs.customer_id='WXM' THEN 'WII'||SUBSTR(lot_hs.mainpd_id,6,1) else lot_hs.customer_id end = cc.cust_id and locate(cc.mainpd_id,lot_hs.mainpd_id)>0 and locate(cc.prodspec_id,lot_hs.prodspec_id)>0 and locate(cc.custprod_id_45,substr(lot_hs.custprod_id,3,3))>0 where lot_hs.ope_category = 'Ship' ；以上sql如何优化

这是一个比较复杂的 SQL 语句，可以从以下几个方面考虑进行优化：

1.使用 JOIN 替代子查询

可以使用 JOIN 语句替代子查询，可以提高查询效率。例如，将以下子查询：

(select mainpd_id, sum(masks)layer from f3rpt.ASMCRPT_VW_MAINPD_MASKS_ALL group by mainpd_id) as c

改写为：

FROM f3rpt.ASMCRPT_VW_MAINPD_MASKS_ALL c GROUP BY mainpd_id

2.使用索引

对于频繁查询的字段，可以添加索引以提高查询效率。例如，可以为以下字段添加索引：

b.mainpd_id
a.lot_id
a.cust_id
lot_hs.customer_id
cc.cust_id_define
cc.mainpd_id
cc.prodspec_id
cc.custprod_id_45

3.使用 EXPLAIN 分析查询计划

使用 EXPLAIN 命令可以分析查询计划，了解查询语句的执行情况，从而优化查询语句以提高查询效率。

4.使用 UNION 替代多个 OR 条件

对于多个 OR 条件的查询语句，可以使用 UNION 来代替，可以提高查询效率。例如：

AND lot_type = 'Production' AND LOT_ID NOT LIKE 'H%' and substr(lot_id,7,4)='.00F' and ope_category in ('Ship','Unship')

可以改写为：

AND lot_type = 'Production' AND LOT_ID NOT LIKE 'H%' and substr(lot_id,7,4)='.00F' and ope_category = 'Ship'
UNION
AND lot_type = 'Production' AND LOT_ID NOT LIKE 'H%' and substr(lot_id,7,4)='.00F' and ope_category = 'Unship'