小编典典

为什么CTE计算在查询计划中重复?如何在不重复代码的情况下对其进行优化?

sql

在此查询的查询计划中,grp_set的计算重复了4次(不同的排序每次花费23%,因此它花费23 * 4 =所有资源的92%):

with
     grp_set as (select distinct old_num,old_tbl,old_db,old_val_num from err_calc)
    ,grp as (select id = row_number() over (order by old_num),* from grp_set)

    ,leaf as (select grp.id ,c.* ,sort = convert(varchar(max),old_col) + " - " + severity + " - " + err
        from grp
        join err_calc c on
                            c.old_num   = grp.old_num
                        and c.old_tbl       = grp.old_tbl
                        and c.old_db        = grp.old_db
                        and c.old_val_num   = grp.old_val_num
    )

    select old_num,old_tbl,old_db,old_val_num,conc.*
        from (select sep=",") sep
        cross join grp
        cross apply (select
             old_col    = stuff((select sep + old_col   from leaf where leaf.id = grp.id order by leaf.sort FOR XML PATH("")),1,len(sep),"")
            ,old_val    = stuff((select sep + old_val   from leaf where leaf.id = grp.id order by leaf.sort FOR XML PATH("")),1,len(sep),"")
            ,severity   = stuff((select sep + severity  from leaf where leaf.id = grp.id order by leaf.sort FOR XML PATH("")),1,len(sep),"")
            ,err        = stuff((select sep + err       from leaf where leaf.id = grp.id order by leaf.sort FOR XML PATH("")),1,len(sep),"")
        ) conc

表err_calc包含约35万条记录,并且按old_db,old_tbl,new_tbl,severity,err,old_col,new_col,old_val_num,old_val,old_num,new_num只有一个索引。

该查询的目的是由于SQL中缺少串联聚合,因此每组串联4个字符串字段。

等效和期望的查询是否存在串联聚合或使用CLR实现,以及是否可以将order by应用于聚合源,以及是否可以通过by引用所有分组字段grouping.*

select grouping.*
    ,severity   =conc(sep+severity)
    ,err        =conc(sep+err)
    ,old_col    =conc(sep+old_col)
    ,old_val    =conc(sep+old_val)
    from err_calc
    cross join (select sep=',') sep
    group by old_num,old_tbl,old_db,old_val_num
    order by old_col,severity,err

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2021-05-30

共1个答案

小编典典

因为它像子查询一样被使用,并且多次使用。cf.
在同一查询中多次调用CTE

您应该JOIN使用CTE而不是使用A重写查询CROSS APPLY,并将字符串串联逻辑放在SELECT查询的一部分中,然后CTE将被调用一次。

2021-05-30