代码之家 › 专栏 › 技术社区 › Laramie

T-SQL:一个更好的滑动分布函数/查询

tile statistics sql-server-2008 tsql

Laramie · 技术社区 · 15 年前

我需要一个类似于ntile()提供的T-SQL排序方法,只是每个tile的成员都在一个滑动分布中,这样排名较高的tile的成员就更少了。

例如

CREATE TABLE #Rank_Table(
id int identity(1,1) not null,
hits bigint not null default 0,
PERCENTILE smallint null
)
--Slant the distribution of the data
INSERT INTO #Rank_Table (hits)
select CASE 
  when DATA > 9500 THEN DATA*30
  WHEN data > 8000  THEN DATA*5 
  WHEN data < 7000  THEN DATA/3 +1
  ELSE DATA
 END
FROM
 (select top 10000 (ABS(CHECKSUM(NewId())) % 99 +1) * (ABS(CHECKSUM(NewId())) % 99 +1 ) DATA
 from master..spt_values t1
  cross JOIN master..spt_values t2) exponential

Declare @hitsPerGroup as bigint
Declare @numGroups as smallint
set @numGroups=100

select @hitsPerGroup=SUM(hits)/(@numGroups -1) FROM #Rank_Table 

select @hitsPerGroup HITS_PER_GROUP

--This is an even distribution
SELECT  id,HITS, NTILE(@numGroups) Over (Order By HITS DESC) PERCENTILE 
FROM #Rank_Table 
GROUP by id, HITS

--This is my best attempt, but it skips groups because of the erratic distribution
select 
    T1.ID, 
    T1.hits, 
    T.RunningTotal/@hitsPerGroup + 1 TILE,
    T.RunningTotal
FROM    #Rank_Table T1
        CROSS APPLY ( Select SUM(hits) RunningTotal FROM #Rank_Table where hits <= T1.hits) T
order by T1.hits 

DROP TABLE #Rank_Table

在rank_表中,ntile(@numgroups)创建了@numgroups组的均匀分布。我需要的是@numgroups组,其中tile 1的成员最少,tile 2将有一个或多个tile 1,tile 3将有1个或多个tile 2…瓷砖100将是最多的。

我正在使用SQL Server 2008。实际上,这将针对一个可能有数百万行的永久表运行,以便定期用百分位数从1到100更新百分位数列。

我最好的尝试以上将跳过百分位数和表现不佳。一定有更好的办法。

2 回复 | 直到 14 年前

gbn 14 年前

A better NTILE implementation ?牛传染性胃肠炎病毒

Laramie 14 年前

为了创建更线性的分布,我在数据表中添加了一个计算列,点击 HITS_SQRT AS (CONVERT([int],sqrt(HITS*4),(0))) PERSISTED .

使用此列,您可以计算“按百分比点击”的目标数量。

select @hitsPerGroup=SUM(HITS_SQRT)/(@numGroups -1)-@numGroups, @dataPoints=COUNT(*) FROM #Rank_Table

然后,该脚本创建一个临时表,该表的行_number()按点击数排序,并按降序迭代这些行,将其百分位数从100更新为1。一个连续的总命中数被保存,当 @hitsPerGroup 通过后,百分比从100降低到99、99降低到98等。

然后,源数据表用它的百分比更新。有一个临时工作表的索引来加速更新。

完整脚本使用 #Rank_Table 作为源数据表。

--Create Test Data
CREATE TABLE #Rank_Table(
id int identity(1,1) not null,
hits bigint not null default 0,
PERCENTILE smallint NULL,
HITS_SQRT  AS (CONVERT([int],sqrt(HITS*4),(0))) PERSISTED
)
--Slant the distribution of the data
INSERT INTO #Rank_Table (hits)
select CASE 
  when DATA > 9500 THEN DATA*30
  WHEN data > 8000  THEN DATA*5 
  WHEN data < 7000  THEN DATA/3 +1
  ELSE DATA
 END
FROM
 (select top 10000 (ABS(CHECKSUM(NewId())) % 99 +1) * (ABS(CHECKSUM(NewId())) % 99 +1 ) DATA
 from master..spt_values t1
  cross JOIN master..spt_values t2) exponential

--Create temp work table and variables to calculate percentiles
    Declare @hitsPerGroup as int
    Declare @numGroups as int
    Declare @dataPoints as int
    set @numGroups=100

    select @hitsPerGroup=SUM(HITS_SQRT)/(@numGroups -1)-@numGroups, @dataPoints=COUNT(*) FROM #Rank_Table 

    --show the number of hits that each group should have
    select @hitsPerGroup HITS_PER_GROUP

    --Use temp table for the calculation
    CREATE TABLE #tbl (
        row int,
        hits int,
        ID bigint,
        PERCENTILE smallint null
    )
    --add index to row
    CREATE CLUSTERED INDEX idxRow ON #tbl(row) 

    insert INTO #tbl
    select ROW_NUMBER() over (ORDER BY HITS), hits_SQRT, ID, null from #Rank_Table

    --Update each row with a running total.
    --lower the percentile by one when we cross a threshold for the maximum number of hits per group (@hitsPerGroup)
    DECLARE @row as int
    DEClare @runningTotal as int
    declare @percentile int
    set @row = 0
    set @runningTotal = 0
    set @percentile = @numGroups

    while @row <= @dataPoints
    BEGIN
        select @runningTotal=@runningTotal + hits from #tbl where row=@row

        if @runningTotal >= @hitsPerGroup
        BEGIN

            update #tbl
            set PERCENTILE=@percentile
            WHERE PERCENTILE is null and row <@row

            set @percentile = @percentile - 1

            set @runningTotal = 0
        END

        --change rows
        set @row = @row + 1
    END

    --get remaining
    update #tbl
    set PERCENTILE=@percentile
    WHERE PERCENTILE is null

    --update source data
    UPDATE m SET PERCENTILE = t.PERCENTILE
    FROM #tbl t
    inner join #Rank_Table m on t.ID=m.ID


--Show the results
    SELECT PERCENTILE, COUNT(id) NUMBER_RECORDS, SUM(HITS) HITS_IN_PERCENTILE 
    FROM #Rank_Table 
    GROUP BY PERCENTILE
    ORDER BY PERCENTILE 

--cleanup
    DROP TABLE #Rank_Table
    DROP TABLE #tbl

它的性能不是一流的,但它达到了平滑滑动分布的目的。