Again, when I use table2 instead of the table2view, it only updates the first row properly and sets all other rows' table1.table1column1 = 0.

数学

我正在尝试将 table1.table1column1 = 设置为 table2column1、table2column2 和 table2column3 的百分位数之和 通过 id.

I'm trying to set table1.table1column1 = to the sum of the percentiles of table2column1, table2column2, and table2column3 by id.

我通过(计算 table2columnX 的不同值 <= 到当前 table2columnX )/(不同 table2columnX 的总计数s).

I do a percentile by (counting the distinct values of a table2columnX <= to the current table2columnX ) / (the total count of distinct table2columnXs).

我使用 DISTINCT 来去除过多的重复.

I use DISTINCT to get rid of the excessive duplicates.

查看

这是视图的 SELECT.这有帮助吗?

Here's the SELECT for the view. Does this help?

CREATE VIEW myTable.table2view AS SELECT
    table2.table2column1 AS table2column1,
    table2.table2column2 AS table2column2,
    table2.table2column2 AS table2column3,
FROM table2
GROUP BY table2.id;

视图的 SELECT 中的 GROUP BY 是否有什么特别之处使这项工作(我没有看到)?

Is there something special about the GROUP BY in the view's SELECT that makes this work (that I'm not seeing)?

推荐答案

我可能会说查询很慢，因为它在触发器触发时重复访问表.

I would probably say that the query is slow because it is repeatedly accessing the table when the trigger fires.

我不是 SQL 专家，但我曾尝试使用临时表组合查询.您可以查看它是否有助于加快查询速度.我在下面的代码示例中使用了不同但发音相似的列名称.

I am no SQL expert but I have tried to put together a query using temporary tables. You can see if it helps speed up the query. I have used different but similar sounding column names in my code sample below.

在我之前的代码中有一个计算错误.现已更新.

EDIT : There was a calculation error in my earlier code. Updated now.

SELECT COUNT(id) INTO @no_of_attempts from tb2;

-- DROP TABLE IF EXISTS S1Percentiles;
-- DROP TABLE IF EXISTS S2Percentiles;
-- DROP TABLE IF EXISTS S3Percentiles;

CREATE TEMPORARY TABLE S1Percentiles (
    s1 FLOAT NOT NULL,
    percentile FLOAT NOT NULL DEFAULT 0.00
);

CREATE TEMPORARY TABLE S2Percentiles (
    s2 FLOAT NOT NULL,
    percentile FLOAT NOT NULL DEFAULT 0.00
);

CREATE TEMPORARY TABLE S3Percentiles (
    s3 FLOAT NOT NULL,
    percentile FLOAT NOT NULL DEFAULT 0.00
);



INSERT INTO S1Percentiles (s1, percentile)
    SELECT A.s1, ((COUNT(B.s1)/@no_of_attempts)*100)
    FROM (SELECT DISTINCT s1 from tb2) A
    INNER JOIN tb2 B
    ON B.s1 <= A.s1
    GROUP BY A.s1;

INSERT INTO S2Percentiles (s2, percentile)
    SELECT A.s2, ((COUNT(B.s2)/@no_of_attempts)*100)
    FROM (SELECT DISTINCT s2 from tb2) A
    INNER JOIN tb2 B
    ON B.s2 <= A.s2
    GROUP BY A.s2;

INSERT INTO S3Percentiles (s3, percentile)
    SELECT A.s3, ((COUNT(B.s3)/@no_of_attempts)*100)
    FROM (SELECT DISTINCT s3 from tb2) A
    INNER JOIN tb2 B
    ON B.s3 <= A.s3
    GROUP BY A.s3;

-- select * from S1Percentiles;
-- select * from S2Percentiles;
-- select * from S3Percentiles;

UPDATE tb1 A
    INNER JOIN
    (
    SELECT B.tb1_id AS id, (C.percentile + D.percentile + E.percentile) AS sum FROM tb2 B
        INNER JOIN S1Percentiles C
        ON B.s1 = C.s1
        INNER JOIN S2Percentiles D
        ON B.s2 = D.s2
        INNER JOIN S3Percentiles E
        ON B.s3 = E.s3
    ) F
    ON A.id = F.id

    SET A.sum = F.sum;

-- SELECT * FROM tb1;

DROP TABLE S1Percentiles;
DROP TABLE S2Percentiles;
DROP TABLE S3Percentiles;

这样做是为了记录每个分数组的百分位数，然后最后只用必要的数据更新 tb1 列，而不是重新计算每个学生行的百分位数.

What this does is that it records the percentile for each score group and then finally just updates the tb1 column with the requisite data instead of recalculating the percentile for each student row.

您还应该索引 s1、s2 和 s3 列以优化对这些列的查询.

You should also index columns s1, s2 and s3 for optimizing the queries on these columns.

注意:请根据您的数据库架构更新列名称.另请注意，每个百分位数计算都乘以 100，因为我相信百分位数通常是这样计算的.

Note: Please update the column names according to your db schema. Also note that each percentile calculation has been multiplied by 100 as I believe that percentile is usually calculated that way.

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