How Can I Efficiently Pivot Data in SQL Using Dynamic SQL Techniques?

Use dynamic SQL to efficiently implement SQL data pivot

This article discusses how to use dynamic SQL technology to convert tabular data into pivot table format, focusing on improving the efficiency and flexibility of data conversion.

Initial Query

The following query uses the CASE statement and GROUP BY to implement data pivoting:

SELECT bar, 
   MAX(CASE WHEN abc."row" = 1 THEN feh ELSE NULL END) AS "val1",
   MAX(CASE WHEN abc."row" = 2 THEN feh ELSE NULL END) AS "val2",
   MAX(CASE WHEN abc."row" = 3 THEN feh ELSE NULL END) AS "val3"
FROM
(
  SELECT bar, feh, row_number() OVER (partition by bar) as row
  FROM "Foo"
 ) abc
GROUP BY bar 

This method is effective for pivoting data, but is less efficient and less flexible when dealing with large data sets.

Improved solution using Crosstab function

The

function provided by the tablefunc module of crosstab()PostgreSQL can provide a more efficient and dynamic solution.

Install tablefunc module

Before using crosstab(), you need to ensure that the tablefunc module has been installed into the PostgreSQL database. You only need to execute the following command once per database:

CREATE EXTENSION tablefunc;

Crosstab implementation

The following crosstab queries can be used for pivoting:

SELECT * FROM crosstab(
  'SELECT bar, 1 AS cat, feh
   FROM   tbl_org
   ORDER  BY bar, feh')
 AS ct (bar text, val1 int, val2 int, val3 int);  -- 可根据需要增加列

Instructions:

• tbl_org is the input table.
The subquery in
• crosstab() selects bar, a dummy category cat, and feh. The cat column only serves as a placeholder and will be ignored.
The
• ORDER BY clause ensures that the values ​​are in proper order.

This query will return data in the desired pivot table format.

Dynamic Crosstab

In order to achieve more dynamic applications, we can use window functions to synthesize category columns:

SELECT * FROM crosstab(
   $$
   SELECT bar, val, feh
   FROM  (
      SELECT *, 'val' || row_number() OVER (PARTITION BY bar ORDER BY feh) AS val
      FROM tbl_org
      ) x
   ORDER BY 1, 2
   $$
 , $$VALUES ('val1'), ('val2'), ('val3')$$         -- 可根据需要增加列
) AS ct (bar text, val1 int, val2 int, val3 int);  -- 可根据需要增加列

This query dynamically creates category columns based on values ​​in the table.

Conclusion

All in all, the crosstab() function provides a more efficient and flexible solution for pivoting in SQL, simplifying queries and allowing flexible customization according to needs.

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