Left Join Suggestion: A Comprehensive Approach to Avoiding Value Repeats
SQL Server’s LEFT JOIN operation is a powerful tool for combining data from two or more tables based on a common column. However, when dealing with multiple tables that share the same common column, it can be challenging to avoid repeating values from different tables. In this article, we’ll explore a proposed solution to tackle this issue using SQL Server’s ROW_NUMBER() function and cleverly designed join operations.
Problem Statement
Suppose you have multiple tables (#d, #t1, #t2) with a common column DataDate that you want to join together. However, you don’t want to repeat values from different tables when merging them. The resulting data should have unique values for each table while preserving the original data.
Demo Data Preparation
To illustrate this problem and proposed solution, let’s create demo data using SQL Server:
/* Prepare demo objects */
DROP TABLE IF EXISTS #d, #t1, #t2
CREATE TABLE #d (DataDate date)
CREATE TABLE #t1 (DataDate date, Value1 float, Value2 float)
CREATE TABLE #t2 (DataDate date, Value3 float, Value4 float)
/* Insert demo data */
INSERT INTO #d VALUES ('20181201'),('20181202'),('20181203')
INSERT INTO #t1 VALUES
('20181201', 3.14, 1.18),
('20181201', 3.135, 1.185),
('20181202', 3.15, 1.19),
('20181203', 3.16, 1.195)
INSERT INTO #t2 VALUES
('20181201', 4.14, 2.18),
('20181203', 4.15, 2.19),
('20181203', 4.1, 2.195)
/* Prepare third table */
CREATE TABLE #t3 (DataDate date, Value5 float, Value6 float)
INSERT INTO #t3 VALUES
('20181201', 3.14, 1.18),
('20181201', 3.135, 1.185),
('20181202', 3.16, 1.195)
Proposed Solution
To avoid repeating values from different tables when merging them, we can use a combination of ROW_NUMBER() and cleverly designed join operations.
SELECT
COALESCE(d.DataDate, t1.datadate, t2.datadate, t3.datadate) AS DataDate
, t1.Value1
, t1.Value2
, t2.Value3
, t2.Value4
, t3.Value5
, t3.Value6
FROM
(SELECT
*
, ROW_NUMBER() OVER (PARTITION BY DataDate ORDER BY (SELECT NULL)) AS rn
FROM #d) AS d
FULL JOIN
(SELECT
*
, ROW_NUMBER() OVER (PARTITION BY DataDate ORDER BY (SELECT NULL)) AS rn
FROM #t1) AS t1
ON (t1.DataDate = d.DataDate AND t1.rn = d.rn)
FULL JOIN
(SELECT
*
, ROW_NUMBER() OVER (PARTITION BY datadate ORDER BY (SELECT NULL)) AS rn
FROM #t2) AS t2
ON (t2.DataDate = d.DataDate AND t2.rn = d.rn)
OR (t2.DataDate = t1.DataDate AND t2.rn = t1.rn)
FULL JOIN
(SELECT
*
, ROW_NUMBER() OVER (PARTITION BY datadate ORDER BY (SELECT NULL)) AS rn
FROM #t3) AS t3
ON (t3.DataDate = d.DataDate AND t3.rn = d.rn)
OR (t3.DataDate = t1.DataDate AND t3.rn = t1.rn)
OR (t3.DataDate = t2.DataDate AND t3.rn = t2.rn)
ORDER BY DataDate;
Results
The proposed solution produces the following result:
| DataDate | Value1 | Value2 | Value3 | Value4 | Value5 | Value6 |
|---|---|---|---|---|---|---|
| 01/12/2018 00:00:00 | 3.14 | 1.18 | 4.14 | 2.18 | 3.14 | 1.18 |
| 01/12/2018 00:00:00 | 3.135 | 1.185 | null | null | 3.135 | 1.185 |
| 02/12/2018 00:00:00 | 3.15 | 1.19 | null | null | 3.16 | 1.195 |
| 03/12/2018 00:00:00 | 3.16 | 1.195 | 4.15 | 2.19 | null | null |
| 03/12/2018 00:00:00 | null | null | 4.1 | 2.195 | null | null |
As expected, the solution avoids repeating values from different tables when merging them.
Performance Improvement
To improve performance, we can add indexes on the common column DataDate:
/* Add to improve performance */
CREATE CLUSTERED INDEX CI_DataDate ON #d (DataDate);
CREATE CLUSTERED INDEX CI_DataDate ON #t1 (DataDate);
CREATE CLUSTERED INDEX CI_DataDate ON #t2 (DataDate);
CREATE CLUSTERED INDEX CI_DataDate ON #t3 (DataDate);
Conclusion
The proposed solution demonstrates how to avoid repeating values from different tables when merging them using SQL Server’s ROW_NUMBER() function and cleverly designed join operations. By adding indexes on the common column, we can improve performance. This approach is particularly useful when working with multiple tables that share a common column, making it easier to handle complex data merge scenarios.
Last modified on 2023-10-08