Some common MySQL methods for merging query results

MySQL is one of the most popular relational database management systems currently. For database operators, querying data, calculating and processing it is an essential skill. But sometimes, we need to combine some results to make it easier to analyze and process the results. In MySQL, there are multiple ways to achieve this.

Below, we will introduce some commonly used MySQL methods to merge query results.

1. UNION

UNION is one of the most common ways to merge query results. It can combine the results of multiple SELECT statements and remove duplicate rows from the final result.

For example, we have two tables A and B, which have the same columns:

SELECT column1, column2 FROM A
UNION
SELECT column1, column2 FROM B;

This query will merge the data in tables A and B and remove duplicate rows. It should be noted that UNION can only combine the results of two SELECT statements. If you need to combine the results of three or more SELECT statements, you need to use the UNION operator multiple times.

2. UNION ALL

UNION ALL is very similar to UNION, but does not remove duplicate rows. When using UNION ALL, duplicate rows will be retained.

For example, there are two tables A and B, which have the same columns:

SELECT column1, column2 FROM A
UNION ALL
SELECT column1, column2 FROM B;

This query will merge the data in tables A and B and retain duplicate rows.

Because UNION ALL does not need to remove duplicate rows, it is faster and more efficient than UNION. However, if the data is very large, query performance may be affected.

3. INNER JOIN

INNER JOIN can combine data from two or more tables and match the data in their common columns. This operation will only return results when there is a match between the data in the two tables.

For example, there are two tables A and B, they have the same column column1:

SELECT A.column1, A.column2, B.column3
FROM A
INNER JOIN B
ON A.column1 = B.column1;

This query will return matching data rows in tables A and B. In this example, only rows with matches are returned.

4. LEFT JOIN

LEFT JOIN is very similar to INNER JOIN, it can also combine data from two or more tables and combine their common columns matches the data in . However, it returns not only results for matches, but also results for which there are no matches in the left table.

For example, there are two tables A and B, they have the same column column1:

SELECT A.column1, A.column2, B.column3
FROM A
LEFT JOIN B
ON A.column1 = B.column1;

This query will return all the data rows in table A, and the matching data rows in table B, If there is no data in table B that matches table A, a NULL value will be returned.

5. RIGHT JOIN

RIGHT JOIN is the opposite of LEFT JOIN, it returns results with no matches in the right table.

For example, there are two tables A and B, they have the same column column1:

SELECT A.column1, A.column2, B.column3
FROM A
RIGHT JOIN B
ON A.column1 = B.column1;

This query will return all the data rows in table B, and the matching data rows of table A, If there is no data in table A that matches table B, a NULL value will be returned.

6. FULL OUTER JOIN

FULL OUTER JOIN can merge all data rows from two tables together, even if there is not a match in both tables .

MySQL does not support the FULL OUTER JOIN statement. However, UNION ALL can be used in conjunction with LEFT JOIN and RIGHT JOIN to achieve similar effects.

For example, there are two tables A and B, they have the same column column1:

SELECT A.column1, A.column2, B.column3
FROM A
LEFT JOIN B
ON A.column1 = B.column1
UNION ALL
SELECT A.column1, A.column2, B.column3
FROM A
RIGHT JOIN B
ON A.column1 = B.column1
WHERE A.column1 IS NULL;

This query will return matches with all data rows in table A and table B and no matches rows of data.

Conclusion

The above are common methods of merging query results in MySQL. Which method you choose depends on the results you need and the performance of your query.

When executing queries, always pay attention to query efficiency. In most cases, UNION operations take a long time. If you are querying with large data sets, you should avoid using the UNION command and instead use other available methods to optimize query performance.

Of course, for a specific business scenario, we also need to choose which method to use based on actual business needs.

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