Interpreting SQL Query Execution Plans for Performance Analysis.
Jul 15, 2025 am 02:51 AMTo understand SQL execution plan, first use the database's own commands (such as MySQL's EXPLAIN, PostgreSQL's EXPLAIN ANALYZE, and SQL Server graphical interface) to obtain the execution plan; secondly, focus on checking the scan type, whether temporary sorting or temporary tables occur, estimated row count and cost values; then focus on common performance bottlenecks such as full table scanning, low nesting loop efficiency, temporary sorting, etc.; finally, adjusting based on actual conditions, including checking indexes, avoiding SELECT *, optimizing JOIN and sorting operations, and regularly updating statistical information.
Understanding SQL query execution plans is a key step in optimizing database performance. Many people’s first reaction when seeing an execution plan is that they “can’t understand it”. In fact, as long as they master a few core indicators and analysis methods, they can quickly locate the problem.

Basic ways to view execution plans
The commands for viewing execution plans in different database systems are slightly different. For example, use EXPLAIN
in MySQL, EXPLAIN ANALYZE
in PostgreSQL, and use graphic interface to directly display the execution plan in SQL Server.

Generally speaking, the execution plan will show information such as the type of operation, access method, the amount of data involved, and the estimated cost of each step. The key point is:
- Which type of scan was used (full table scan or index scan)
- Whether a temporary sort or temporary table appears
- Is the estimated number of rows reasonable?
- Is there a step toward a cost value (cost) significantly higher?
This information can help you determine whether there are inefficient operations in the current query.

Pay attention to common performance bottlenecks
Several of the most noteworthy performance bottlenecks in the execution plan include:
- Full table scan : If a table does not go through the index but performs a full table scan, it may mean that the appropriate index is missing or the query conditions are unclear.
- Temporary sort/temporary table : This usually occurs when there is
ORDER BY
,GROUP BY
or a subquery. If the data volume is large, such operations will significantly affect performance. - Inefficient nested loops : When joining two large tables, the cost of nested loops may be very high. You can consider rewriting SQL or adjusting the connection method.
- High-cost node : The "cost" field in the execution plan can help you identify which step is the most resource-consuming, and priority optimization of this part is often the most obvious effect.
For example, if you find that a query scans a table of millions of data in a full table, but actually only requires a few thousand records, it is likely that the index is missing or the index is not used correctly.
How to optimize based on actual conditions
After getting the execution plan, the next step is to tune according to the observed problems. Here are a few practical suggestions:
- Check if fields in WHERE conditions have appropriate index support
- Try to avoid SELECT *, select only the required fields, and reduce the amount of data transmission
- For JOIN operation, confirm whether the connection field has been indexed
- If file sorting occurs, you can try to avoid it by adding overwrite indexes or adjusting ORDER BY
- Use forced indexes (such as FORCE INDEX) appropriately to verify the index effect
It should be noted that sometimes the "optimal path" given by the execution plan is not necessarily really optimal, especially when the statistical information is inaccurate. Therefore, it is also important to update statistics regularly.
Basically that's it. Understanding the implementation plan is not something that can be achieved overnight, but as long as you look at a few more real cases, you can quickly establish basic judgment skills.
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