Why Does "explain" Show a Different Row Count Than "count()"?

Discrepancy between "explain" and "count()": Unveiling the True Number of Rows

In the realm of SQL queries, the discrepancy between the rows reported by the "explain" statement and the actual count() value can often leave developers puzzled. To unravel this mystery, let's delve into the subtle nuances of the "explain" function.

The "explain" statement provides valuable insights into the execution plan of a query. It displays the number of rows that the optimizer estimates the query will need to process. However, this estimate can sometimes deviate significantly from the true count, as exemplified in the provided code:

mysql> select count(*) from table where relation_title='xxxxxxxxx';
+----------+
| count(*) |
+----------+
|  1291958 |
+----------+

mysql> explain select * from table where relation_title='xxxxxxxxx';
+----+-------------+---------+-
| id | select_type | rows    |
+----+-------------+---------+-
|  1 | SIMPLE      | 1274785 | 
+----+-------------+---------+-

This discrepancy stems from the predictive nature of the optimizer's algorithm. "explain" provides an approximate guess based on stored statistical information about the table. While this estimation is typically accurate, it can err for various reasons, such as outdated statistics or complex query patterns.

In this case, the estimate provided by "explain" falls short of the true count. This is because the optimizer underestimated the number of matching rows for the predicate "relation_title='xxxxxxxxx'." Consequently, the estimate misses out on some rows that satisfy the condition.

To obtain a precise count, relying solely on "explain" can be misleading. Instead, the "count()" function provides an accurate and reliable count of the rows that match a specified criteria. By utilizing "count()", developers can be certain of the exact number of rows selected by their queries.

It's important to note that "explain" remains a powerful tool for optimizing query performance. By understanding its limitations and complementing it with "count()" when necessary, developers can effectively troubleshoot and improve the efficiency of their SQL queries.

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