mysql affected rows vs changed rows

For REPLACE, deleted rows are also counted. For UPDATE, affected rows is by default the number of rows that were actually changed. You can run it in phpMyAdmin or run a mysql_affected_rows after it, you’ll see it affects only the rows that need to be updated. Manually fixing the issue with the row (or deleting it) and issuing FLUSH PRIVILEGES will fix it. As MySQL doesn’t have inherent support for updating more than one rows or records with a single update query as it does for insert query, in a situation which needs us to perform updating to tens of thousands or even millions of records, one update query for each row seems to be too much.. Reducing the number of SQL database queries is the top tip for optimizing SQL applications. Also the speed it pretty good, I still need to test it on a huge table, but for my example a products table isn’t necessarily huge (on average I’d say 1000-10000 rows), so it should be quite efficient in the end. The good news is that in MySQL 5.6 you can have the database handle both columns. So even though we didn’t make a change to the updated_at column in our UPDATE statement, MySQL knew to update it. For these user accounts what works and what doesn't is not defined, but it's safe to assume that nothing will work. Scan count 1, logical reads 3982, physical reads 0, read-ahead reads 7, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. If the CLIENT_FOUND_ROWS flag to mysql_real_connect() is specified when connecting to mysqld, affected rows is instead the number of rows matched by the WHERE clause. For instance, you can request the names of customers who […] I am using a while loop to attempt to extract data from two columns in all of the rows of the table. If no rows match the given criteria then it returns false instead. Then check to see how many rows were updated, because rows cannot be updated by two processes at once, if you updated the row, you got the lock. Below is the description of the table geek. Return Value: It returns the number of rows present in a result set. And now rerun the SELECT, and we observe the following message returned with the results: (232056 rows affected) Table 'TestCompression'. Consider there is a table named geek in a MySQL database named Geeks. The query is as follows − mysql> select StudentId from SecondTableRows; Output To simplify things on the client side it's better to wrap it in a stored procedure. Do this by using the SET PASSWORD statement without the FOR clause: The query is as follows − mysql> call Sp_AllRowsOfATable(); Query OK, 1 row affected (0.61 sec) After calling the stored procedure, let us check what happened with the second table. Assuming you're using PHP, you'd use mysql_affected_rows(), if the return from that was 1, you successfully locked it. 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