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. Manually fixing the issue with the row (or deleting it) and issuing FLUSH PRIVILEGES will fix it. 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. 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. Do this by using the SET PASSWORD statement without the FOR clause: Return Value: It returns the number of rows present in a result set. mysql> SET PASSWORD FOR tom@localhost = PASSWORD('new_password'); Query OK, 0 rows affected (0.00 sec) If you are logged in as a non-root user and your user does not have the UPDATE privilege for the mysql database, you can change only your own password. To simplify things on the client side it's better to wrap it in a stored procedure. The query is as follows − mysql> select StudentId from SecondTableRows; Output 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. Below is the description of the table geek. The good news is that in MySQL 5.6 you can have the database handle both columns. If no rows match the given criteria then it returns false instead. For UPDATE, affected rows is by default the number of rows that were actually changed. 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. And now rerun the SELECT, and we observe the following message returned with the results: (232056 rows affected) Table 'TestCompression'. Call the above stored procedure to loop through all rows of the first table. So even though we didn’t make a change to the updated_at column in our UPDATE statement, MySQL knew to update it. Consider there is a table named geek in a MySQL database named Geeks. For REPLACE, deleted rows are also counted. 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. It is a mandatory parameter and represents the result set returned by a fetch query in MySQL. 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. In versions of MySQL earlier than 5.0.3, InnoDB rows contain some redundant information, such as the number of columns and the length of each column, even for fixed-size columns. Assuming you're using PHP, you'd use mysql_affected_rows(), if the return from that was 1, you successfully locked it. For these user accounts what works and what doesn't is not defined, but it's safe to assume that nothing will work. Another question: how did you achieve this state ? 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.

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