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26-Jan-2018 23:26

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The following My SQL statement will update the 'receive_qty' column of newpurchase table with a new value 25 if the value of purch_price is more than 50.

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Finally, it needs information about which specific rows are to be updated (controlled by the WHERE keyword).But if there are a large number of rows that require an update, then the overhead of issuing large numbers of UPDATE statements can result in the operation as a whole taking a long time to complete.The traditional advice for improving performance for multiple UPDATE statements is to “prepare” the required query once, and then “execute” the prepared query once for each row requiring an update.But it's hard to tell from what has been explicitly given in your question.

CREATE ALGORITHM=MERGE VIEW products_with_packaging_info AS SELECT p.*, pt.width as packaging_width, pt.height as packaging_height, pt.weight as packaging_weight, pt.case_count AS packaging_case_count FROM PRODUCTS p JOIN PACK_TYPES pt ON = p.packaging_type; queries against this view work exactly the same as queries against either table individually, as long as every product has a pack type.Let us start with a simple table: UPDATE staff SET salary = 1200 WHERE name = ' Bob'; UPDATE staff SET salary = 1200 WHERE name = ' Jane'; UPDATE staff SET salary = 1200 WHERE name = ' Frank'; UPDATE staff SET salary = 1200 WHERE name = ' Susan'; UPDATE staff SET salary = 1200 WHERE name = ' John'; UPDATE staff SET salary = 1200 WHERE name = ' Bob'; UPDATE staff SET salary = 1250 WHERE name = ' Jane'; UPDATE staff SET salary = 1200 WHERE name = ' Frank'; UPDATE staff SET salary = 1250 WHERE name = ' Susan'; UPDATE staff SET salary = 1200 WHERE name = ' John'; We are no longer setting all the salary fields to the same value, so we can’t collapse it into a single statement.