How to update data after adding columns?

When updating data from a database column, it is recommended to use batch update or batch update functions. Batch updates can be processed using cursor cyclic processing. Batch updates can be used to optimize efficiency by using the database parallel update characteristics, while avoiding performance problems or locked tables caused by direct update of all rows.

How to elegantly update data after adding a database column?

Many friends will encounter this problem in database operations: How to fill in the existing data after adding a column? Directly update the UPDATE statement? That efficiency is worrying and prone to problems. This article will talk about this seemingly simple database update technique, but actually has hidden mystery.

Let’s talk about some basic things first. As for the database, to put it bluntly, it is an orderly data warehouse. Adding columns is like adding a shelf to the warehouse, but the shelves are empty, so things have to be put on. The UPDATE statement is like a porter, but the way it carries determines efficiency and stability. Blindly updating all rows with UPDATE statements is like throwing things on the shelf with a forklift, which is inefficient and may collapse the shelf (data is damaged).

The core lies in how to update data efficiently and securely. The most direct way is of course to use UPDATE , but you need to add some material. For example, you can update in batches according to actual conditions, or use the batch update function of the database. This is like using a conveyor belt, rather than a forklift, to transport goods, which is much more efficient. Code example (taking MySQL as an example, other databases are similar):

 <code class="sql">-- 分批更新，假设每次更新1000行DECLARE done INT DEFAULT FALSE; DECLARE batch_size INT DEFAULT 1000; DECLARE start_id INT DEFAULT 0; DECLARE end_id INT DEFAULT 0; DECLARE cur CURSOR FOR SELECT id FROM your_table; DECLARE CONTINUE HANDLER FOR NOT FOUND SET done = TRUE; OPEN cur; read_loop: LOOP FETCH cur INTO start_id; SET end_id = start_id batch_size -1; IF done THEN LEAVE read_loop; END IF; UPDATE your_table SET new_column = DEFAULT_VALUE WHERE id BETWEEN start_id AND LEAST(end_id, (SELECT MAX(id) FROM your_table)); END LOOP; CLOSE cur;</code>

This code is processed in batches with cursors to avoid performance problems caused by directly updating all rows. DEFAULT_VALUE is replaced by default according to your needs, such as 0 , NULL , or a calculation result. Note that the LEAST function is used to prevent end_id from exceeding the maximum id .

To be more advanced, you can use the characteristics of the database to optimize. Some databases support parallel updates, which can greatly shorten the update time. But be aware that parallel updates may also bring about data consistency problems and need to be handled with caution. This is like using multiple conveyor belts at the same time, which is extremely efficient, but it is necessary to coordinate the work of each conveyor belt to avoid chaos.

Let’s talk about the easy pitfalls. It is inefficient to update all rows directly with UPDATE your_table SET new_column = 'some value'; and if your table is very large, it may cause the database to lock tables and affect other operations. This is like using manpower to transport all goods, which is slow and easy to cause congestion.

Finally, don't forget to consider the readability and maintainability of the code. Clear code is not only easy to understand, but also easier to debug and maintain. Good programming habits can help you avoid many detours. It's like an orderly warehouse, making it easy for you to find the goods you need at any time. Remember, the code is written for people to see, and the second is executed for machines.

In short, there is no universal method to update data after adding columns. You need to choose the appropriate solution based on your data volume, database type and actual needs. Think more and try more to find the most elegant solution. Remember, efficiency and stability are equally important.

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