How should I properly update MySQL databases?
Given a MySQL database that comprises 60 tables and corresponding data, and an enhanced version of the said database sans data, how does one proceed?



This refreshed iteration of the database boasts additional features such as auto-increments and indexes.
The crux of the issue revolves around deriving an up-to-date database that perfectly merges existing data with the new structure.

 Here's a high-level step-by-step guide on how you can carry this out.

However, before anything else, make sure to create backups of both databases to avoid any irreversible loss of data or structure.

Comparison
Compare the structure of the old and the new database. You can do this by generating the SQL schema files for both databases and doing a comparison.

To generate the schema for a database called myDatabase, you can use the following command:

mysqldump -d -u username -p myDatabase > myDatabase_schema.sql
Tools like diff can help with comparison.

Generate Updating Script
From the comparison, you can generate an updating SQL script that will modify your existing database structure to the new one.

Such scripts may involve ALTER TABLE statements to add or remove columns, change data types, introduce auto-incrementing IDs, and define indices.

For example, to add an auto increment primary key you would:

ALTER TABLE table_name
MODIFY COLUMN column_name datatype AUTO_INCREMENT PRIMARY KEY;
And to create an index:

CREATE INDEX index_name
ON table_name(column1, column2,...);
Test the Script
Apply the updating script on a copy of your old database first, not the actual database you're using. This way, you can catch and correct any errors that occur during the updating process without disrupting your main database.

Data Migration
If some tables or columns are entirely new in the updated structure, you may need to migrate data if appropriate. This can involve writing additional SQL scripts or using a tool designed for data migration.

Apply Updates to the Main Database
After you are sure that the script works as intended, you can apply it to the main database. Ensure to minimize downtime if your database is used in a production environment.

Remember, taking backups before any major operation is recommended, as things could go wrong. Make sure you understand all changes you're making to mitigate risks. And take notes of the steps you take to have a fallback plan if the resulting database does not behave as expected.

Assuming this is a live database, note that this approach can result in downtime which should be considered when planning to perform these actions.


Based on the information in the previous response, we can delve a bit deeper into some of the steps.

1. Comparison

This part is where you determine what changes have been made in the new structure that are not available in the current database. You can use the native diff utility if you are using a Unix-like operating system for this.

In case your databases are fairly large or complex, or if you're not comfortable using command-line tools. GUI tools such as MySQL Workbench, Navicat, or SQLyog can accomplish similar comparisons.

These tools not only show the differences between schemas but also generate the SQL scripts necessary for patching the old database.

2. Generate Script

To add more detail to the prior examples of scripts:

Adding new columns:

ALTER TABLE table_name
ADD COLUMN column_name datatype;
Modifying existing columns:

ALTER TABLE table_name
MODIFY COLUMN column_name new_datatype;
Deleting a column:

ALTER TABLE table_name
DROP COLUMN column_name;
Create an index:

CREATE INDEX index_name
ON table_name(column_name);
Depending on what the changes are, the specifics of this will vary. Creating the migration script can be complicated and time consuming, but it's crucial because this directly modifies your database.

3. Test the Script

Testing the update script is done to make sure that the changes you have constructed match the requirements without causing any harm (like data loss or application issues).

A practical way to do this is to create a clone of your old database and run your update script on it. Then you can verify the results by doing another schema comparison between the updated clone and the new database.

If there are still differences, you need to adjust your update script and repeat the process until you get it right.

4. Data Migration

Data migration would be involved if a new table or column requires existing data to be moved to it. This can be done with simple UPDATE and INSERT INTO... SELECT queries, or they may be more complex as required.

For example, to move data from old_column in the same table to new_column:

UPDATE table_name
SET new_column = old_column;
To copy all data from old_table to new_table:

INSERT INTO new_table
SELECT * FROM old_table;
5. Apply Updates to the Main Database

Once you are confident in your migration script (i.e., it's been thoroughly tested), you can then run this on your actual database.


In addition to the instructions in the previous responses, another strategy you may choose to consider is a phased or iterative approach. This involves gradually integrating the new schema changes into the existing database. This strategy is preferred when downtime is a key concern and must be minimized.

Here's how you can go about it:

Phased Migration

Design an Interim Schema: Identify the changes between the old and new schema, and design an interim schema that is compatible with both the old and new database. This may mean adding new columns or tables that are needed in the new schema but making sure they don't disrupt the operations of older applications.

Backfill Data: Start a process to populate the new columns or tables in the backdrop with the necessary data. This can be done iteratively over a period of time without affecting the database's availability.

Application Code Switch: Once your data backfill is complete and verified, modify your application code to begin using the new table or column instead of the old one. This switch should be tested thoroughly before implementing.

Gradual Rollout: Consider gradually rolling out these changes starting with a small subset of users and continuously monitoring for any issues. As you gain confidence, you may increase this user base until everyone is using the new application code.

Deprecate Old Schema: Once all operations have been migrated to the new schema, old tables and columns can be safely dropped.

This approach requires more planning and time compared to the 'all-at-once' strategy, but its advantage lies in minimizing the operational risk and downtime. However, it's not always viable or the best approach depending on your unique circumstances.

Furthermore, for database migrations as a whole, there are tools available that can help automate the process:

Schema Migration Tools: Tools like Liquibase and Flyway help to automate and manage schema changes. These tools allow you to script changes, which can be version controlled and automatically applied in sequence.

Database Migration Services: For larger or more complex migrations, cloud providers offer database migration services. AWS Database Migration Service and Google's Cloud Database Migration Service are examples.

Remember, complexity of data migration largely depends on the specific changes in the schema, the amount of data, and the particular requirements of your infrastructure and application. Trying to plan for everything is difficult, so thorough testing in a production-like environment is crucial to success.

You have the chance to carry out migration tasks, for instance, within the dbForge platform.

You can establish a fresh database schema, and then employ the menu path "Compare -> New Schema comparison ..." in order to juxtapose it with the prior one, thereby capturing all differing aspects of the structures.

Identify the components that require an update, perform a right-click maneuver on them and choose "Show schema update script". Consequently, this will provide you with all the requisite ALTER's and CREATE's commands.

Nonetheless, you should exercise caution. There is a possibility that you might need to execute certain updates in a manual fashion. Remember that in the world of databases, automation is a valuable tool, but a keen eye and human touch are sometimes necessary to successfully complete the task.

Essentially, there are dual paths to consider:

1. One can create DDL (Data Definition Language) SQL, that structures the required schema from the base database. Typically, this is an immediate procedure with all changes being atomically represented via DDL scripts. Tools that facilitate structure migration or database comparison can be found automatically. The most rudimentary approach involves exporting the architecture from the erstwhile database (excluding data), followed by using text diff to craft the necessary script to modify the DDL.

2. The alternative entails taking data from the former database and transferring it to the new one. In other words, data is exported from the old entity and populated into the new one.

Regardless of the approach, structural changes can lead to problems, usually pertaining to unique or external indexes not being set up properly (data remains unpopulated). Two solutions here are, either disabling all checks and triggers, using 'insert ignore' then investigating any discrepancies and determining root causes, following which consistency checks can be carried out. Alternatively, proceed with data insertion as planned and endeavour to ascertain why issues ensued. The latter is the only option with DDL scripts.

In scenarios like these, I generally favour data export/import due to index rebuilding, added verifications, and the utility of the old database as a contingency backup. Although, DDL scripts are always available (they align databases between local and remote development servers). Should issues arise, one might have to script data alteration in the combined dump or turn off features in the new database, modify the data, and re-enable them.

Keep in mind that database migration is not just about transferring data; it's also about making sure that the new system operates efficiently and reliably while minimizing downtime.