Tag: mysql

How to solve error SQL Import Google Cloud

Is it possible that when you try to import a backup of your MySQL database on Google Cloud, you have the following error :

We are trying to import a backup in Google Cloud SQL
The following error appears in the logs
error: exit status 1 stdout(capped at 100k bytes): stderr: ERROR 3546 (HY000) at line 26: @@GLOBAL.GTID_PURGED cannot be changed: the added gtid set must not overlap with @@GLOBAL.GTID_EXECUTED

To solve the problem, open the SQL file with text editor and search the error “@@GLOBAL.GTID_EXECUTED”

After modifying the *.sql file, you should be able to import successfully :

It should now work

Import / Export MySQL Workbench tables in Google Cloud SQL database

If you have a database on Google Cloud and you want to import and export some tables to another database, you will need a database explorer to export your .SQL backup.

Export the tables you want in database

Google Cloud interface only allow to export all a database or a specific database, but not tables

As you can see you don’t have the option to select tables.
To do so, you will have to connect the database with a SQL explorer.
In MySQL Workbench you should go in Server > Data Export

Then you should be able to select the tables you want

select Export to Self-Contained File to have a .SQL file

Import the SQL file to Google Cloud

You will need to upload the SQL file to Google Cloud in order to import it. In order to do it, go to Google Cloud > Cloud Storage, create the bucket if it doesn’t exist yet :

create the bucket dedicated for SQL, with random numbers, to have a unique name
Upload the SQL file generated by MySQL Workbench

Then, you can go on Google Cloud > SQL > Import

Select the SQL file from the bucked and select the database you want the tables to be imported

And then you should have imported successfully the tables on the selected database. You should check it in Operations


In case of errors, check the error in Operations, and modify the .SQL file with a text editor, search the error in the SQL file and remove the lines, and repeat the process (upload it again to Google Cloud Storage and import the SQL file again)