![]() ![]() Now, you should have the case that ROWIDs and the text key are consistent, so tracking changes in one will track changes in the other. Then do a join to find records with the same text key but different ROWID, and renumber the ROWID in your local database to match. Assuming the changeset set comes in as an SQLite database, first, do a join to find records with the same ROWID but different text keys, and renumber those rows to some value unused in either the local database or the changeset. If this is the case, my concept of a prefilter would be then when you bring the changeset in, you first fix your database to correct for ROWID issues with your text key. I am not an expert in the session extension either (I haven't used it at all), and I am a bit surprised that it can't handle the case of the unique identification of a data row being a unique text field instead of the somewhat arbitrary ROWID primary key. TEXT, PRIMARY KEY(translatableId, language)) TranslatableId INTEGER NOT NULL REFERENCES translatables(id) ON DELETEĬASCADE, language TEXT NOT NULL CHECK (language != ''), translation I am not an expert in Sqlite, so maybe somebody knows a better way.ĬREATE TABLE IF NOT EXISTS translatables(id INTEGER NOT NULL UNIQUE, translationTextId TEXT PRIMARY KEY NOT NULL CHECK (translationTextId != ''), screenId TEXT, defaultText TEXT)ĬREATE TABLE IF NOT EXISTS translations(id INTEGER NOT NULL UNIQUE, Like you see in this examples I have an extra unique index which could be an alias to ROWID but this is impossible because I use already an other So I think what I really need is an alias of ROWID which is not a PRIMARY KEY. Then I cannot use ROWID for it because it is unstable and does not work together with the FOREIGN KEYS. Third I need an integer id for efficiency in the child table because the PRIMARY KEY in the parent table is large. Second I need the PRIMARY KEY of a text field for the sessions. Option 2Īssuming the table has been restored with its original data (including duplicate rows), here’s another option for de-duping it.First I need the ROWID for the update hook. Unless it has been explicitly removed from the table, you can use this as a unique identifier for each row, which enables us to construct the above queries. By default, every row in SQLite has a special column, usually called the rowid, that uniquely identifies that row within the table. The reason we were able to do this is because of SQLite’s rowid. Two of the duplicate rows for “Bark” have also been deleted. To delete the duplicate values, we can modify the above query by replacing SELECT * with DELETE: DELETE FROM PetsĪs expected, one of the duplicate rows for our dog “Wag” has been deleted and the other one remains. This shows us that three rows are going to be deleted when we de-dupe the table in the next step. Option 1īefore we de-dupe the table, we can use the following query to see which row/s will be deleted: SELECT * FROM Pets In any case, below are two options for finding and deleting duplicate rows. If there was a primary key, it would contain unique values across all rows, and there would be no duplicates. Therefore, it’s not a unique identifier for each row, and it cannot be used as a primary key. The PetId column might look like it could be a primary key, but it actually contains duplicate values. In this case, all columns are duplicates. ![]() We can see that the first two rows are duplicates, as are the last three rows. Suppose we have a table with the following data: SELECT * FROM Pets ![]() This is often referred to as de-duping the table. So if there are three identical rows for example, it deletes two of them and keeps one. These examples delete duplicate rows but keep one. The following options can be used to delete duplicate rows in SQLite. ![]()
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