![]() ![]() Note 1: as mentioned in comments, there is a chance you cannot swap in the new column and change the application code at the same time. Obviously, test the process in a test environment beforehand. On the other hand, you can revert to the old column until the very end, in case some problems appear. The total time for the change will be (much) more than with a simple data type change. In my experience this is the way you have to plan with the shortest downtime possible. eventually drop the old column, after removing writing to it on the application side.Check beforehand that the application handles the data type change nicely on all read paths. This will normally be a very fast operation. once all rows are updated, you can do a pair of ALTER TABLE for renaming both columns in the same transaction (the new one to amount, the old one to something else).There is a good chance you want to do a VACUUM ANALYZE after a certain number of rows were updated. Do this gradually, so that the system can still operate normally (probably somewhat slower than usual). copy values from the old column to the new one.change application logic so that it writes into both the old and new columns - this way new rows will have the new column filled with data.add the new column with the desired data type.We want to explore if there are any other strategies to do this task OR in our current strategies what can we do extra or different to minimise our down time. If in doing so aīIGGER DB instance can help, we are open to explore that as well. NOTE: Our primary goal is to minimise the down time. ![]() Create a new partitioned table with exact same configuration, NOTE: we ran this command on the table without dropping any indexes ALTER TABLE table_1 ALTER COLUMN amount type numeric(22, 6) įew of the different strategies that we are exploring:ĭrop all the indexes, triggers and foreign keys while the update runs and recreate them at the end.Ī. Now running an Alter command like below one is taking a lot of time ( hours): So we need to change our type to numeric(22, 6). Now we need to support higher precision upto 6. Initially we created amount column with data type numeric(18, 2). On table_1 (user_id, column_2, column_3, column_5) This table also contains multiple indexes (including partial indexes) create index index_1 Id bigint default nextval('table_1_id_seq'::regclass) not null, Each partition contains 6 months data except the first partition which contains data for almost 18 months.ĭatabase specs: db.r6g.16xlarge (vCPU:64, memory:512, :: represents CAST operator in PostgreSQL.We have a very big POSTGRES table containing more than 8 BILLION rows and growing at a very high rate ( 30 million rows per day). It is asking us to cast the roll_no values into integer type explicitly. PostgreSQL is even providing us with a hint. Specifically, the error will read − ERROR: column "roll_no" cannot be cast automatically to type integer HINT: You might need to specify "USING roll_no::integer". This is because the conversion of text to integer is not that straightforward for PostgreSQL. Now, let us try to convert the roll_no column back to an integer ALTER TABLE marks It simply replaces the digit with the character representing that digit. Because integer to text conversion does not confuse PostgreSQL. Now, for understanding the cases where we need to use an expression, let us first convert the roll_no column to VARCHAR type. We need not use any expression for converting the column type. Now, suppose we want to convert the serial_no column from type INTEGER to BIGINTEGER. Now, let us populate it INSERT INTO marks(serial_no,name, roll_no, marks_obtained, Let us create a new table marks − CREATE TABLE marks( Let us understand both the cases using an example. However, if you convert a TEXT or a VARCHAR entry to INTEGER, you will not be able to do that by default, unless you provide an expression for converting the existing TEXT/VARCHAR values to an integer. For instance, if you convert a column of type INTEGER to type BIGINTEGER, you need not use any expression for the conversion of existing entries to the new types. It is used when you need to use an expression for converting the existing entries in that column from the current type to the new type. The USING part of the syntax is optional. Please note that altering the type of a column is not recommended generally, especially if your table has a lot of entries already. In order to change the type of a column, the syntax is ALTER TABLE table_nameĪLTER COLUMN column_name TYPE new_data_type USING expression ![]()
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