Updating millions of rows is zac efron dating in
Updating a large table in Postgres is not as straightforward as it seems.
The main problem with this approach is the performance, it is a very slow process because in place updates are costly.
It may also require more complex application logic during the migration.
The fastest way to update a large table is to create a new one.
), how I might cluster rows together that are subject to updates, and what I might do if I just get too many updates to handle. The fastest way to update every row in the table is to rebuild the table from scratch. Case 2 is common in Data Warehouses and overnight batch jobs.
I worry about how ETL tools apply updates (did you know Data Stage applys updates singly, but batches inserts in arrays? The two most common forms of Bulk Updates are: Case 1 is uninteresting.