Hii, On Fri, Sep 13, 2024 at 10:22 PM yudhi s <learnerdatabase99@xxxxxxxxx> wrote: > > Hello, > We have to update a column value(from numbers like '123' to codes like 'abc' by looking into a reference table data) in a partitioned table with billions of rows in it, with each partition having 100's millions rows. As we tested for ~30million rows it's taking ~20minutes to update. So if we go by this calculation, it's going to take days for updating all the values. So my question is > > 1) If there is any inbuilt way of running the update query in parallel (e.g. using parallel hints etc) to make it run faster? > 2) should we run each individual partition in a separate session (e.g. five partitions will have the updates done at same time from 5 different sessions)? And will it have any locking effect or we can just start the sessions and let them run without impacting our live transactions? Do you have any indexes? If not - you should, if yes - what are they? Thank you. > > UPDATE tab_part1 > SET column1 = reftab.code > FROM reference_tab reftab > WHERE tab_part1.column1 = subquery.column1; > > Regards > Yudhi
