Hii, On Fri, Sep 13, 2024 at 10:22 PM yudhi s <learnerdatabas...@gmail.com> 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
