Thanks to a change in historical data, I have a need to update a large number of records (around 50 million). The update itself is straight forward, as I can just issue an "UPDATE table_name SET changed_field=new_value();" (yes, new_value is the result of a stored procedure, if that makes a difference) command via psql, and it should work. However, due to the large number of records this command will obviously take a while, and if anything goes wrong during the update (one bad value in row 45 million, lost connection, etc), all the work that has been done already will be lost due to the transactional nature of such commands (unless I am missing something).
Given that each row update is completely independent of any other row, I have the following questions:
1) Is there any way to set the command such that each row change is committed as it is calculated?
2) Is there some way to run this command in parallel in order to better utilize multiple processor cores, other than manually breaking the data into chunks and running a separate psql/update process for each chunk? Honestly, manual parallelizing wouldn’t be too bad (there are a number of logical segregations I can apply), I’m just wondering if there is a more automatic option.
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Israel Brewster
Software Engineer
Alaska Volcano Observatory
Geophysical Institute - UAF
2156 Koyukuk Drive
Fairbanks AK 99775-7320
Work: 907-474-5172
cell: 907-328-9145