I inhereted a unmaintained database in which the partition function was set on a date field and expired on the first of the year. The data is largely historic and I can control the jobs that import new data into this table.
My question is relating to setting up or altering partitioning to include so much data, roughly 1.5TB counting indexes. This is on a live system and I don’t know what kind of impact it will have with so many users connecting to it at once. I will test this on a non prod system but then I can’t get real usage load on there. My alternative solution was to kill all the users hitting the DB and quickly doing a rename of the table, and renaming a table that does have a proper partitioning scheme in.
I wanted to:
-Keep the same partition function but extend it to:
keep all 2011 data up to a certain date (let’s say Nov 22nd 2011) on 1 partition, all data coming in after that need to be put in their own new partitions
-Do a quick switch of the specific partition which has the full years worth of data
Anyone know if altering a partition on a live system to include a new partition for a full years worth of data, roughly 5-6 billion records and 1.5tb, is plausible? Any pitfalls? I will share my test results once I complete them but want any input. Thanks!
Partitions switch are a metadata only operation and the size of the partition switched in or out does not matter, it can be 1Kb or 1TB, it takes the exactly same amount of time (ie. very fast).
However what you’re describing is not a partition switch operation, but a partition split: you want to split the last partition of the table into two partitions, one containing all the existing data and a new one empty. Splitting a partition has to split the data, and unfortunately this is an offline size-of-data operation.