Importing new database table

Question

Where I'm at there is a main system that runs on a big AIX mainframe. To facility reporting and operations there is nightly dump from the mainframe into SQL Server, such that each of our 50-ish clients is in their own database with identical schemas. This dump takes about 7 hours to finish each night, and there's not really anything we can do about it: we're stuck with what the application vendor has provided.

After the dump into sql server we use that to run a number of other daily procedures. One of those procedures is to import data into a kind of management reporting sandbox table, which combines records from a particularly important table from across the different databases into one table that managers who don't know sql so can use to run ad-hoc reports without hosing up the rest of the system. This, again, is a business thing: the managers want it, and they have the power to see that we implement it.

The import process for this table takes a couple hours on it's own. It filters down about 40 million records spread across 50 databases into about 4 million records, and then indexes them on certain columns for searching. Even at a coupld hours it's still less than a third as long as the initial load, but we're running out of time for overnight processing, we don't control the mainframe dump, and we do control this. So I've been tasked with looking for ways to improve one the existing procedure.

Currently, the philosophy is that it's faster to load all the data from each client database and then index it afterwards in one step. Also, in the interest of avoiding bogging down other important systems in case it runs long, a couple of the larger clients are set to always run first (the main index on the table is by a clientid field). One other thing we're starting to do is load data from a few clients at a time in parallel, rather than each client sequentially.

So my question is, what would be the most efficient way to load this table? Are we right in thinking that indexing later is better? Or should we create the indexes before importing data? Should we be loading the table in index order, to avoid massive re-ordering of pages, rather than the big clients first? Could loading in parallel make things worse by causing to much disk access all at once or removing our ability to control the order? Any other ideas?

Update
Well, something is up. I was able to do some benchmarking during the day, and there is no difference at all in the load time whether the indexes are created at the beginning or at the end of the operation, but we save the time building the index itself (it of course builds nearly instantly with no data in the table).

Answer 1

To the best of my knowledge, you are correct - it's much better to add the records all at once and then index once at the end.

Answer 2

I have worked with loading bulk sets of data in SQL Server quite a bit and did some performance testing on the Index on while inserting and the add it afterwards. I found that BY FAR it was much more efficient to create the index after all data was loaded. In our case it took 1 hour to load with the index added at the end, and 4 hours to add it with the index still on.

I think the key is to get the data moved as quick as possible, I am not sure if loading it in order really helps, do you have any stats on load time vs. index time? If you do, you could start to experiment a bit on that side of things.

Answer 3

Loading with the indexes dropped is better as a live index will generate several I/O's for every row in the database. 4 million rows is small enough that you would not expect to get a significant benefit from table partitioning.

You could get a performance win by using bcp to load the data into the staging area and running several tasks in parallel (SSIS will do this). Write a generic batch file wrapper for bcp that takes the file path (and table name if necessary) and invoke a series of jobs in half a dozen threads with 'Execute Process' tasks in SSIS. For 50 jobs it's probably not worth trying to write a data-driven load controller process. Wrap these tasks up in a sequence container so you don't have to maintain all of the dependencies explicitly.

You should definitely drop and re-create the indexes as this will greatly reduce the amount of I/O during the process.

If the 50 sources are being treated identically, try loading them into a common table or building a partitioned view over the staging tables.

Answer 4

Index at the end, yes. Also consider setting the log level setting to BULK LOGGED to minimize writes to the transaction log. Just remember to set it back to FULL after you've finished.