Kynn Jones wrote:
Hi! As part of a data warehousing project, I need to pre-process data downloaded from an external source, in the form of several large flat files. This preprocessing entails checking the validity of various data items, and discarding those that fail to pass all the checks. Currently, the code that performs the checks generates intermediate temporary tables of those bits of data that are invalid in some way. (This simplifies the process of generating various quality-control reports about the incoming data). The next step is to weed out the bad data from the main tables, and here's where I begin to get lost. To be concrete, suppose I have a table T consisting of 20 million rows, keyed on some column K. (There are no formal constrains on T at the moment, but one could define column K as T's primary key.) Suppose also that I have a second table B (for "bad") consisting of 20 thousand rows, and also keyed on some column K. For each value of B.K there is exactly one row in T such that T.K = B.K, and the task is to delete all these rows from T as efficiently as possible. My naive approach would something like DELETE FROM T WHERE T.K IN ( SELECT K FROM B ); ...which, according to EXPLAIN, is a terrible idea, because it involves sequentially scanning all 20 million rows of T just to delete about only 0.1% of them. It seems to me better to sequentially scan B and rely on an index on T to zero-in the few rows in T that must be deleted. Is this strategy something that can be done with plain SQL (even if to do this I must produce additional helper tables, indices, etc.), or must I write a stored procedure to implement it?
The planner knows how to produce such a plan, so it must thinking that it's not the fastest plan.
Have you ANALYZEd the tables? You do have an index on T.K, right? What does EXPLAIN ANALYZE output look like? (you can do BEGIN; EXPLAIN ANALYZE ...; ROLLBACK; if you don't want to actually delete the rows)
The sequential scan really could be the fastest way to do that. If those 0.1% of the rows are scattered randomly across the table, an index scan might end up fetching almost every page, but using random I/O which is much slower than a sequential read. For example, assuming you can fit 100 rows on a page, deleting 0.1% of the rows would have to access ~ 10% of the pages. At that point, it can easily be cheaper to just seq scan it.
You can try to coerce the planner to choose the indexscan with "set enable_seqscan=off", to see how fast it actually is.
You could also write the query as DELETE FROM t USING b WHERE t.k = b.k, but I doubt it makes much difference.
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