I have a table that, if we look at just the relevant parts, has two columns: id and raw_data. id is an integer, and raw_data is a text blob. At this point, the table has no constraints or indexes except for an index on id.

My goal is to deduplicate (by id) this data and dump it all to plaintext files (on Amazon S3).

Note that any row with the same id can be assumed to be an exact duplicate (so I only need one, random row’s data per id).

The table is on an Amazon EC2 RDS database with 2TB of space, 15GB of RAM. I can expand settings if needed, but want this to run over a reasonable time (i.e. max 24-48 hours, preferably faster).

The queries I’m trying to run (but are too slow) are:

SELECT DISTINCT ON (id) id, data FROM table OFFSET <0 through end of table> LIMIT 250000 

The first few offsets run within a reasonable time, but quickly becomes unmanageable (at least minutes to return) when the offset hits 10m+.

Since starting, I’ve created that id index, removed all other constraints and indexes (there’s other columns than I described, but not relevant), set maintenance_work_mem to 4GB (for creating the id index), and most recently tried making the id index a clustered index. But this happened:

cluster id using idx_0; ERROR:  could not extend file "base/16390/46741.294": wrote only 4096 of  8192 bytes at block 38558630 HINT:  Check free disk space. 

Key questions:

1) Is SELECT DISTINCT ON with an OFFSET the right way to do this? Is there a more efficient query for pulling the data?

2) Is there anything else I can do to the DB/table to optimize? Would the clustered index solve my problem? Why is it taking over 1.1TB of extra space to deal with ~800GB of data?

Thanks for any advice!