We have a database that contains around 235 GB of data (calculcated using
pg_total_relation_size for each table) on a server with around 77GB of memory. The server is used for nothing else (aside from SSH, backup and similar administrative stuff). We are running postgres 9.2.
I extracted one table of 13GB and tested it on a seperate server with 4GB of memory to benchmark some queries, indexes, etc. outside of our production environment. I had some questions for this which can be seen here: https://stackoverflow.com/questions/26468982/avoiding-external-disk-sort-for-aggregate-query.
On the seperate server, the queries use index-only scans and run relatively fast (compared to pre-index creation with sequence scans). The same queries against the same table on the production machine does a sequence scan almost no matter what settings I set up (short of setting
seq_page_cost lower than
random_page_cost, which is a Bad Idea(tm).)
Our workload is to extract analytical data - we have around 10 columns that are raw numbers that we do a lot of
SUM() aggregate queries on, usually grouped by an item ID. The data is updated constantly, mostly with
UPDATE queries to existing rows to update per-day data is it comes in during the day (so a row for a specific day may be updated ~20 times in one day). The 13GB table is for one of our biggest customers and have around 6 million rows.
The customized settings from the production config looks like this:
shared_buffers = 20000MB effective_cache_size = 56000MB work_mem = 512MB maintenance_work_mem = 2048MB checkpoint_segments = 64 temp_buffers = 16MB max_stack_depth = 4MB wal_level = archive archive_mode = on archive_timeout = 6h checkpoint_timeout = 1h wal_writer_delay = 100 wal_keep_segments = 32
I am looking for some insights for how to create indexes (and alter queries), as obviously in the larger setup the query planner acts differently based on the amount of data.
- Is it better with small indexes that only cover the small parts of the query to help with lookups or full covering indexes (for index-only scans)?
- Does the above setup match my server specifications and workload?
- Any good tips to speed up aggregate queries (mainly
SUM) for all rows and grouped by item ID (I am aware we may need to look into column-store databases)?
Also, does any of the above stand out as being "wrong" or should I modify it? We are running it off locally attached disks, but backup is being sent off to NFS disks (SAN).