Hi Mark, We have a somewhat similar situation - we have years of continuous data which are managed in Postgis. The tables are partitioned into annual subsets. The previous (static) years' underlying tables have a clustered index on UTC timestamp, the current year table has a conventional index. It works well, with 20 odd partitions to date.
An annual basis for partitions may not be ideal in your case, but you have not specified how long it takes for your data to become fixed - or if there is a way the database can tell that records are now static. If there is, a scheduled task which migrates such records from a live to fixed partition would perhaps be appropriate. Organising your data by UTC timestamp may be the simplest approach for you. Cheers Brent Wood Programme leader: Environmental Information Delivery NIWA DDI: +64 (4) 3860529 ________________________________________ From: pgsql-general-ow...@postgresql.org [pgsql-general-ow...@postgresql.org] on behalf of Melvin Davidson [melvin6...@gmail.com] Sent: Tuesday, February 10, 2015 6:01 AM To: Marc Mamin Cc: Tim Uckun; pgsql-general Subject: Re: [GENERAL] Partioning with overlapping and non overlapping constraints Well, without knowing too much about your application, it certainly sounds like using the metricts_YYYYMMDD is the way to go. As for modifying the constraint daily, couldn't you just use where timestamp > current_date - Interval '1 Day' ? On Mon, Feb 9, 2015 at 5:14 AM, Marc Mamin <m.ma...@intershop.de<mailto:m.ma...@intershop.de>> wrote: >I have two partitioning questions I am hoping somebody can help me with. > >I have a fairly busy metric(ish) table. It gets a few million records per day, >the data is transactional for a while but then settles down and is used for >analytical purposes later. > >When a metric is reported both the UTC time and the local times are stored >along with the other data belonging to the metric. Don't you have duplicate information within your UTC, location and local_time data ? Maybe you can just attach a timezone to each location... >I want to partition this table to both make it faster to query and also to >spread out the writes. Ideally the partitions would be based on the UTC >timestamp and the sending location. For example > >metrics_location_XXXXX_2015_01_01 > >First problem with this approach is that there could be tens of thousands of >locations so this is going to result hundreds of thousands of tables. I know >there are no upper limits to how many tables there are but I am thinking this >might really get me into trouble later. With only a few millions rows per day, weekly or even monthly partitions without regard of locations should be sufficient for older data. It should be possible to partition your hot data differently; But Instead of using one partition per location, you may use a hash/modulo approach to keep the number of partitions in a reasonable count if required at all (This can be helpful: https://github.com/markokr/pghashlib). Here I would avoid to include time information except for the limit between old and hot tables. And depending on the pattern and performance requirement of your analytic queries this may be sufficient (i.e. don't partition on the time at all). With smaller partitions for hot data, it should be quite fast to move them one by one to the old data. I have no experience with the trigger based partitioning of Postgres (we handle partitions logically at the application level), so I'm not sure how difficult this approach is. I suppose that you'll need a function that move data from hot to old partitons and that fix the triggers accordingly. > >Second and possibly more vexing problem is that often the local time is >queried. Ideally I would like to put three constraints on the child tables. >Location id, UTC timestamp and the local time but obviously the local >timestamps would overlap with other locations in the same timezone Even if I >was to only partition by UTC the local timestamps would overlap between tables. > >So the questions in a nutshell are. > >1. Should I be worried about having possibly hundreds of thousands of shards. >2. Is PG smart enough to handle overlapping constraints on table and limit >it's querying to only those tables that have the correct time constraint. If you partition on the UTC time only, you don't have overlapping. When querying on the local time, the planner will consider all partitions, but an additional index or constraint on this column should be sufficient as long as your partition count remains small. regards, Marc Mamin -- Melvin Davidson I reserve the right to fantasize. Whether or not you wish to share my fantasy is entirely up to you. [http://us.i1.yimg.com/us.yimg.com/i/mesg/tsmileys2/01.gif] -- Sent via pgsql-general mailing list (pgsql-general@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-general
