Re: advice sought - general approaches to optimizing queries around "event streams"

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От Gavin Flower
Тема Re: advice sought - general approaches to optimizing queries around "event streams"
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Msg-id 5425D947.2080304@archidevsys.co.nz
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Ответ на advice sought - general approaches to optimizing queries around "event streams"  (Jonathan Vanasco <postgres@2xlp.com>)
Список pgsql-general
On 27/09/14 09:02, Jonathan Vanasco wrote:
> I have a growing database with millions of rows that track resources against an event stream.
>
> i have a few handfuls of queries that interact with this stream in a variety of ways, and I have managed to drop
thingsdown from 70s to 3.5s on full scans and offer .05s partial scans. 
>
> no matter how i restructure queries, I can't seem to get around a few bottlenecks and I wanted to know if there were
anytips/tricks from the community on how to approach them. 
>
> a simple form of my database would be:
>
>     --  1k of
>     create table stream (
>         id int not null primary key,
>     )
>
>     -- 1MM of
>     create table resource (
>         id int not null primary key,
>         col_a bool,
>         col_b bool,
>         col_c text,
>     );
>
>     -- 10MM of
>     create table streamevent (
>         id int not null,
>         event_timestamp timestamp not null,
>         stream_id int not null references stream(id)
>     );
>
>     -- 10MM of
>     create table resource_2_stream_event(
>         resource_id int not null references resource(id),
>         streamevent_id int not null references streamevent(id)
>     )
>
> Everything is running off of indexes; there are no seq scans.
>
> I've managed to optimize my queries by avoiding joins against tables, and turning the stream interaction into a
subqueryor CTE. 
> better performance has come from limiting the number of "stream events"  ( which are only the timestamp and
resource_idoff a joined table ) 
>
> The bottlenecks I've encountered have primarily been:
>
> 1.    When interacting with a stream, the ordering of event_timestamp and deduplicating of resources becomes an
issue.
>     I've figured out a novel way to work with the most recent events, but distant events are troublesome
>
>     using no limit, the query takes 3500 ms
>     using a limit of 10000, the query takes 320ms
>     using a limit of 1000, the query takes 20ms
>
>     there is a dedicated index of on event_timestamp (desc) , and it is being used
>     according to the planner... finding all the records is fine; merging-into and sorting the aggregate to handle the
deduplicationof records in a stream seems to be the issue (either with DISTINCT or max+group_by) 
>
>
> 2.     I can't figure out an effective way to search for a term against an entire stream (using a tsquery/gin based
search)
>
>     I thought about limiting the query by finding matching resources first, then locking it to an event stream, but:
>         - scanning the entire table for a term takes about 10 seconds on an initial hit.  subsequent queries for the
sameterms end up using the cache, and complete within 20ms. 
>
>     I get better search performance by calculating the event stream, then searching it for matching documents, but I
stillhave the performance issues related to limiting the window of events 
>
> i didn't include example queries, because I'm more concerned with the general approaches and ideas behind dealing
withlarge data sets than i am with raw SQL right now. 
>
> i'm hoping someone can enlighten me into looking at new ways to solve these problems.   i think i've learned more
aboutpostgres/sql in the past 48hour than I have in the past 15 years, and I'm pretty sure that the improvements I need
willcome from new ways of querying data , rather than optimizing the current queries. 
>
Minor point: when specifying PRIMARY KEY, you don't need to also put NOT
NULL (this should make no change to performance).

I notice that the 'id' of 'streamevent' is not marked as a PRIMARY KEY,
so it will not have an index associated with it - hence referencing it
as a foreign key might be slower than expected.


Cheers,
Gavin


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