Re: Faster distinct query?

Sorry - break for dinner! So much happens on a global scale in a few
hours. :-)!

I took a few minutes and created a simple example here of what I imagine
you have on that table. I only inserted ~80 million rows of test data, but
hopefully, it's somewhat representative.

TimescaleDB's current implementation of SkipScan only allows distinct on
one column, and because of where we can place the hook to read the query
cost, a LATERAL JOIN (or similar) can't be used to get both columns like
you want. So, to outsmart the planner, you can get your results with one of
the DISTINCT queries in a function. I realize this is getting a bit
specific, so it might not be an exact fit for you, but this query comes
back on my 78 million rows in 67ms. YMMV

Step 1: Create a function that returns the array of channels per station

CREATE FUNCTION channel_array(TEXT) RETURNS text[]
AS $$
SELECT array_agg(channel) FROM (
select distinct on (channel) channel from stations where station=$1
) a
$$
LANGUAGE SQL;

Step 2: Use a CTE for the distinct stations, querying the function for each
station

WITH s1 AS (
SELECT DISTINCT ON (station) station FROM stations
)
SELECT station, channel_array(station) channel
FROM s1;

If it's using the index, you should see something like:

Subquery Scan on s1 (cost=0.57..16.22 rows=19 width=34) (actual
time=0.580..4.809 rows=19 loops=1)

-> Unique (cost=0.57..11.28 rows=19 width=2) (actual time=0.043..0.654
rows=19 loops=1)

-> Custom Scan (SkipScan) on stations (cost=0.57..11.23 rows=19
width=2) (actual time=0.042..0.647 rows=19 loops=1)

-> Index Only Scan using idx_station_channel on stations
(cost=0.57..1807691.34 rows=76000032 width=2) (actual time=0.040..0.641
rows=19 loops=1)
Index Cond: (station > NULL::text)

Heap Fetches: 19

HTH,
Ryan

On Wed, Sep 22, 2021 at 6:22 PM Israel Brewster <ijbrewster(at)alaska(dot)edu>
wrote:

> On Sep 22, 2021, at 2:05 PM, Ryan Booz <ryan(at)timescale(dot)com> wrote:
>
> Ah. I didn't realize that. If SkipScan was chosen, you'd actually see it
> as one of the execution nodes. I also realize I was making a few
> assumptions about your data, are channels shared among stations, or are all
> channels unique (like an ID) per station? That would impact the index and
> approach.
>
>
> Ok, that may be a good point: “channel” is currently a varchar column,
> containing something like ‘BHZ’, ‘EHZ’, ‘BHE’ etc. There are only a handful
> of possible channels that I am currently aware of, which are shared among
> stations - most stations have a ‘BHZ’ channel, for example. That would be
> fairly simple to normalize out if that would help.
>
>
> Something like:
>
> station | channel
> ----------|-----------
> 1 1
> 1 2
> 2 3
> 2 4
>
> or:
> station | channel
> ----------|-----------
> 1 1
> 1 2
> 2 1
> 2 2
>
>
>
>
> On Wed, Sep 22, 2021 at 5:53 PM Israel Brewster <ijbrewster(at)alaska(dot)edu>
> wrote:
>
>> On Sep 22, 2021, at 1:50 PM, Ryan Booz <ryan(at)timescale(dot)com> wrote:
>>
>> Cool. I'd be interested to see the explain on it if you ever try it
>> again. On that cardinality, I'd expect it to be really fast, so I'm
>> interested to see if the (SkipScan) nodes were actually used.
>>
>>
>> With timescaledb extension installed, the explain is what I posted in the
>> original message (https://explain.depesz.com/s/mtxB#html) Without
>> timescaledb installed, the explain looks the same, except it takes twice as
>> long to run.
>>
>> Unless I missed something in your message, i.e. some sort of tweak to the
>> query to get it to use the timescaledb features?
>>
>> ---
>> Israel Brewster
>> Software Engineer
>> Alaska Volcano Observatory
>> Geophysical Institute - UAF
>> 2156 Koyukuk Drive
>> Fairbanks AK 99775-7320
>> Work: 907-474-5172
>> cell: 907-328-9145
>>
>>
>> On Wed, Sep 22, 2021 at 5:35 PM Israel Brewster <ijbrewster(at)alaska(dot)edu>
>> wrote:
>>
>>>
>>> On Sep 22, 2021, at 12:49 PM, Ryan Booz <ryan(at)timescale(dot)com> wrote:
>>>
>>> [Timescale Dev Advocate here]
>>> I realize this might not be the most accepted answer (could be
>>> interpreted as trying to "sell" something), but feels like an opportunity
>>> to talk about DISTINCT queries and opportunities. Because you have that
>>> index, Timescale 2.3 added a "Skip Scan" query planner node that works on
>>> regular BTree indexes (it doesn't have to be time-series/TimescaleDB
>>> Hypertable data at all). In this case, your distinct query would likely run
>>> in a few milliseconds based on the counts you mention (170 stations, 3
>>> channels per station), and then the outer aggregation would do the GROUP
>>> BY. So, you **could** add the TimescaleDB extension to your database (or a
>>> copy of) and give it a try. You don't actually need to use any TimescaleDB
>>> features otherwise.
>>>
>>>
>>> I had actually already done that, as I was considering, in spite of past
>>> negative experiences with timescaledb, experimenting with it on this DB to
>>> see if it worked any better with this data. Out of curiosity, I tried
>>> removing the timescaledb extension, whereupon the query in question took
>>> roughly twice as long. So you are right that installing timescaledb speeds
>>> things up, even when not using any timescaledb specific functions. So that
>>> was a good call. Thanks!
>>>
>>> ---
>>> Israel Brewster
>>> Software Engineer
>>> Alaska Volcano Observatory
>>> Geophysical Institute - UAF
>>> 2156 Koyukuk Drive
>>> Fairbanks AK 99775-7320
>>> Work: 907-474-5172
>>> cell: 907-328-9145
>>>
>>>
>>>
>>> - A writeup of why this kind of DISTINCT query is slow in PostgreSQL
>>> (for now) and what we did to overcome it:
>>> https://blog.timescale.com/blog/how-we-made-distinct-queries-up-to-8000x-faster-on-postgresql/
>>> - Plans for a similar feature in PostgreSQL proper that we'd totally
>>> support but hasn't made forward progress yet:
>>> https://commitfest.postgresql.org/19/1741/
>>>
>>> Anyway, it might be worth a shot. HTH
>>>
>>> Ryan B
>>>
>>> On Wed, Sep 22, 2021 at 4:27 PM David G. Johnston <
>>> david(dot)g(dot)johnston(at)gmail(dot)com> wrote:
>>>
>>>> On Wed, Sep 22, 2021 at 1:21 PM Michael Lewis <mlewis(at)entrata(dot)com>
>>>> wrote:
>>>>
>>>>> In the future, please share the plan returned by explain analyze, and
>>>>> some data about how many rows in the involved tables,
>>>>>
>>>>
>>>> I believe we consider it acceptable to link to an explain viewer, which
>>>> is what the OP did. Reading explain output in email has its own
>>>> challenges, and I'd rather have the website than a text attachment.
>>>>
>>>>
>>>>> How does the below work? It should do a very simple index scan only,
>>>>> then aggregate the relative few rows after the fact.
>>>>>
>>>>> select station, array_agg(distinct(channel)) as channels
>>>>> FROM(
>>>>> SELECT station,channel FROM data GROUP BY station,channel
>>>>> ) AS sub
>>>>> group by station;
>>>>>
>>>>
>>>> Yeah, am pondering this too, though seems like the queries should be
>>>> identical so the plan/execution should be the same either way.
>>>>
>>>>
>>>>> If there is correlation between station & channel, then you might look
>>>>> at creating a multivariate statistics object and analyzing the table so the
>>>>> planner can make better choices
>>>>>
>>>>
>>>> There is no where clause so I'm doubtful there is much to be gained
>>>> going down this path. The Index-Only scan seems like an optimal way to
>>>> obtain this data and the existing query already does that. The aggregation
>>>> path might vary though it seems like that shouldn't be the case here.
>>>>
>>>> David J.
>>>>
>>>
>>>
>>
>