Window Functions in SQL (2013)

I highly recommend a deep dive into the relational world, and I feel super grateful for the SQL-focused job I held previously. Brought those lessons back with me to both FP and OO.

nickpeterson• 10 years ago

They are extremely useful, although they seem to vary in performance quite a bit (SQL Server experience here, so YMMV). I'm always a bit shocked how little SQL most software developers know, especially because it's often the bottleneck if used poorly.

thom4• 10 years ago

I think my only real complaint about window functions is that you can't access the 'current' row in aggregates and 'filter' conditions. It means very complex look aheads or look behinds aren't really possible.

It would also be great if windows could be function parameters in Postgres. I like to abstract complicated conditionals and calculations into functions, but it falls down if you're operating over a window.

lukaseder6• 10 years ago

Would you mind providing an example of what you'd like to do, which is too complex for window functions?

thom4• 10 years ago

Apologies for contrived examples. First, it'd be nice to be able to use both rows inside some aggregates, e.g.:

    min(ST_Distance(this.point, foo.point)) over (blah)

That is, for each 'foo', get me the minimum distance to another foo in the current window.

The second peeve is to do with filters, e.g.:

    count(*) filter (where this.time - foo.time < 5 and type_id = 42) over (blah)

That is, how many events of type 42 are there up to 5 seconds before the current event.

In both cases, it's sad not being able to address the current row as well as the row in the window. I'm not saying either form is completely impossible to get working somehow, I just think it'd be a nice feature.

taeric• 10 years ago

So, yeah. Window functions are new to me. I was actually asking the team about a month ago if there was a way to do this in SQL. Consider my mind blown, and thanks for posting!

jnordwick9• 10 years ago

LAG/LEAD are basically SQL having to give in a little to the timeseries and column db people. It obliterates the set theoretic nature of SQL, and they are dog slow.

This is why any decent columnar/timeseries db has its own often arrish query language to take advantages of ordering information inherent in the data. There is an order in that index and SQL table, you just don't have good tools to access and use it.

This touches on a conversation I was having a couple weeks ago where somebody was saying that column/array storage is purely a backend consideration and don't need to care about it in the front end of the database. That view gets you ugly primitives like LAG/LEAD. Being able to exploit your backend decision is paramount to performance.

Products like Informix or KDB+ just give you full access to the data on and off disk as an array so you ca build complex windowing primitives (and even store them and reuse them later).

(PS: I just find this really funny. KDB+ is probably is the only database I know that literally does streaming analytics on a Raspberry Pi. No joke, the full DB on Linux ARM/Pi. https://kx.com/download/ )

saurik• 10 years ago

Exciting! Can you point at something where one could learn about this specific feature of these kinds of databases? (Maybe like, "this is an example of that aspect of their syntax in particular, go read how it works", or "here is an article taking about how awesome this property is".)

jnordwick9• 10 years ago

Not exciting. Most of the array processing / streaming facilities are steaming piles.

You have Hadoop/MR and Monet in the OSS group. SysbaseIQ, KDB, Teradata, Vertica, VectorWise, etc. all provide either extended SQL or additional query support to use ordering information in some (often weak) way.

You can even count Oracle In Memory Analytics with TSQL with its cursor model if you really want.

For example for KDB to get the last price and sum of volumer for each second of AAPL you would do in KSQL:

  select last px, sum vol by time.second from trade where sym=`AAPL

on it can be done in its lower level language K/Q as (approx, I'm a little rusty)

  g:group trade.time.second @ where trade.sym=`AAPL
  flip`px`vol!(last each trade.px g; sum each trade.vol g)

thom4• 10 years ago

Do you know what the story is for using geospatial data with KDB+?

jnordwick9• 10 years ago

This is about the closest I know. Kx does a lot with utilities for metering and IoT stuff, but I haven't really kept up with that side of things as much as I do with the finance side. However I do know there are some using it for geospatial, and they are always eager to push into new areas so love the challenge. If a new datatype/index type needs to be done to support geospatial and be the fastest there, they are always up to the challenge.

There were a couple really, really cool tech talks I've been to. The title alone gives it props :)

"where Rumsfeldism & Kx collide"

https://kx.com/2014/12/07/visualizing-really-big-data/

in case you're curious about one of the other: a polymer hypergrid with an absurd amount of real time updating data:

http://openfin.github.io/fin-hypergrid-polymer-demo/componen...

aksyn• 10 years ago

http://code.kx.com/wiki/Cookbook/Geospatial

lukaseder6• 10 years ago

I would be very surprised if LEAD and LAG couldn't profit from indexing, if you design your query / window function in a way that it actually can profit.

Perhaps you're hinting at the idea that it's too easy to screw this up as a user, for it to be inefficient

jnordwick9• 10 years ago

The doesn't help that much since you are probably already using an index for filter criteria, the table is probably unkeyed (fact table).

The case it does work is that you are ordered on timestamp (for example), the query planner properly figures to use any filtering indexes and sequential indexes, ... magic occurs

Now the job is making an SQL statement that the query planner can actual understand and optimize since SQL lacks so much of the machinery for order-dependent processing (this was a feature when SQL was conceived remember).

alfalfasprout• 10 years ago

KDB+ is incredibly well designed, fast, and very mature. But it has one big problem. At $$$ / year (can't divulge pricing due to NDAs but it's > $10^4 for a very modest installation) you're talking about a massive expense if you want any kind of large deployment.

jnordwick9• 10 years ago

I love KDB. When I first started, I hated it... with a fierce passion. I didn't see the point, but I was young and dumb and better looking.

When the "Why's that company so big? I can do that in a weekend." article came out last week:

https://news.ycombinator.com/item?id=12626314

I immediately thought of Kx and KDB and how it is literally the exact opposite. If people only knew how small the firm started with Arthur hacking away seemingly out developing entire corporations they would laugh.

"Yeah give me about two years and a dev team of a about 20 then about 10 for QA and we've have something shippable... abother year or two for performance... 5 years we'll be in the hunt." Yeah, we'll this guy over here basically did it in six months with only two others. And it's 100x faster than anything else. Why can't you do that?

Given his history too with A+ at Morgan Stanley, it wouldn't be the first time a team of a small handful he was at the core of beat the socks off everybody else either. Some people just have this amazing ability to see simplicity. I've had the pleasure of being around a few people boss like that.

cygned• 10 years ago

The most useful feature imho is temporal data. Too bad Postgres does not support it.

teilo• 10 years ago

Windows functions are a feature I cannot live without. They achieve results that otherwise could only be achieved with complex and ugly CASE and embedded SELECTs. Another reason Postgres is superior to MySQL.

Window Functions in SQL (2013)

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