Re: Disk buffering of resultsets - Mailing list pgsql-jdbc
From | Dave Cramer |
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Subject | Re: Disk buffering of resultsets |
Date | |
Msg-id | CADK3HH+offVAUeAq5ROw3_Kg2p9BXT1zEEiNMLgKV_MX2WkVYA@mail.gmail.com Whole thread Raw |
In response to | Re: Disk buffering of resultsets (Vitalii Tymchyshyn <vit@tym.im>) |
Responses |
Re: Disk buffering of resultsets
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List | pgsql-jdbc |
Hello, all.Basically, alpha of p.1 is available here: https://github.com/tivv/pgjdbc/tree/offloadingIt passes all the tests of cursor-based implementation, but I want to add some more (mostly with multiple open statements).Best regards, Vitalii Tymchyshyn2014-10-14 4:09 GMT-04:00 Enrico Olivelli - Diennea <enrico.olivelli@diennea.com>:Hi,
we can give support doing some benchs with our platform as soon as some ALFA/BETA will be available.
We are longing for this series of improvements!
I hope that these features could be used with 9.3 server and that we won’t need to upgrade to 9.4 (which is not still stable )
Thank you very much
Enrico Olivelli
Software Development Manager @Diennea
Tel.: (+39) 0546 066100 - Int. 925
Viale G.Marconi 30/14 - 48018 Faenza (RA)
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Da: pgsql-jdbc-owner@postgresql.org [mailto:pgsql-jdbc-owner@postgresql.org] Per conto di Vitalii Tymchyshyn
Inviato: lunedì 13 ottobre 2014 17:34
A: Craig Ringer
Cc: Tom Lane; John R Pierce; PG-JDBC Mailing List
Oggetto: Re: [JDBC] Disk buffering of resultsets
Hello, again.
Sorry for the pause, I had a really busy week. Yet it allowed me to think a little more.
As for me, there are three independent goals that can be addressed independently:
1) Prevent OOMs
Unfortunately this can be addressed with out of heap saving only. The way I did in draft would still OOM when secondary query comes.
Note that it's not that unusual. It's usually used without any multithreading to perform a client-side join, e.g. when complicated inheritance scenario is in place or to load some dictionary data without much duplication (e.g. only few wide dictionary entries for the long query), ...
I am still thinking to do it without much parsing (you will need record type and size and that's all, without field parsing) by simply copying as-is to temp file. Pluggable interfaces can be done later if needed.
2) Fast first record
Here we need to introduce strategies for "who is doing copying and when" from (1). I propose pluggable strategies with few predefined (see below). User can pass predefined strategy name or an Executor as a DataSource parameter or static method reference that returns an Executor when a string is needed (e.g. in connection URI). This would also allow to easily point to Executors.* methods. We may think about ScheduledExecutor requirement to also reuse it for QueryTimeout stuff.
I propose to have next predefined strategies:
a) Direct executor, that does all loading at the very beginning, potentially saving to a temp file.
b) Postponed executor, that works much like in my draft: reads as needed without any disk saving. Performs disk saving only when connection is needed for some other statement.
c) JVM-wide Executors.newCachedThreadPool that will start offloading in parallel as fetchSize is reached.
Also I'd propose to set default fetchSize to some reasonable value, like 1000 and specify one of the strategies (e.g (a)) as default so that we won't get OOM on default settings. Or we should allow to set default fetch size on connection/data source level (or both).
3) Fast cancel/resultset close.
It's the only place where switching to portals is needed as far as I can see and it can be done orthogonal to (1) and (2). I don't see any other goal that will benefit from it. To be honest, I am willing to do (1) and (2), but not (3) because this would mean me to get much deeper into the protocol I know almost nothing about right now.
Best regards, Vitalii Tymchyshyn.
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