QUEUE_SPLITTER3(1)

NAME
queue_splitter3 - PgQ consumer that transports events from one queue into several target queues

SYNOPSIS

queue_splitter3 [switches] config.ini

DESCRIPTION

queue_spliter is PgQ consumer that transports events from source queue into several target queues. ev_extra1 field in each event shows into which target queue it must go. (pgq.logutriga() puts there the table name.)

One use case is to move events from OLTP database to batch processing server. By using queue spliter it is possible to move all kinds of events for batch processing with one consumer thus keeping OLTP database less crowded.

QUICK-START

Basic queue_splitter setup and usage can be summarized by the following steps:

    1. pgq must be installed both in source and target databases. See pgqadm man page for details. Target database must also have pgq_ext schema installed.

    2. edit a queue_splitter configuration file, say queue_splitter_sourcedb_sourceq_targetdb.ini

    3. create source and target queues

        $ pgqadm.py ticker.ini create <queue>

    4. launch queue splitter in daemon mode

        $ queue_splitter3 queue_splitter_sourcedb_sourceq_targetdb.ini -d

    5. start producing and consuming events

CONFIG

  Common configuration parameters

job_name
    Name for particulat job the script does. Script will log under this name to logdb/logserver. The name is also used as default for PgQ consumer name. It should be unique.

pidfile
    Location for pid file. If not given, script is disallowed to daemonize.

logfile
    Location for log file.

loop_delay
    If continuisly running process, how long to sleep after each work loop, in seconds. Default: 1.

connection_lifetime
    Close and reconnect older database connections.

use_skylog
    foo.

  Common PgQ consumer parameters

queue_name
    Queue name to attach to. No default.

consumer_name
    Consumers ID to use when registering. Default: %(job_name)s

  queue_splitter parameters

src_db
    Source database.

dst_db
    Target database.

  Example config file

    [queue_splitter3]
    job_name        = queue_spliter_sourcedb_sourceq_targetdb

    src_db          = dbname=sourcedb
    dst_db          = dbname=targetdb

    pgq_queue_name  = sourceq

    logfile         = ~/log/%(job_name)s.log
    pidfile         = ~/pid/%(job_name)s.pid

COMMAND LINE SWITCHES

Following switches are common to all skytools.DBScript-based Python programs.

-h, --help
    show help message and exit

-q, --quiet
    make program silent

-v, --verbose
    make program more verbose

-d, --daemon
    make program go background

--ini
    show commented template config file.

Following switches are used to control already running process. The pidfile is read from config then signal is sent to process id specified there.

-r, --reload
    reload config (send SIGHUP)

-s, --stop
    stop program safely (send SIGINT)

-k, --kill
    kill program immidiately (send SIGTERM)

USECASE

How to to process events created in secondary database with several queues but have only one queue in primary database. This also shows how to insert events into queues with regular SQL easily.

    CREATE SCHEMA queue;
    CREATE TABLE queue.event1 (
         -- this should correspond to event internal structure
         -- here you can put checks that correct data is put into queue
         id int4,
         name text,
         -- not needed, but good to have:
         primary key (id)
    );
    -- put data into queue in urlencoded format, skip actual insert
    CREATE TRIGGER redirect_queue1_trg BEFORE INSERT ON queue.event1
    FOR EACH ROW EXECUTE PROCEDURE pgq.logutriga('singlequeue', 'SKIP');
    -- repeat the above for event2

    -- now the data can be inserted:
    INSERT INTO queue.event1 (id, name) VALUES (1, 'user');

If the queue_splitter is put on "singlequeue", it spreads the event on target to queues named "queue.event1", "queue.event2", etc. This keeps PgQ load on primary database minimal both CPU-wise and maintenance-wise.