Viewing s-Server Performance in SQLLine
You can view s-Server's massive raw performance by using a script that generates data using a SQL "VALUES" clause. (The rate at which s-Server ingests data is generally much slower than the rate at which it processes data.) s-Server ships with an example script in $SQLSTREAM_HOME/examples/parallelPerformanceTest.
Note: $SQLSTREAM_HOME refers to the installation directory for s-Server, such as /opt/sqlstream/5.0.XXX/s-Server.
To run the script on a Linux machine, navigate to $SQLSTREAM_HOME/examples/parallelPerformanceTest and enter the following:
where "%N" is the number of pipelines you want to run. This number should correspond with the number of cores on your server.
For example, to run two pipelines, you would enter
When you run genParallelPerformanceTest.py, it generates the following four SQL scripts in your current directory:
setup%Npipelines.sql, which creates all streams and pumps.
startpumps%Npipelines.sql, a SQL script to start data flowing.
listen%Npipelines.sql, a SQL script to display totals every minute.
stoppumps%Npipelines.sql, a SQL script to stop data from flowing.
In these scripts, N pipelines are used to count rows, grouped by an integer column. Each pipeline aggregates its input, outputting every millisecond. A final query then sums those together, outputting every minute.
You can invoke these scripts by opening SQLLine and entering sqlline --run=<script name>
You should run these scripts in order.
For example, if you ran the script with two pipelines, you would navigate to $SQLSTREAM_HOME/bin, open SQLLine, and enter the following lines, one at a time:
When you run listen2pipelines.sql, you will see something like the following:
Each line represents the number of rows per half minute.
To stop the pumps, enter the following