53 lines
2.5 KiB
Markdown
53 lines
2.5 KiB
Markdown
# Query Performance Gauge
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This is a little script to measure the performance of queries against a Trino or MySQL instance. You can use it to run
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several queries and measure how long it takes for results to come back to your local machine.
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## How to use
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1. First, you need to install the package in your Python installation or a virtual environment. If you have our Google
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Drive Shared Drive replicated locally, you can do it like this:
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```commandline
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pip install "git+file:///g:\shared drives\data drive\90 useful\10 query_performance_gauge@master"```
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```
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If not, you simply need to clone the repo somewhere in your machine and replace the path in the previous command.
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2. Afterwards, you need to make a config file. See below details on how to compose one.
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3. Once you have your config file ready, run the following command from the terminal.
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```commandline
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measure_query_performance --config my_config_file.json
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```
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4. Results will be printed in your console as they are available. If instead you would like to store them in a file, a
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quick and easy hack is to redirect output in Powershell to a file. You can do it like this:
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```commandline
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measure_query_performance --config my_config_file.json | Out-File - FilePath my_results.txt
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```
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## Composing a config file
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You can take a look at examples for different setups in `config_examples`. If you want to make a new config file, it
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will probably be easier for you to start from one of those templates.
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A few notes:
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- The valid engines are `"trino"` and `"mysql"`.
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- You can place as many queries as you would like in the `queries_to_measure` list.
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- I advice you to make the first query a silly, fast query such as `SELECT 1` to validate your connection and
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quickly confirm that everything is set up properly.
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## A few more details
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- Queries are run sequentially, as in the second query will only start after the first query is finished.
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- For this to work, your local machine must have access and permission to the connection you are targeting, so
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remember to set up VPNs and other necessary configs properly.
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- A peculiarity: when using MySQL through an SSH tunnel, the port number used by the remote MySQL should be
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free in your local machine. That means that if the MySQL database is listening on port 3306, your local machine
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should have port 3306 free before running this.
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- Queries in JSON must be stored in a single line. A bit of a headache, I know. JSON limitations. You can use [this
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webpage](https://sqlformatter.org/) to easily jump between prettified and one-line formats for any query.
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