Python-Spark-Log-Analysis

Python scripts to process, and analyze log files using PySpark.

👋 This repository's maintainer is available to hire for Python/PySpark/Spark NLP consulting projects. To get a cost estimate, send email to lallyelias87@gmail.com (for projects of any size or complexity).

Requirements

Usage

Clone this repository

git clone https://github.com/lykmapipo/Python-Spark-Log-Analysis.git
cd Python-Spark-Log-Analysis

Install all dependencies

pip install -r requirements.txt

To parse and prepare raw log files, run:

python prepare.py

To get basic summary report of structured logs, run:

python summarize.py

To perform word frequency analysis on structured logs, run:

python count_words.py

To perform keyword extraction analysis on structured logs, run:

python keywords.py

Data

Check data/raw directory for all raw logs data. Each file is in text format, and each log entry is format as [timestamp] level: message.
Check data/interim/structured-logs directory for structured logs data generated when run prepare.py. Each file is in parquet format, and each log entry follow below spark schema:

root
 |-- log_timestamp: timestamp (nullable = true)
 |-- log_level: string (nullable = true)
 |-- log_message: string (nullable = true)
 |-- log_length: integer (nullable = true)
 |-- log_year: integer (nullable = true)
 |-- log_month: integer (nullable = true)
 |-- log_day: integer (nullable = true)
 |-- log_hour: integer (nullable = true)
 |-- log_minute: integer (nullable = true)
 |-- log_second: integer (nullable = true)
 |-- log_message_length: integer (nullable = true)

Check summary report generated when run summarize.py.
Check word frequency analysis report generated when run count_words.py.
Check keywords extraction analysis report generated when run keywords.py.

Contribute

It will be nice, if you open an issue first so that we can know what is going on, then, fork this repo and push in your ideas. Do not forget to add a bit of test(s) of what value you adding.

Questions/Issues/Contacts

lallyelias87@gmail.com, or open a GitHub issue

Licence

The MIT License (MIT)

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.