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Highly verstatile Python SQL Benchmarking tool that generates realistic queries to test performance of any SQL database schema on any given hardware platform. I was a contributing member of this project originally developed at Deep Information Sciences.

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deep_data_bench

Deep Data Bench

How to install:

Ubuntu:

$ sudo apt-get update

$ sudo apt-get install git libmysqlclient-dev python-dev

$ sudo pip install virtualenv

$ virtualenv --python=python2.7 ~/.venv/deep_data_bench; source ~/.venv/deep_data_bench/bin/activate

(deep_data_bench)$ pip install -e git+https://github.com/DeepInfoSci/deep_data_bench.git#egg=deep_data_bench

CentOS:

$ sudo yum install centos-release-SCL

$ sudo yum install python27

$ scl enable python27 bash

$ virtualenv --python=python2.7 ~/.venv/deep_data_bench; source ~/.venv/deep_data_bench/bin/activate

(deep_data_bench)$ pip install -e git+https://github.com/DeepInfoSci/deep_data_bench.git#egg=deep_data_bench

What is Deep Data Bench?

Deep Data Bench is a versatile MySQL benchmarking tool that runs with your data. Rather than using a consistent schema and transaction profile, Deep Data Bench uses special meta data files and configuration files to define and run its tests. These files are highly customizable and generated from a schema you specify.
Deep Data Bench allows you to define tests that run various CRUD profiles in parallel, serial, and with different numbers of threads. It allows for a fine level of control over what those queries will look like and how long or frequently they are run.

Installed Programs:

deep_data_bench - main benchmark app

get_meta_data - for obtaining meta data json file for making very custom workloads/profiles

report_viewer - user to view various reports from a deep_data_bench report file/object

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Highly verstatile Python SQL Benchmarking tool that generates realistic queries to test performance of any SQL database schema on any given hardware platform. I was a contributing member of this project originally developed at Deep Information Sciences.

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