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This repository contains the implementations of efficient shuffle operators for streaming database systems. It includes the core partitioning logic, write-out management, and performance evaluation benchmarks. The code is designed for high-performance tuple shuffling and scalable partitioning in multithreaded environments.

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LadnerJonas/bachelor-thesis-implementation

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Implementation of the Bachelor Thesis

This bachelor thesis implements efficient shuffle operators for streaming database systems.

Table of Contents

Cloning the Repository

To clone the repository along with its required submodules, run the following command:

git clone --recursive git@github.com:LadnerJonas/bachelor-thesis-implementation.git

Setting up the Python Environment

To set up the Python environment, run the following commands:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Prototype

The prototype implements a benchmark to compare in-memory partition algorithms.

Running the Prototype

Please follow the instructions in the prototype/README.md file to run the prototype.

Shuffle operator implementations

The various shuffle operator implementations can be found in the include/ and src/ directory. The benchmarks and tests can be executed in the benchmark/ and test/ directory.

Overview repository

For an overview of the key findings and access to the accompanying thesis and presentation, please visit the overview repository

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This repository contains the implementations of efficient shuffle operators for streaming database systems. It includes the core partitioning logic, write-out management, and performance evaluation benchmarks. The code is designed for high-performance tuple shuffling and scalable partitioning in multithreaded environments.

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