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Styx: Transactional Stateful Functions on Streaming Dataflows

This repository contains the codebase of Styx described in: https://arxiv.org/abs/2312.06893.

Cite Styx
@misc{psarakis2024styx,
      title={Styx: Transactional Stateful Functions on Streaming Dataflows}, 
      author={Kyriakos Psarakis and George Siachamis and George Christodoulou and Marios Fragkoulis and Asterios Katsifodimos},
      year={2024},
      eprint={2312.06893},
      archivePrefix={arXiv},
      primaryClass={cs.DC}
}

Preliminaries

This project requires an environment with python 3.12 installed. Please install the styx-package and all the requirements of the coordinator and the worker modules as well as pandas, numpy and matplotlib.

You can use the following commands:

pip install styx-package/.  
pip install -r coordinator/requirements.txt
pip install -r worker/requirements.txt
pip install pandas numpy matplotlib

Folder structure

  • coordinator Styx coordinator.

  • demo The YCSB-T, Deathstar, TPC-C and scalability benchmarks we used for the experiments.

  • env env folder for the docker-compose Minio container.

  • styx-package The Styx framework Python package.

  • tests Tests for the worker components of Styx.

  • worker Styx worker.

Running experiments

In the scripts directory, we provide a number of different scripts that can be used to run the experiments of Styx.

Reproduce paper results

From the projects root:

./scripts/run_batch_experiments.sh
./scripts/run_scalability_experiments.sh

Run single experiment

To run a single experiment:

./scripts/run_experiment.sh [WORKLOAD_NAME] [INPUT_RATE] [N_KEYS] [N_PART] [ZIPF_CONST] [CLIENT_THREADS] [TOTAL_TIME] [SAVING_DIR] [WARMUP_SECONDS] [EPOCH_SIZE]

e.g. to run the YCSB-T workload with 1000000 keys at 1000 TPS, 4 partitions, 0.0 zipfian coefficient, 1 client thread, for 60 seconds with 10 second warmup time, a batch size of 1000 and save the results in the results folder: ./scripts/run_experiment.sh ycsbt 1000 1000000 4 0.0 1 60 results 10 1000

The options for [WORKLOAD_NAME] are ycsbt for YCSB-T, dhr for deathstar hotel reservation, dmr for deathstar movie review and tpcc for TPC-C. [ZIPF_CONST] only affects the ycsbt workload.

Note: If you want to change the number of CPUs per worker you have to go to the docker-compose.yml and change the WORKER_THREADS value + the resources along with the /scripts/start_styx_cluster.sh $threads_per_worker. In the paper experiments we used 8.

Alternative way of execution

Alternatively, you can also handle the individual components of Styx as follows. First, you need to deploy the Kafka cluster and the MinIO storage. And use any of the clients in the /demo folder.

Kafka

To run kafka: docker compose -f docker-compose-kafka.yml up

To clear kafka: docker compose -f docker-compose-kafka.yml down --volumes

MinIO

To run MinIO: docker-compose up -f docker-compose-minio.yml up

To clear MinIO: docker-compose -f docker-compose-minio.yml down --volumes

Then, you can start the Styx engine and specify the desired scale.

Styx Engine

To run the SE: docker-compose up --build --scale worker=4

To clear the SE: docker-compose down --volumes