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A Benchmark for Learned Indexes

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Search on Sorted Data Benchmark

Build Status

SOSD is a benchmark to compare (learned) index structures on equality lookup performance over densely packed, sorted data. It comes with state-of-the-art baseline implementations to compare against and many datasets to compare on. Each dataset consists of 200 million to 800 million 32-bit or 64-bit unsigned integers.

Dependencies

On vanilla Ubuntu 20.04 LTS:

sudo apt -y update
sudo apt -y install zstd python3-pip m4 cmake clang libboost-all-dev
pip3 install --user numpy scipy
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
source $HOME/.cargo/env

Usage instructions

We provide a number of scripts to automate things. Each is located in the scripts directory, but should be executed from the repository root.

Running the benchmark

  • ./scripts/download.sh downloads and stores required data from the Internet
  • ./scripts/build_rmis.sh compiles and builds the RMIs for each dataset
    • ./scripts/download_rmis.sh will download pre-built RMIs instead, which may be faster. You'll need to run build_rmis.sh if you want to measure build times on your platform.
  • ./scripts/prepare.sh constructs query workloads and compiles the benchmark
  • ./scripts/execute.sh executes the benchmark on each workload, storing the results in results. You can use the -c flag to output a .csv file of results rather than a .txt.

Custom scripts to run different workloads based on adversarial-ml-for-learned-indexes:

  • ./scripts/execute_workload_read_only.sh executes the non-poisoned read-only workload using dynamic indexes (ALEX, B-Tree and Dynamic-PGM), storing the results in results.
  • ./scripts/execute_workload_read_heavy.sh executes the non-poisoned read-heavy workload using dynamic indexes (ALEX, B-Tree and Dynamic-PGM), storing the results in results.
  • ./scripts/execute_workload_write_heavy.sh executes the non-poisoned write-heavy workload using dynamic indexes (ALEX, B-Tree and Dynamic-PGM), storing the results in results.
  • ./scripts/execute_workload_write_only.sh executes the non-poisoned write-only workload using dynamic indexes (ALEX, B-Tree and Dynamic-PGM), storing the results in results.
  • ./scripts/execute_poisoned_workload_read_only.sh executes the poisoned read-only workload using dynamic indexes (ALEX, B-Tree and Dynamic-PGM), storing the results in results.
  • ./scripts/execute_poisoned_workload_read_heavy.sh executes the poisoned read-heavy workload using dynamic indexes (ALEX, B-Tree and Dynamic-PGM), storing the results in results.
  • ./scripts/execute_poisoned_workload_write_heavy.sh executes the poisoned write-heavy workload using dynamic indexes (ALEX, B-Tree and Dynamic-PGM), storing the results in results.
  • ./scripts/execute_poisoned_workload_write_only.sh executes the poisoned write-only workload using dynamic indexes (ALEX, B-Tree and Dynamic-PGM), storing the results in results.

Build times can be long, as we make aggressive use of templates to ensure we do not accidentally measure vtable lookup time. For development, this can be annoying: you can set USE_FAST_MODE in config.h to disable some features and get a faster build time.

Cite

If you use this benchmark in your own work, please cite us:

@article{sosd-vldb,
  author    = {Ryan Marcus and
               Andreas Kipf and
               Alexander van Renen and
               Mihail Stoian and
               Sanchit Misra and
               Alfons Kemper and
               Thomas Neumann and
               Tim Kraska},
  title     = {Benchmarking Learned Indexes},
  journal   = {Proc. {VLDB} Endow.},
  volume    = {14},
  number    = {1},
  pages     = {1--13},
  year      = {2020}
}

@article{sosd-neurips,
  title={SOSD: A Benchmark for Learned Indexes},
  author={Kipf, Andreas and Marcus, Ryan and van Renen, Alexander and Stoian, Mihail and Kemper, Alfons and Kraska, Tim and Neumann, Thomas},
  journal={NeurIPS Workshop on Machine Learning for Systems},
  year={2019}
}

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