The AHA-Tree: An Adaptive Index for HTAP Workloads
<|reference_start|>The AHA-Tree: An Adaptive Index for HTAP Workloads: In this demo, we realize data indexes that can morph from being write-optimized at times to being read-optimized at other times nonstop with zero-down time during the workload transitioning. These data indexes are useful for HTAP systems (Hybrid Transactional and Analytical Processing Systems), where transactional workloads are write-heavy while analytical workloads are read-heavy. Traditional indexes, e.g., B+-tree and LSM-Tree, although optimized for one kind of workload, cannot perform equally well under all workloads. To migrate from the write-optimized LSM-Tree to a read-optimized B+-tree is costly and mandates some system down time to reorganize data. We design adaptive indexes that can dynamically morph from a pure LSM-tree to a pure buffered B-tree back and forth, and has interesting states in-between. There are two challenges: allowing concurrent operations and avoiding system down time. This demo benchmarks the proposed AHA-Tree index under dynamic workloads and shows how the index evolves from one state to another without blocking.<|reference_end|>
@article{xing2024the,
    title={The AHA-Tree: An Adaptive Index for HTAP Workloads},
    author={Lu Xing, Walid G. Aref},
    journal={arXiv preprint arXiv:2406.08746},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.08746},
    primaryClass={cs.DB}
}