Real-Time LSM-Trees for HTAP Workloads
Abstract
Real-time analytics systems employ hybrid data layouts in which data are stored in different formats throughout their lifecycle. Recent data are stored in a row-oriented format to serve OLTP workloads and support high insert rates, while older data are transformed to a column-oriented format for OLAP access patterns. We observe that a Log-Structured Merge (LSM) Tree is a natural fit for a lifecycle-aware storage engine due to its high write throughput and level-oriented structure, in which records propagate from one level to the next over time. To build a lifecycle-aware storage engine using an LSM-Tree, we make a crucial modification to allow different data layouts in different levels, ranging from purely row-oriented to purely column-oriented, leading to a Real-Time LSM-Tree. We give a cost model and an algorithm to design a Real-Time LSM-Tree that is suitable for a given workload, followed by an experimental evaluation of LASER - a prototype implementation of our idea built on top of the RocksDB key-value store.
Cite
@article{arxiv.2101.06801,
title = {Real-Time LSM-Trees for HTAP Workloads},
author = {Hemant Saxena and Lukasz Golab and Stratos Idreos and Ihab F. Ilyas},
journal= {arXiv preprint arXiv:2101.06801},
year = {2022}
}