Real-Time LSM-Trees for HTAP Workloads
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 OLA...
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Published in | 2023 IEEE 39th International Conference on Data Engineering (ICDE) pp. 1208 - 1220 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.04.2023
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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ISSN: | 2375-026X |
DOI: | 10.1109/ICDE55515.2023.00097 |