Frequency Domain Data Encoding in Apache IoTDB
Summary: Frequency-domain encoding for Apache IoTDB using SNR-guided quantization plus a novel descending bit-packing scheme to eliminate precision and skewness waste. Sorts coefficients by magnitude to shrink dynamic bit-width; also used as lossy time-domain compression and deployed with strong space-efficiency. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Haoyu Wang (Tsinghua University)
- 2. Shaoxu Song (Tsinghua University)
BibTeX Citation
@article{wang_vldb23,
title = {{Frequency Domain Data Encoding in Apache IoTDB}},
author = {Wang, Haoyu and Song, Shaoxu},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {2},
pages = {282--290},
doi = {10.14778/3565816.3565829},
url = {https://doi.org/10.14778/3565816.3565829},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,793 | Apache IoTDB: A Time Series Database for IoT Applications | 2023 | SIGMOD | 7.1217835e-05 |
| 4,496 | Sim-Piece: Highly Accurate Piecewise Linear Approximation through Similar Segment Merging | 2023 | VLDB | 6.6622617e-05 |
| 9,156 | Apache TsFile: An IoT-native Time Series File Format | 2024 | VLDB | 5.3119028e-05 |
| 10,245 | FLEA: Frequency-based Lossless Encoding Algorithm for Periodic Time Series | 2026 | SIGMOD | 5.093636e-05 |
| 11,339 | Scalable Model-Based Management of Massive High Frequency Wind Turbine Data with ModelarDB | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 148 | Gorilla: A Fast, Scalable, In-Memory Time Series Database | 2015 | VLDB | 0.00029250767 |
| 2,023 | Decomposed Bounded Floats for Fast Compression and Queries | 2021 | VLDB | 9.2950046e-05 |
| 9,199 | On Repairing Timestamps for Regular Interval Time Series | 2022 | VLDB | 5.3058708e-05 |
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