FLEA: Frequency-based Lossless Encoding Algorithm for Periodic Time Series
Summary: FLEA is a lossless compressor for periodic time series that quantizes frequency-domain coefficients while encoding time-domain residuals. An energy-based rate-optimal search and adaptive coefficient/residual partitioning deliver state-of-the-art compression with fast decoding, integrated into Apache TsFile. (summarized by gpt-5.6-luna on Jul 26 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Tianrui Xia (Tsinghua University)
- 2. Jinzhao Xiao (Tsinghua University)
- 3. Shaoxu Song (Tsinghua University)
BibTeX Citation
@inproceedings{xia_sigmod26,
title = {{FLEA: Frequency-based Lossless Encoding Algorithm for Periodic Time Series}},
author = {Xia, Tianrui and Xiao, Jinzhao and Song, Shaoxu},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802063},
url = {https://dl.acm.org/doi/10.1145/3802063},
year = {2026}
}
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 66 | The Snowflake Elastic Data Warehouse | 2016 | SIGMOD | 0.00038561587 |
| 148 | Gorilla: A Fast, Scalable, In-Memory Time Series Database | 2015 | VLDB | 0.00029250767 |
| 1,364 | Chimp: Efficient Lossless Floating Point Compression for Time Series Databases | 2022 | VLDB | 0.00011020069 |
| 2,023 | Decomposed Bounded Floats for Fast Compression and Queries | 2021 | VLDB | 9.2950046e-05 |
| 3,793 | Apache IoTDB: A Time Series Database for IoT Applications | 2023 | SIGMOD | 7.1217835e-05 |
| 4,762 | Time Series Data Encoding for Efficient Storage: A Comparative Analysis in Apache IoTDB | 2022 | VLDB | 6.519484e-05 |
| 6,556 | Hierarchical Residual Encoding for Multiresolution Time Series Compression | 2023 | SIGMOD | 5.8404094e-05 |
| 7,033 | Frequency Domain Data Encoding in Apache IoTDB | 2023 | VLDB | 5.7222622e-05 |
| 9,156 | Apache TsFile: An IoT-native Time Series File Format | 2024 | VLDB | 5.3119028e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 3,269 | ALP: Adaptive Lossless floating-Point Compression | 2023 | SIGMOD |
| 2 | 11,155 | High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation | 2024 | SIGMOD |
| 3 | 4,065 | LeCo: Lightweight Compression via Learning Serial Correlations | 2024 | SIGMOD |
| 4 | 4,496 | Sim-Piece: Highly Accurate Piecewise Linear Approximation through Similar Segment Merging | 2023 | VLDB |
| 5 | 10,258 | Kangaroo: Efficient Lossless Floating-Point Compression via Dynamic Reference Selection | 2026 | SIGMOD |
| 6 | 6,556 | Hierarchical Residual Encoding for Multiresolution Time Series Compression | 2023 | SIGMOD |
| 7 | 7,033 | Frequency Domain Data Encoding in Apache IoTDB | 2023 | VLDB |
| 8 | 8,635 | Camel: Efficient Compression of Floating-Point Time Series | 2024 | SIGMOD |
| 9 | 3,540 | Elf: Erasing-based Lossless Floating-Point Compression | 2023 | VLDB |
| 10 | 1,364 | Chimp: Efficient Lossless Floating Point Compression for Time Series Databases | 2022 | VLDB |