Should I Hide My Duck in the Lake?
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866915980481921024 |
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| author | Dann, Jonas Alonso, Gustavo |
| author_facet | Dann, Jonas Alonso, Gustavo |
| contents | Data lakes spend a significant fraction of query execution time on scanning data from remote, disaggregated storage. Decoding alone accounts for 46% of runtime when running TPC-H directly on Parquet files. To address this bottleneck, we propose a vision for a data processing SmartNIC for the cloud that sits on the network datapath of compute nodes to offload decoding and pushed-down operators, effectively hiding the cost of parsing raw files. Our experimental estimations with DuckDB suggest that by operating directly on pre-filtered data, as delivered by a SmartNIC, we can significantly increase query processing performance and can still match query throughput of traditional setups with smaller, less expensive CPUs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_18775 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Should I Hide My Duck in the Lake? Dann, Jonas Alonso, Gustavo Databases Data lakes spend a significant fraction of query execution time on scanning data from remote, disaggregated storage. Decoding alone accounts for 46% of runtime when running TPC-H directly on Parquet files. To address this bottleneck, we propose a vision for a data processing SmartNIC for the cloud that sits on the network datapath of compute nodes to offload decoding and pushed-down operators, effectively hiding the cost of parsing raw files. Our experimental estimations with DuckDB suggest that by operating directly on pre-filtered data, as delivered by a SmartNIC, we can significantly increase query processing performance and can still match query throughput of traditional setups with smaller, less expensive CPUs. |
| title | Should I Hide My Duck in the Lake? |
| topic | Databases |
| url | https://arxiv.org/abs/2602.18775 |