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arXiv · 2609.11148

OmniTable: A Unified Wide-Table System for Petabyte-Scale LLM Data Curation and Exploration

Yuzhuo Fu·Xiangchun Wang·Chao Huang·Liyi Wang·Binwei Zeng·Yuhan Wang·Taotao Nie·Dongke Hu·Wang Hong·Jiayi Wang·Wenwen Cui·Zhuyan Zhou·Yushun Guo·Yuhan Xing·Jiaxin Lian·Peng Lin·Qing Cui·Wenhui Shi·Jun Zhou
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Abstract

Data curation is a critical bottleneck in industrial-grade LLM development, where petabyte-scale unstructured corpora are scattered across hundreds of physical tables, feature engineering relies on manual, table-centric pipeline orchestration, and data lineage is largely absent. We present OmniTable as an architecture blueprint for a unified wide-table layer built on Logical Unification, Physical Separation, targeting petabyte-scale LLM data curation and exploration. OmniTable makes four contributions: (1) a unified wide-table abstraction that consolidates multi-source heterogeneous data and thousands of derived features under a single logical schema via logical-physical mapping; (2) declarative feature lifecycle management that automates dependency resolution, execution planning, operator fusion, and lineage tracking, replacing manual pipeline orchestration with a "declare-and-execute" paradigm; (3) an adaptive execution engine with autonomous governance that achieves stable PB-scale feature backfill through heterogeneous compute routing (CPU/GPU), adaptive tuning, UDF-level fault tolerance, and automated storage layout optimization; and (4) hybrid-accelerated data exploration combining a global ID index, transparent OLAP offloading, and background materialized views to deliver second-level point lookups and filtered exports exceeding 20 TB/hour. In production, OmniTable manages over 35 PB of training data across web, code, PDF, and SFT domains, reducing the human-in-the-loop curation cycle from approximately 14 days to approximately 2.5 days (5.6x over the pre-OmniTable production workflow), with consistent feature versioning, auditable lineage, and minimal manual intervention.

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Yuzhuo Fu, Xiangchun Wang, Chao Huang, Liyi Wang, Binwei Zeng, Yuhan Wang, Taotao Nie, Dongke Hu, Wang Hong, Jiayi Wang, Wenwen Cui, Zhuyan Zhou, Yushun Guo, Yuhan Xing, Jiaxin Lian, Peng Lin, Qing Cui, Wenhui Shi, Jun Zhou. 2026-09-10. OmniTable: A Unified Wide-Table System for Petabyte-Scale LLM Data Curation and Exploration. https://doi.org/10.14778/3827998.3828032

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