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English(EN) Transactional Data Change for Real-Time Analytics in Lakehouses

Retina框架支持湖泊数据仓库的实时交易数据变更

研究人员开发了一个名为Retina的新数据同步框架,旨在实现湖泊数据仓库的实时、交易数据变更。该系统解决了将数据从源传播到湖泊数据仓库的挑战,同时保持ACID保证并最大限度地减少资源消耗。评估表明,Retina实现了10毫秒的数据新鲜度和超过每秒320万行的吞吐量,显著优于现有的湖泊数据仓库系统和HTAP数据库。 AI

影响 该框架可以提高湖泊数据仓库中实时数据分析的效率和性能,影响数据的管理和查询方式。

排序理由 该集群描述了在arXiv上的一篇学术论文中提出的一个新颖的数据同步框架。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Retina框架支持湖泊数据仓库的实时交易数据变更

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该集群描述了在arXiv上的一篇学术论文中提出的一个新颖的数据同步框架。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Dongyang Geng, Haoqiong Bian, Zinuo Li, Haoyue Li ·

    湖仓实时分析的交易数据变更

    arXiv:2611.12169v2 Announce Type: replace-cross Abstract: Real-time data analytics has become a key demand for lakehouses. It requires propagating data changes from the data source to the lakehouse in real time, while ensuring ACID guarantees and minimizing resource consumption a…