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New research uses data provenance for query template identification

By PulseAugur Editorial · [1 sources] ·

A new research paper proposes a novel method for identifying query templates by analyzing data provenance. This approach constructs query-level profiles that capture data dependencies and structural properties, summarizing them into numerical features called Provenance Structural Descriptors (PSD). Experiments using TPC-DS query templates demonstrated that these provenance footprints can accurately identify query templates, with accuracy improving as more historical data becomes available. AI

RANK_REASON The cluster contains a research paper published on arXiv detailing a novel approach to query template identification using data provenance. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New research uses data provenance for query template identification

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The cluster contains a research paper published on arXiv detailing a novel approach to query template identification using data provenance. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Paulo Pintor, Rog\'erio Costa, Jos\'e Moreira ·

    Data Provenance Aggregation and Structural Descriptors for Query-Template Identification

    arXiv:2610.22705v1 Announce Type: cross Abstract: Runtime query similarity identification supports several activities, including workload analysis, identifying recurring behaviour, auditing, debugging, and anomaly detection. Existing methods for evaluating query similarity mostly…

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