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Ortiz et al., 2019 - Google Patents

An empirical analysis of deep learning for cardinality estimation

Ortiz et al., 2019

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Document ID
11397446675908808231
Author
Ortiz J
Balazinska M
Gehrke J
Keerthi S
Publication year
Publication venue
arXiv preprint arXiv:1905.06425

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We implement and evaluate deep learning for cardinality estimation by studying the accuracy, space and time trade-offs across several architectures. We find that simple deep learning models can learn cardinality estimations across a variety of datasets (reducing the …
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Classifications

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    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386—Retrieval requests
    • G06F17/30424—Query processing
    • G06F17/30533—Other types of queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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