QuerySplit and Cardinality Estimation Errors
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Questions and Answers

What is the lesson learned for future improvements in query optimization?

  • Mediocre optimizers are suitable for handling heavy subqueries
  • Heavy subqueries should be executed first for better performance
  • Using alternative re-optimization algorithms is the best approach
  • Fine-grained subqueries are preferred for re-optimization to avoid cardinality estimation errors (correct)
  • What percentage of the queries belong to the first two categories where QuerySplit outperforms alternative re-optimization algorithms?

  • 40%
  • 70% (correct)
  • 50%
  • 30%
  • What is a significant finding about the 'Worse' category of queries?

  • The 'Worse' category has a large effect on the overall benchmark performance
  • The 'Worse' category is the most frequent type of query
  • The 'Worse' category contains a majority of the queries
  • The 'Worse' category has minimal effect on the overall benchmark performance (correct)
  • In the example shown in Figure 21(a), what does the join graph depict?

    <p>The execution plan for QuerySplit and IEF</p> Signup and view all the answers

    What mistake does PostgreSQL’s optimizer make in estimating the cardinality of S1?

    <p>It underestimates the cardinality of S1</p> Signup and view all the answers

    Which algorithm chose to execute S2 first instead of S1?

    <p>IEF</p> Signup and view all the answers

    What is the main advantage of QuerySplit compared to robust query processing baselines?

    <p>It is more efficient in handling cardinality estimation errors</p> Signup and view all the answers

    Why do learned cardinality estimation algorithms like NeuroCard and DeepDB achieve limited performance improvement?

    <p>They don't handle string columns efficiently</p> Signup and view all the answers

    What is the likely reason re-optimization is more effective and efficient than refining cardinality estimation in improving query performance?

    <p>It leads to query plans that are closer to optimal</p> Signup and view all the answers

    What is the reason behind USE having the same performance in both index configurations?

    <p>It disables nest-loop join, thus ignoring indexes in its query planning</p> Signup and view all the answers

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