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  • Analyzing the Impact of Cardinality Estimation on Execution Plans in . . .
    Our empirical study broadens the scope of prior studies in significant ways First, we include complex SQL queries containing group-by, aggregation, outer joins and sub-queries from real-world workloads and indus-try benchmarks We evaluate on both row-oriented and column-oriented physical designs
  • Analyzing the Impact of Cardinality Estimation on Execution Plans in . . .
    Cardinality estimation is widely believed to be one of the most important causes of poor query plans Prior studies evaluate the impact of cardinality estimation on plan quality on a set of Select-Project-Join queries on PostgreSQL DBMS
  • Cardinality Estimation (SQL Server) - SQL Server | Microsoft Learn
    Cardinality estimation (CE) in SQL Server is derived primarily from histograms that are created when indexes or statistics are created, either manually or automatically Sometimes, SQL Server also uses constraint information and logical rewrites of queries to determine cardinality
  • Cardinality Estimation Benchmark | Learned Systems
    In order to build large workloads to evaluate the impact of cardinality estimators, we introduce a novel programmatic templating scheme We use it to generate over 15K challenging queries on two databases (IMDb and StackExchange)
  • An Empirical Analysis of Deep Learning for Cardinality Estimation
    We find that simple deep learning models can learn cardinality estimations across a variety of datasets (reducing the error by 72% - 98% on average compared to PostgreSQL) In addition, we empirically evaluate the impact of injecting cardinality estimates produced by deep learning models into the PostgreSQL optimizer
  • Cost-Guided Cardinality Estimation: Focus Where it Matters
    We propose a new technique, called cost-guided cardinality estimation, which, at training time, emphasizes predictions that matter most to query plans Our method relies on a new metric, Plan-Error, that captures the impact of cardinality estimates on the optimized plans generated by a DBMS
  • Statistics and Cardinality Estimation in SQL Server
    In SQL Server, query optimization and execution are heavily influenced by statistics and cardinality estimation Understanding how these components work is crucial for database administrators and developers aiming to improve query performance
  • Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation - VLDB
    Cardinality estimation (CardEst) plays a significant role in gener-ating high-quality query plans for a query optimizer in DBMS In the last decade, an increasing number of advanced CardEst meth-ods (especially ML-based) have been proposed with outstanding estimation accuracy and inference latency
  • Understanding Cardinality Estimation | by nizami khalilbayli - Medium
    One of the most important aspects influencing cardinality estimation is physical design of a database Indexes and their count highly impact query optimizer for choosing the best plan
  • ASM in Action: Fast and Practical Learned Cardinality Estimation
    Learned cardinality estimators have shown remarkable improvements in estimation accuracy by exploiting machine learning techniques, yet suffer from inefficiency or sub-optimal query plans when deployed in query optimizers





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