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PREDICTING EXECUTION TIMES OF CONCURRENT QUERIES

机译:预测并发查询的执行时间

摘要

Example embodiments relate to predicting execution times of concurrent queries. In example embodiments, historical data is iteratively generated for a machine learning model by varying a concurrency level of query executions in a database, determining a query execution plan for a pending concurrent query, extracting query features from the query execution plan, and executing the pending concurrent query to determine a query execution time. The machine learning model may then be created based on the query features, variation in the concurrency level, and the query execution time. The machine learning model is used to generate an execution schedule for production queries, where the execution schedule satisfies service level agreements of the production queries.
机译:示例实施例涉及预测并发查询的执行时间。在示例实施例中,通过改变数据库中查询执行的并发级别,确定未决并发查询的查询执行计划,从查询执行计划中提取查询特征并执行未决,来为机器学习模型迭代地生成历史数据。并发查询以确定查询的执行时间。然后可以基于查询特征,并发级别的变化以及查询执行时间来创建机器学习模型。机器学习模型用于生成生产查询的执行计划,其中执行计划满足生产查询的服务级别协议。

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