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13 | 13 | k-NN algorithm, <filename>aqo</filename> improves cardinality estimation, which can optimize execution plans and, consequently, speed up query execution. |
14 | 14 | </para> |
15 | 15 | <para>The <filename>aqo</filename> module can collect statistics on all the executed |
16 | | - queries and classify it according to the query type. If the |
| 16 | + queries, excluding the queries that access system relations. |
| 17 | + The collected statistics is classified by query type. If the |
17 | 18 | queries differ in their constants only, they belong to the same |
18 | 19 | type. For each type, <filename>aqo</filename> stores the cardinality quality, planning |
19 | 20 | time, execution time, and execution statistics for machine learning. Based on this data, <filename>aqo</filename> builds a new query plan and uses it for the next query of the same type. |
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