테이블이 자주 업데이트되거나 삽입되는 경향이 있다면 색인의 재현율 정확도를 높이기 위해 주기적으로 기존 ScaNN 색인을 다시 색인화하는 것이 좋습니다. 색인 측정항목을 모니터링하여 색인이 빌드된 이후 벡터 분포 또는 벡터 변형의 변경사항을 확인한 다음 그에 따라 색인을 다시 생성할 수 있습니다.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-09-05(UTC)"],[[["\u003cp\u003eVector indexes may require maintenance to adapt to data changes and maintain search accuracy.\u003c/p\u003e\n"],["\u003cp\u003eReindexing is recommended for tables with frequent updates or insertions to improve the recall accuracy of the index.\u003c/p\u003e\n"],["\u003cp\u003eYou can monitor index metrics to identify changes in vector distributions or mutations that might necessitate reindexing.\u003c/p\u003e\n"],["\u003cp\u003eYou can manually rebuild a vector index using the \u003ccode\u003eREINDEX INDEX CONCURRENTLY\u003c/code\u003e command, providing the index name.\u003c/p\u003e\n"],["\u003cp\u003eIndex names must be unique per table within the database.\u003c/p\u003e\n"]]],[],null,["Select a documentation version: Current (16.8.0)keyboard_arrow_down\n\n- [Current (16.8.0)](/alloydb/omni/current/docs/ai/maintain-vector-indexes)\n- [16.8.0](/alloydb/omni/16.8.0/docs/ai/maintain-vector-indexes)\n- [16.3.0](/alloydb/omni/16.3.0/docs/ai/maintain-vector-indexes)\n- [15.12.0](/alloydb/omni/15.12.0/docs/ai/maintain-vector-indexes)\n- [15.7.1](/alloydb/omni/15.7.1/docs/ai/maintain-vector-indexes)\n- [15.7.0](/alloydb/omni/15.7.0/docs/ai/maintain-vector-indexes)\n\n\u003cbr /\u003e\n\nThis document explains different options that you can use to maintain vector indexes. You might want to maintain indexes to ensure that your indexes adapt to the changes in data that might impact accuracy of your search results. As your dataset grows, use the strategies in the following sections to avoid degradation in query performance.\n\n\u003cbr /\u003e\n\nView vector index metrics\n\nIf your table is prone to frequent updates or insertions, then we recommend\nperiodically [reindexing the existing ScaNN index](#manually-rebuild-index)\nin order to improve the recall accuracy for your index. You can monitor\nindex metrics to view changes in vector distributions or vector mutations since\nthe index was built, and then reindex accordingly.\n\nFor more information about metrics, see [View Vector index metrics](/alloydb/omni/current/docs/reference/vector-index-metrics).\n\nManually rebuild your index\n\nYou can manually rebuild your index if you want to\nrebuild it with the configurations you specified when it was created.\n\nTo manually rebuild your index, run the following command: \n\n REINDEX INDEX CONCURRENTLY \u003cvar translate=\"no\"\u003e\u003cspan class=\"devsite-syntax-n\"\u003eINDEX_NAME\u003c/span\u003e\u003c/var\u003e;\n\nReplace \u003cvar translate=\"no\"\u003eINDEX_NAME\u003c/var\u003e with the name of the index you want to\nrebuild---for example, `my-scann-index`. The index names are shared\nacross your database. Ensure that each index name is unique to each\ntable in your database.\n\nFor more information about reindexing in PostgreSQL, see\n[REINDEX](https://www.postgresql.org/docs/15/sql-reindex.html).\n\nWhat's next\n\n- [Vector index metrics](/alloydb/omni/current/docs/reference/vector-index-metrics)\n- [Optimize vector query performance for ScaNN](/alloydb/omni/current/docs/ai/scann-vector-query-perf-overview)"]]
