From 38b5ea9066a8eae29222e26595957d022d2de26c Mon Sep 17 00:00:00 2001 From: Robert Schulze Date: Thu, 12 Sep 2024 12:43:27 +0000 Subject: [PATCH] Fix docs --- docs/en/engines/table-engines/mergetree-family/annindexes.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/en/engines/table-engines/mergetree-family/annindexes.md b/docs/en/engines/table-engines/mergetree-family/annindexes.md index b73700c40f4..f507e2b9f86 100644 --- a/docs/en/engines/table-engines/mergetree-family/annindexes.md +++ b/docs/en/engines/table-engines/mergetree-family/annindexes.md @@ -109,7 +109,7 @@ The vector similarity index currently does not work with per-table, non-default Vector index creation is known to be slow. To speed the process up, index creation can be parallelized. The maximum number of threads can be configured using server configuration -setting [max_build_vector_similarity_index_thread_pool_size](server-configuration-parameters/settings.md#server_configuration_parameters_max_build_vector_similarity_index_thread_pool_size). +setting [max_build_vector_similarity_index_thread_pool_size](../../../operations/server-configuration-parameters/settings.md#server_configuration_parameters_max_build_vector_similarity_index_thread_pool_size). ANN indexes are built during column insertion and merge. As a result, `INSERT` and `OPTIMIZE` statements will be slower than for ordinary tables. ANNIndexes are ideally used only with immutable or rarely changed data, respectively when are far more read requests than write