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k-NN settings

The k-NN plugin adds several new cluster settings.

Cluster settings

Setting Default Description
knn.algo_param.index_thread_qty 1 The number of threads used for native library index creation. Keeping this value low reduces the CPU impact of the k-NN plugin, but also reduces indexing performance.
knn.cache.item.expiry.enabled false Whether to remove native library indexes that have not been accessed for a certain duration from memory.
knn.cache.item.expiry.minutes 3h If enabled, the idle time before removing a native library index from memory.
knn.circuit_breaker.unset.percentage 75% The native memory usage threshold for the circuit breaker. Memory usage must be below this percentage of knn.memory.circuit_breaker.limit for knn.circuit_breaker.triggered to remain false.
knn.circuit_breaker.triggered false True when memory usage exceeds the knn.circuit_breaker.unset.percentage value.
knn.memory.circuit_breaker.limit 50% The native memory limit for native library indexes. At the default value, if a machine has 100 GB of memory and the JVM uses 32 GB, the k-NN plugin uses 50% of the remaining 68 GB (34 GB). If memory usage exceeds this value, k-NN removes the least recently used native library indexes.
knn.memory.circuit_breaker.enabled true Whether to enable the k-NN memory circuit breaker.
knn.plugin.enabled true Enables or disables the k-NN plugin.
knn.model.index.number_of_shards 1 The number of shards to use for the model system index, the OpenSearch index that stores the models used for Approximate Nearest Neighbor (ANN) search.
knn.model.index.number_of_replicas 1 The number of replica shards to use for the model system index. Generally, in a multi-node cluster, this should be at least 1 to increase stability.
knn.advanced.filtered_exact_search_threshold null The threshold value for the filtered IDs that is used to switch to exact search during filtered ANN search. If the number of filtered IDs in a segment is less than this setting’s value, exact search will be performed on the filtered IDs.
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