Text similarity search with vector fields — Search Labs
From its beginnings as a recipe search engine, Elasticsearch was designed to provide fast and powerful full-text search. Given these roots, improving text search has been an important motivation for our ongoing work with vectors. In Elasticsearch 7.0, we introduced experimental field types for high-dimensional vectors, and now the 7.3 release brings support for using these vectors in document scor
Elastic Stackを使ったschema on writeとschema on read
オブザーバビリティも、セキュリティも、検索ソリューションも、Elasticsearchプラットフォームならすべて実現できます。
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kuromoji_tokenizer | Elasticsearch Plugins and Integrations [8.14] | Elastic
mode The tokenization mode determines how the tokenizer handles compound and unknown words. It can be set to: normal Normal segmentation, no decomposition for compounds. Example output: 関西国際空港 アブラカダブラ search Segmentation geared towards search. This includes a decompounding process for long nouns, also including the full compound token as a synonym. Example output: 関西, 関西国際空港, 国際, 空港 アブラカダブラ extend
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Nodes | Elasticsearch Guide [8.14] | Elastic
Any time that you start an instance of Elasticsearch, you are starting a node. A collection of connected nodes is called a cluster. If you are running a single node of Elasticsearch, then you have a cluster of one node. Every node in the cluster can handle HTTP and transport traffic by default. The transport layer is used exclusively for communication between nodes; the HTTP layer is used by REST
Heap size settings | Elasticsearch Guide [8.14] | Elastic
Elastic Docs ›Elasticsearch Guide [8.14] ›Deleted pages « Cluster name setting Leader index retaining operations for replication » Heap size settingsedit See Heap size settings. « Cluster name setting Leader index retaining operations for replication » Most Popular Video Get Started with Elasticsearch Video Intro to Kibana Video ELK for Logs & Metrics
Graph: Explore Connections in Elasticsearch Data | Elastic
Search and analytics, data ingestion, and visualization – all at your fingertips.
Phrase Matching | Elasticsearch: The Definitive Guide [2.x] | Elastic
In the same way that the match query is the go-to query for standard full-text search, the match_phrase query is the one you should reach for when you want to find words that are near each other: Like the match query, the match_phrase query first analyzes the query string to produce a list of terms. It then searches for all the terms, but keeps only documents that contain all of the search terms,
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dynamic | Elasticsearch Guide [8.10] | Elastic
Mapping concepts across SQL and Elasticsearch | Elasticsearch Guide [master] | Elastic
Using Kibana with Shield | Shield [2.4] | Elastic
Miscellaneous cluster settings | Elasticsearch Reference [6.1] | Elastic
term_vector | Elasticsearch Guide [8.14] | Elastic
Multiword Queries | Elasticsearch: The Definitive Guide [2.x] | Elastic
Running As a Service on Linux | Elasticsearch Guide [1.3] | Elastic