不爲也 比不能也

Text vs. keywordWith the release of Elasticsearch 5.0 coming closer, it is time to introduce one of the release highlights of this upcoming release: the removal of the string type. The background for this change is that we think the string type is confusing: Elasticsearch has two very different ways to search strings. You can either search whole values, that we often refer to as keyword search, ..

Give memory to the filesystem cache Elasticsearch heavily relies on the filesystem cache in order to make search fast. In general, you should make sure that at least half the available memory goes to the filesystem cache so that Elasticsearch can keep hot regions of the index in physical memory.Elasticsearch는 search 속도를 빠르게 하기 위해, filesystem cache에 많이 의존한다. 일반적으로, Elasticsearch가 index 중 많이 사용하는 ..

string fields replaced by text/keyword fieldseditThe string field datatype has been replaced by the text field for full text analyzed content, and the keyword field for not-analyzed exact string values. For backwards compatibility purposes, during the 5.x series:string field datatype이 full text analyzed 내용에 대해서는 text field로, not-analyzed exact string 값에 대해서는 keyword field로 변경되었다. 이전 version과의 호환..

Significant terms on numeric fieldseditNumeric fields have been refactored to use a different data structure that performs better for range queries. However, since this data structure does not record document frequencies, numeric fields need to fall back to running queries in order to estimate the number of matching documents in the background set, which may incur a performance degradation.numer..

While Elasticsearch comes with a number of analyzers available out of the box, the real power comes from the ability to create your own custom analyzers by combining character filters, tokenizers, and token filters in a configuration that suits your particular data.Elasticsearch가 수많은 내장 analyzer를 제공하지만, 진정한 힘은 자신의 특별한 데이터에 적합한 설정에서, character filters, tokenizers 그리고 token filters를 조합하여, 자신만의 사용자..