不爲也 比不能也

Here are some great slides from our Core Elasticsearch: Operations course that help explain the concept. We'd recommend that you take the full course to understand this even better, but I'll provide an overview from our training here:다음은 Core Elasticsearch: Operations 과정(개념을 설명하는)에서 제공하는 몇 개의 멋진 slide이다. 이 내용을 더 잘 이해하기 위해서는 전체 과정을 수강하는 것이 좋겠지만, 여기에서 과정의 개요를 제공한다.Shard allocation is the process o..

A keen observer will notice that all the queries so far in this book have operated on whole terms. To match something, the smallest unit had to be a single term. You can find only terms that exist in the inverted index.눈썰미가 좋은 독자라면, 지금까지 이 책의 모든 query는 전체 단어를 기준으로 동작된다는 것을 알아차렸을 것이다. 어떤 것과 일치한다는 것은, 가장 작은 단위가 단일 단어이어야 한다. inverted index에 존재하는 단어만을 검색할 수 있다.But what happens if you want to match p..

To find all postcodes beginning with W1, we could use a simple prefix query:W1 로 시작하는 우편번호를 검색하기 위해, 간단한 prefix query를 사용할 수 있다.GET /my_index/address/_search { "query": { "prefix": { "postcode": "W1" } } }COPY AS CURLVIEW IN SENSE The prefix query is a low-level query that works at the term level. It doesn’t analyze the query string before searching. It assumes that you have passed it the exact ..

As we have said before, "You can find only terms that exist in the inverted index". Although the prefix, wildcard, and regexp queries demonstrated that that is not strictly true, it is true that doing a single-term lookup is much faster than iterating through the terms list to find matching terms on the fly. Preparing your data for partial matching ahead of time will increase your search perform..

Aggregations work via a data structure known as doc values (briefly introduced in Doc Values Intro).Doc values are what make aggregations fast, efficient and memory-friendly, so it is useful to understand how they work.aggregation은 doc values (Doc Values Intro에서 간단히 소개된)로 알려진 데이터 구조를 통해, 동작한다.doc values는 aggregation을 빠르게, 효율적으로, 메모리 친화적으로 만든다. 때문에, 그것이 동작하는 방법을 이해하는 것은 중요하다.Doc values exists bec..