不爲也 比不能也

With 5.0 on the horizon, a number of query types deprecated in 2.x will be removed. Many of those are replaced by functionality of the bool query, so here’s a quick guide on how to move away from filtered queries; and, or, not queries; and a general look into how to parse boolean logic with the bool query.5.0 이 출시되면서, 2.x 에서 deprecate된 많은 query 유형이 제거된다. 그들 중 많은 부분이 bool query 기능으로 대체된다. 그래서, 여기..

The fact that Elasticsearch operates with shards and replicas adds challenges when it comes to having good scoring. Elasticsearch가 shard, relpica와 함께 동작한다는 사실은 score 계산에 어려움이 있다는 것을 의미한다. Scores are not reproducible Say the same user runs the same request twice in a row and documents do not come back in the same order both times, this is a pretty bad experience isn’t it? Unfortunately this is so..

The searches so far have been simple: single names, filtered by age. Let’s try a more advanced, full-text search—a task that traditional databases would really struggle with.지금까지의 검색은 이름 하나만을 검색하고, 나이를 filtering하는 단순한 검색이었다. 기존의 DB와 진정으로 겨뤄볼 수 있는, 더 고급스러운 full-text 검색을 해 보자.We are going to search for all employees who enjoy rock climbing:rock climbing을 즐겨 하는 모든 직원을 찾아보자.GET /megacorp/employee/_s..

The query DSL is a flexible, expressive search language that Elasticsearch uses to expose most of the power of Lucene through a simple JSON interface. It is what you should be using to write your queries in production. It makes your queries more flexible, more precise, easier to read, and easier to debug.query DSL은 간단한 JSON interface를 이용해, Lucene을 100% 활용하기 위해, Elasticsearch가 사용하는 유연하고, 표현력 있는 검..

The DSL used by Elasticsearch has a single set of components called queries, which can be mixed and matched in endless combinations. This single set of components can be used in two contexts: filtering context and query context.elasticsearch에서 사용되는 DSL은"DSL (Domain Specific Language)"query라 불리는 component의 단일 집합을 가지는데, 이것은 무한한 조합으로 섞이고 일치될 수 있다. 이 단일 component 집합은 두 개의 context, filtering과 query c..

Real world search requests are never simple; they search multiple fields with various input text, and filter based on an array of criteria. To build sophisticated search, you will need a way to combine multiple queries together into a single search request.현실에서 검색 request는 결코 간단하지 않다. 다양한 입력 문자열과 여러 조건의 배열을 기반으로 한 filter를 가지고 다수의 field를 검색한다. 정교한 검색을 위해, 하나의 검색 request에 다수의 query를 함께 조합해야 한다.To ..

In order to sort by relevance, we need to represent relevance as a value. In Elasticsearch, the relevance score is represented by the floating-point number returned in the search results as the _score, so the default sort order is _score descending.relevance로 정렬하기 위해, relevance를 값으로 표시해야 한다. Elasticsearch에서 relevance score 는 _score 로, 검색 결과에 반환되는, 부동 소수점 숫자로 표시된다. 기본 정렬 순서는 _score 의 내림차순이다.Somet..

We’ve mentioned that, by default, results are returned in descending order of relevance. But what is relevance? How is it calculated?기본적으로 결과는 relevance를 기준으로, 내림차순으로 반환된다고 언급한 바 있다. 그런데, relevance가 무엇이고, 어떻게 계산되는가?The relevance score of each document is represented by a positive floating-point number called the _score. The higher the _score, the more relevant the document.각 document의 relevance ..

In Getting Started we covered the basic tools in just enough detail to allow you to start searching your data with Elasticsearch. It won’t take long, though, before you find that you want more: more flexibility when matching user queries, more-accurate ranking of results, more-specific searches to cover different problem domains.Getting Started에서 Elasticsearch로 데이터 검색을 시작할 수 있는, 충분히 자세한 기본적인 too..

While all queries perform some sort of relevance calculation, not all queries have an analysis phase.Besides specialized queries like the bool or function_score queries, which don’t operate on text at all, textual queries can be broken down into two families:모든 query가 relevance 연산의 일종을 수행하지만, 모든 query가 analysis 절을 가지지는 않는다. 텍스트를 전혀 다루지 않는, bool 이나 function-score query 같은 특별한 query 이외에, 텍스트를 다루는 ..