不爲也 比不能也

In Elasticsearch 6.0, we released a new feature called index sorting. Read up more on this on the linked blog, but in short, what this does is to take the documents at index time and sort them by a key or set of keys in an order of your choosing. This has a few advantages that we’ve talked about:Elasticsearch 6.0 에서 index sorting이라는 새로운 기능이 출시되었다. link된 게시물에서 이에 대해 자세히 읽어 보자. 간단히 말하자면, index시에 d..

When dealing with numbers in this chapter, we have so far searched for only exact numbers. In practice, filtering on ranges is often more useful. For example, you might want to find all products with a price greater than $20 and less than $40.이 장에서 number를 다룰 때, 지금까지는 정확한 수만을 검색했었다. 실제로는, 범위를 filtering하는 것이 때때로 더 유용하다. 예를 들어, 가격이 $20보다 크고 $40보다 작은 모든 상품을 찾아보자.In SQL terms, a range can be express..

Life is easy if all your data fits on a single machine. Classic algorithms taught in CS201 will be sufficient for all your needs. But if all your data fits on a single machine, there would be no need for distributed software like Elasticsearch at all. But once you start distributing data, algorithm selection needs to be made carefully.모든 데이터가 단일 시스템으로 충분하다면, 참 쉬울 것이다. CS201에서 배운 고전적인 알고리즘으로, 모든 ..

The first approximate aggregation provided by Elasticsearch is the cardinality metric. This provides the cardinality of a field, also called a distinct or unique count. You may be familiar with the SQL version:Elasticsearch에서 제공되는, 첫 번째 approximate aggregation은 cardinality metric이다. 이것은 고유한(distinct) 또는 유일한(unique) 값의 수라고 불리기도 하는, filed의 cardinality(기수)를 제공한다. 아래 SQL 버전에 익숙할 것이다.SELECT COUNT(DIS..

Some aggregations, such as the terms bucket, operate on string fields. And string fields may be either analyzed or not_analyzed, which raises the question: how does analysis affect aggregations?terms bucket 같은 어떤 aggregation은 string field에서 동작한다. 그리고, string field는 analyzed 나 not_analyzed 일 것이다. 그렇다면 질문이 있을 것이다. 분석은 aggregation에 어떤 영향을 미치는가?The answer is "a lot," for two reasons: analysis affect..

This section covered a lot of ground, and a lot of deeply technical issues. Aggregations bring a power and flexibility to Elasticsearch that is hard to overstate. The ability to nest buckets and metrics, to quickly approximate cardinality and percentiles, to find statistical anomalies in your data, all while operating on near-real-time data and in parallel to full-text search—these are game-chan..