不爲也 比不能也

Elasticsearch is a very versatile platform, that supports a variety of use cases, and provides great flexibility around data organisation and replication strategies. This flexibility can however sometimes make it hard to determine up-front how to best organize your data into indices and shards, especially if you are new to the Elastic Stack. While suboptimal choices will not necessarily cause pr..

In Elasticsearch 6.0 we’re introducing a new feature called Index Sorting. Users can now optimize Elasticsearch indexes to store documents on disk in a specific order. We’re very excited for Index Sorting, as it’s another useful tool in optimizing Elasticsearch performance! Elasticsearch 6.0 에서 Index Sorting 이라 불리는 새로운 기능을 도입하였다. 이제 사용자는 document를 disk에 특정 순서로 저장하여 Elasticsearch index를 최적화할 수 있다..

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..

UPDATE: This article refers to our hosted Elasticsearch offering by an older name, Found. Please note that Found is now known as Elastic Cloud.이 게시물은 기존에 Found라는 이름으로 제공된 Elasticsearch 서비스에 관한 것이다. Found은 이제 Elasticsearch Cloud로 알려져 있다.The previous article in this series, Elasticsearch from the Bottom Up, covered essential data structures within a single shard. In this article, we will look at t..

Running Elasticsearch 2.0? Check out this updated post about performance considerations for Elasticsearch 2.0 indexing. Elasticsearch 2.0을 운영 중이라면? Elasticsearch 2.0 indexing에 대한 성능 고려 사항에서 update된 post를 확인해 보자. Elasticsearch users have delightfully diverse use cases, ranging from appending tiny log-line documents to indexing Web-scale collections of large documents, and maximizing indexing thro..

UPDATE: This article refers to our hosted Elasticsearch offering by an older name, Found. Please note that Found is now known as Elastic Cloud.이 게시물은 기존에 Found라는 이름으로 제공된 Elasticsearch 서비스에 관한 것이다. Found은 이제 Elasticsearch Cloud로 알려져 있다.In this article series, we look at Elasticsearch from a new perspective. We'll start at the "bottom" (or close enough!) of the many abstraction levels, and gradua..

The next problem that needed to be solved was how to make an inverted index updatable without losing the benefits of immutability? The answer turned out to be: use more than one index.해결해야 할 다음 문제는, 불변성의 장점을 잃지 않고, inverted index를 업데이트 가능하도록 만드는 방법이다. 답은 하나 이상의 index를 사용하는 것이다.Instead of rewriting the whole inverted index, add new supplementary indices to reflect more-recent changes. Each invert..

With the development of per-segment search, the delay between indexing a document and making it visible to search dropped dramatically. New documents could be made searchable within minutes, but that still isn’t fast enough.segment별 검색의 개발로, document의 색인과 검색 시에 보이도록 하는 것 사이에 지연이 크게 발생한다. 새로운 document는 수분 내에 검색이 가능하지만, 아직 충분히 빠르지는 않다.The bottleneck is the disk. Commiting a new segment to disk req..

With the automatic refresh process creating a new segment every second, it doesn’t take long for the number of segments to explode. Having too many segments is a problem. Each segment consumes file handles, memory, and CPU cycles. More important, every search request has to check every segment in turn; the more segments there are, the slower the search will be.매초마다 자동 refresh 프로세스가 새로운 segment를 ..

If you are in an indexing-heavy environment, such as indexing infrastructure logs, you may be willing to sacrifice some search performance for faster indexing rates. In these scenarios, searches tend to be relatively rare and performed by people internal to your organization. They are willing to wait several seconds for a search, as opposed to a consumer facing a search that must return in milli..