不爲也 比不能也

Elasticsearch supports a wide range of use-cases across our user base, and more and more of these rely on fast indexing to quickly get large amounts of data into Elasticsearch. Even though Elasticsearch is fast and index performance is continually improved, it is still possible to overwhelm it. At that point you typically see parts of bulk requests getting rejected. In this blog post we will loo..

This is the second post in a three-part series about Instant Aggregations. Read how it all started in The Tale of Caching and Why It Matters from Simon Willnauer and Shay Banon and how the magnificent end to the story in Instant Aggregations: Rewriting Queries for Fun and Profit. Enjoy the trilogy!이 게시물은 Instant Aggregation에 대한 시리즈 중 두번째 게시물입니다. Simon Willnauer과 Shay Banon의 The Tale of Caching a..

For explanation purposes, let’s imagine that we have a cluster consisting of three nodes. It contains one index called blogs that has two primary shards. Each primary shard has two replicas. Copies of the same shard are never allocated to the same node, so our cluster looks something like Figure 8, “1개의 index와 3개의 node를 가진 cluster”.설명을 위해, 3개의 node를 가진 cluster를 가정해 보자. 그것은 2개의 primary shard를 가진 ..

During the initial query phase, the query is broadcast to a shard copy (a primary or replica shard) of every shard in the index. Each shard executes the search locally and builds a priority queue of matching documents.초기 query 절 에서, query는 index에 있는 모든 shard의, shard 복사본(primary 또는 replica shard)에 전달된다. 각 shard는 내부적으로 검색을 실행하고, 일치하는 document의 우선순위(priority) queue 를 생성한다.우선순위(priority) QueueA prio..

The query phase identifies which documents satisfy the search request, but we still need to retrieve the documents themselves. This is the job of the fetch phase, shown in Figure 15, “분산 검색의 fetch 절”.query 절은 어떤 document가 검색 request를 만족하는지를 확인할 뿐이다. 이제 document 자체를 가져와야 한다. 이것이, Figure 15, “분산 검색의 fetch 절”에서 보이는 fetch 절의 역할이다.Figure 15. 분산 검색의 fetch 절 The distributed phase consists of the follow..