不爲也 比不能也

이 글은 한국어, 중국어, 일본어 검색에 대한 3부작 중 마지막 글입니다. 만약 아직 1부를 읽지 않았다면 1부: 형태소 분석기부터 읽으시기 바랍니다. 엘라스틱서치 6.2를 이용한 한국어, 중국어, 일본어 검색 - 2부: Multi-fields에서는 멀티필드를 이용해서 다국어로 작성된 문서를 인덱싱하고 검색하는 방법을 살펴봤습니다. 하지만 하나의 텍스트를 언어에 상관 없이 4개의 필드에 저장하고 4개의 분석기로 분석하는 것은 시간과 저장공간의 낭비입니다. 이제 마지막으로 language detector를 이용해서 최적화해 보겠습니다. 텍스트는 역시 https://www.pyeongchang2018.com/ko/about-the-games에서 발췌했습니다. Language detectorlanguage d..

IntroductionIn this blog post, I am going to describe a new feature of Elasticsearch called Adaptive Replica Selection (ARS). Before describing what ARS does, I’ll first describe the problem that it tries to solve. Imagine that you have a cluster with three nodes. And across those three nodes, you have a shard and its replicas.이 게시물에서는 Elasticsearch의 새로운 기능인 Adaptive Replica Selection (ARS)를 설명하..

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..

Mapping types are going away. Elasticsearch 6.0 supports a single mapping type per index only, and it represents the first step on the way to removing types altogether.mapping type이 없어진다. Elasticsearch 6.0은 index 당 하나의 mapping type만 지원하며, 그것은 type을 완전히 제거하는 것의 첫 번째 단계이다.This blog post explains what types are, why we are removing them, how you can migrate your indices to a single type world, and ..

Elasticsearch 6.0 ships with two great improvements to help minimize index storage size. The best part about the improvements is they will require no special configuration changes or re-architectures, and in most cases will only require a simple upgrade and a newly created index. To illustrate the improvements, we’ll use Metricbeat, a lightweight tool for ingesting metrics into Elasticsearch.Ela..

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..

What If..."What if" questions are fun. "What if you had a time machine: when would you visit?" "What if you had one wish and it would come true: what would it be?" They're the types of hypothetical questions you can ask at a dinner party and get insights about what interests and motives somebody has if barriers were broken down. A few years ago at Elastic, we asked ourselves a "what if" that we ..

We often get questions about the order in which filters are executed, whether filters get executed before or after queries, etc. Those are indeed important questions: the recipe for quickly executing a query is often related to running the cheap bits before the expensive ones. You might have heard or read in the past that filters are executed before queries. While this statement is a good way to..

The idea of this article is to go over the capabilities of some of the features of Ingest node, which will be combined to parse a Comma Separated Value (CSV) file. We will go over what is an Ingest Node, what type of operations one can perform, and show a specific example starting from scratch to parse and display CSV data using the Elasticsearch and Kibana. 이 글의 목적은 CSV(Comma Separated Value) f..