不爲也 比不能也

As the project manager of stagemonitor, an open source performance monitoring tool, I've recently been looking for a database to replace the cool-but-aging Graphite Time Series DataBase (TSDB) as the backend. TSDBs are specialised packages for storing (performance) metric data, like the response time of your app or the CPU utilisation of a server. Ultimately, we were looking for a datastore that..

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..

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.As much as we love Elasticsearch, at Found we've seen customers crash their clusters in numerous ways. Mostly due to simple misunderstandings and usually the fixe..

analysisAnalysis is the process of converting full text to terms. Depending on which analyzer is used, these phrases: FOO BAR, Foo-Bar, foo,bar will probably all result in the terms foo and bar. These terms are what is actually stored in the index. A full text query (not a term query) for FoO:bAR will also be analyzed to the terms foo,bar and will thus match the terms stored in the index. It is ..

Disable the features you do not need By default Elasticsearch indexes and adds doc values to most fields so that they can be searched and aggregated out of the box. For instance if you have a numeric field called foo that you need to run histograms on but that you never need to filter on, you can safely disable indexing on this field in your mappings:기본적으로, Elasticsearch는 대부분의 field가 검색되고 aggreg..

string fields replaced by text/keyword fieldseditThe string field datatype has been replaced by the text field for full text analyzed content, and the keyword field for not-analyzed exact string values. For backwards compatibility purposes, during the 5.x series:string field datatype이 full text analyzed 내용에 대해서는 text field로, not-analyzed exact string 값에 대해서는 keyword field로 변경되었다. 이전 version과의 호환..

A number of changes have been made to mappings to remove ambiguity and to ensure that conflicting mappings cannot be created.모호함을 제거하고, mapping의 충돌이 일어나지 않도록 하기 위해, mapping에 많은 변경이 있었다.One major change is that dynamically added fields must have their mapping confirmed by the master node before indexing continues. This is to avoid a problem where different shards in the same index dynamically add..

So far, we have learned how to use Elasticsearch as a simple NoSQL-style distributed document store. We can throw JSON documents at Elasticsearch and retrieve each one by ID. But the real power of Elasticsearch lies in its ability to make sense out of chaos — to turn Big Data into Big Information.지금까지, 간단한 NoSQL-style의 분산 document 저장소로서의 Elasticsearch를 사용하는 방법에 대해 배웠다. Elasticsearch에 JSON docume..

While playing around with the data in our index, we notice something odd. Something seems to be broken: we have 12 tweets in our indices, and only one of them contains the date 2014-09-15, but have a look at the total hits for the following queries:index에 있는 데이터를 살펴보다 보면, 이상한 점을 발견할 수 있다. 뭔가 깨진 것 같다. index에는 12개의 tweet이 있다. 그 중의 단 하나만 2014-09-15 를 포함하고 있다. 그런데 아래 query의 total hits를 보면GET /_searc..

In order to be able to treat date fields as dates, numeric fields as numbers, and string fields as full-text or exact-value strings, Elasticsearch needs to know what type of data each field contains. This information is contained in the mapping.date field를 날짜로, 숫자 field를 숫자로, string field를 full-text나 exact-value 문자열로 처리하기 위해서는, Elasticsearch는 각 field가 가지고 있는 데이터의 type을 알아야 한다. 이 정보는 mapping에 있다...