不爲也 比不能也

A little over a year ago I described how to maximize indexing throughput with Elasticsearch, but a lot has changed since then so here I explain the changes that affect indexing performance in Elasticsearch 2.0.0.약 1년전, Elasticsearch에서 처리량을 최대화하는 방법에 대해 설명한 적이 있다. 그런데, 그때에 비해 많은 것이 변경되어, 여기에서 Elasticsearch 2.0.0 에서 index 성능에 영향을 미치는 변경 사항에 대해 설명한다.Store throttling is now automaticPrior to 2.0.0, ..

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..

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 ..

Use bulk requests Bulk requests will yield much better performance than single-document index requests. In order to know the optimal size of a bulk request, you should run a benchmark on a single node with a single shard. First try to index 100 documents at once, then 200, then 400, etc. doubling the number of documents in a bulk request in every benchmark run. When the indexing speed starts to ..

Strict REST query string parameter parsingeditPrevious versions of Elasticsearch ignored unrecognized URL query string parameters. This means that extraneous parameters or parameters containing typographical errors would be silently accepted by Elasticsearch. This is dangerous from an end-user perspective because it means a submitted request will silently execute not as intended. This leniency h..

A document doesn’t consist only of its data. It also has metadata—information about the document.The three required metadata elements are as follows:document가 데이터만으로 구성되어 있지는 않다. document에 대한 정보인 metadata 도 가지고 있다. 3개의 필수 metadata는 아래와 같다._indexWhere the document livesdocument가 존재하는 장소_typeThe class of object that the document representsdocument를 대표하는 오브젝트 class_idThe unique identifier for the d..

When you index a document, it is stored on a single primary shard. How does Elasticsearch know which shard a document belongs to? When we create a new document, how does it know whether it should store that document on shard 1 or shard 2?document를 색인하면, 특정 primary shard에 저장된다. Elasticsearch는 document가 어느 shard에 속해 있는지 어떻게 알까? 새로운 document를 생성하면, document를 shard 1 또는 2 중 어느 shard에 저장하는지 어떻게 알까?Th..

Before moving on, we are going to take a detour and talk about how search is executed in a distributed environment. It is a bit more complicated than the basic create-read-update-delete(CRUD) requests that we discussed in Distributed Document Store.더 나아가기에 앞서, 분산 환경에서 검색을 실행하는 방법에 대해 이야기하려 한다. 이것은 Distributed Document Store에서 이야기했던, 기본적인 CRUD(create-read-update-delete) 보다 약간 더 복잡하다.Content Warni..

The uppermost level of a mapping is known as the root object. It may contain the following:mapping의 최상위 단계는 root object 로 알려져 있다. 아래와 같은 것을 포함하고 있다.A properties section, which lists the mapping for each field that a document may containdocument가 가지게 될, 각 field의 mapping을 나열하는 properties 부분.Various metadata fields, all of which start with an underscore, such as _type, _id, and _source_type, _id, _..