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After many years running its own in-house C++ search engine, Amazon is exploring moving its customer facing e-commerce product search to Apache Lucene (tm), serving millions of customers each day worldwide. Solr, Elasticsearch and other Lucene derivatives have been used widely for many years at Amazon, but until now the .com product search has been powered by a proprietary in-house engine. We'll d
Searchkit is an open source library which helps you build a great search experience with Elasticsearch. import Searchkit from "searchkit" import Client from '@searchkit/instantsearch-client' import { InstantSearch, SearchBox, Hits, RefinementList, Pagination, RangeInput } from 'react-instantsearch'; const sk = new Searchkit({ connection: { host: 'http://localhost:9200', // cloud_id: "elastic-cloud
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Update November 2, 2015: Please note that facets are not supported in Elasticsearch 2.0+. For those of you familiar with Elasticsearch, you know that its an amazing modern, scalable, full-text search engine with Apache Lucene and the inverted index at its core. Elasticsearch allows users to query their data and provides efficient and blazingly fast look up of documents that make it perfect for cre
“Solr or Elasticsearch?”…well, at least that is the common question we hear from Sematext’s consulting services clients and prospects. Which one is better, Solr or Elasticsearch? Which one is faster? Which one scales better? Which one is easier to manage? Which one should we use? Is there any advantage to migrating from Solr to Elasticsearch? – and the list goes on. These are all great questions,
Dynamic faceting with Lucene by Michael McCandless. From the post: Lucene’s facet module has seen some great improvements recently: sizable (nearly 4X) speedups and new features like DrillSideways. The Jira issues search example showcases a number of facet features. Here I’ll describe two recently committed facet features: sorted-set doc-values faceting, already available in 4.3, and dynamic range
はじめに Elasticsearchのv1.0.0 が無事リリースされ、Aggregations APIの利用が可能になりました。 Elasticsearchはこれまで、検索結果を集約して解析する仕組みとしてFacets APIを提供していましたが、実質SQLのGroup byでのcountに相当する機能しかなかったため、maxやavgといった複雑な条件で集約を行いたい場合、クエリを分けて集約したり解析したりするしかありませんでした。 v1.0.0でAggregations APIが提供されたことで、maxやavgはもちろん、日付でヒストグラムを取得するといった複雑な集約も楽に行えるようになり、SQL型検索エンジンからの置き換えも行いやすくなってきたのではないかと思います。 内容 Aggregationsで何ができるのか、SQLのGroup byとの置き換えを例に検証してみましたので、その
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