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Solr Integration in the Anserini Information Retrieval Toolkit

Solr Integration in the Anserini Information Retrieval Toolkit

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Title: Solr Integration in the Anserini Information Retrieval Toolkit
Author: Clancy, Ryan
Eskildsen, Toke
Ruest, Nick
Lin, Jimmy
Abstract: Anserini is an open-source information retrieval toolkit built around Lucene to facilitate replicable research. In this demonstration, we examine different architectures for Solr integration in order to address two current limitations of the system: the lack of an interactive search interface and support for distributed retrieval. Two architectures are explored: In the first approach, Anserini is used as a frontend to index directly into a running Solr instance. In the second approach, Lucene indexes built directly with Anserini can be copied into a Solr installation and placed under its management. We discuss the tradeoffs associated with each architecture and report the results of a performance evaluation comparing indexing throughput. To illustrate the additional capabilities enabled by Anserini/Solr integration, we present a search interface built using the open-source Blacklight discovery interface.
Sponsor: This work was supported in part by the Natural Sciences and Engineering Research Council (NSERC) of Canada, the Canada Foundation for Innovation Leaders Fund, and the Ontario Research Fund.
Subject: Information retrieval
anserini
Blacklight
Lucene
Distributed retrieval
SolrCloud
Solr
Information systems
Search engine architectures and scalability
Type: Article
URI: https://doi.org/10.1145/3331184.3331401
http://hdl.handle.net/10315/36205
Citation: Ryan Clancy, Toke Eskildsen, Nick Ruest, and Jimmy Lin. “Solr Integration in the Anserini Information Retrieval Toolkit.” Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (2019).
ISBN: 978-1-4503-6172-9/19/07
Date: 2019

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