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Optimizing Wellhub Autocomplete Service Latency: a Multi-Region Architecture

Every company wants fast, reliable, and low-latency services. Achieving these goals requires significant investment and effort. In this article, I will share how Wellhub invested in a multi-region architecture to achieve a low-latency autocomplete service.

Matheus Felisberto
on Oct 17, 2024
AI, ML & Data Engineering

Understanding Similarity Scoring in Elasticsearch

In this article, the author discusses the importance of Relevancy Score for developing Search Engine solutions and how to calculate the relevancy score using Elasticsearch's similarity module.

Ziv Segal Brilian Firdaus
on Dec 23, 2020
Development

Q&A: Relevant Search with Elasticsearch and Solr

In their book "Relevant Search", Doug Turnbull and John Berryman focus on the challenge of providing search results by balancing the needs and intents of the user. Using Elasticsearch and Solr, relevance engineers can constantly tune the needs of the business vs. the needs of the user.

David Iffland
on Sep 26, 2016
Building Better Search Engines by Measuring Search Quality

Search engines are developed using standard sets of realistic test cases that let developers measure the relative effectiveness of alternative approaches. This article talks about NIST's Text Retrieval Conference (TREC) project used to create the infrastructure to measure the quality of search results.

Ian Soboroff Ellen M. Voorhees Paul Over
on Jul 06, 2014
How Fog Creek Software Made Kiln's Search 1000x Faster with Elasticsearch

ElasticSearch is an open source, distributed, real-time search and analytics engine. This is the story of how Elasticsearch helped Fog Creek Software make Kiln’s Search 1000x faster.

Kevin Gessner
on Sep 11, 2013
Interview and Book Review: The LogStash Book, Log Management Made Easy

James Turnbull makes a compelling case for using Logstash for centralizing logging by explaining the implementation details of Logstash within the context of a logging project. The book targets both small companies and large enterprises through a two sided case; both for the low barrier to entry and the scaling capabilities.

Aslan Brooke
on May 20, 2013
Using AWS Cloud Search

Many of today’s applications heavily rely on the search functionality. In this Article Boris Lublinsky explains how to build Java APIs for uploading data and implementing search for Amazon Cloud Search. Usage of these APIs can simplify embedding Amazon Cloud Search functionality into custom applications.

Boris Lublinsky
on Dec 11, 2012
Software Engineering Meets Evolutionary Computation

In this IEEE article, author Mark Harman talks about evolutionary computation and how it has affected software design. Main focus is on search-based software engineering (SBSE), which focuses on the application of search-based optimization techniques to problems in software engineering. Mark also discusses the application of SBSE in emerging areas such as cloud, mobile and embedded systems.

Mark Harman
on Apr 16, 2012
Implementing Lucene Spatial Support

Lucene geospatial extension proposed in this article is based on a two level search – first level search is based on Cartesian Grid search and the second level implements shape specific spatial calculations

Boris Lublinsky
on Jan 13, 2012
Integrating Lucene with HBase

The article describes overall design and implementation of integrating Lucene search library with HBase back end. It describes integration architecture, implementation and HBase tables design

Boris Lublinsky Mike Segel
on Dec 29, 2011
Guardian.co.uk Switching from Java to Scala

Citing a need to be able to respond faster to events, and disappointment in the feature set and timeframe for Java 7, the team behind guardian.co.uk is using Scala as an alternative to Java for their new projects. InfoQ spoke to Web Platform Development Team Lead Graham Tackley about their current stack, the reasons behind the move, and the experience of using Scala in large-scale development.

Charles Humble
on Apr 04, 2011
LinkedIn Signal: A Case Study for Scala, JRuby and Voldemort

On September 29th LinkedIn Signal was announced, providing a social search application both for LinkedIn shares and tweets from LinkedIn-Twitter bounded accounts. This article aims to provide more insight into the motivation and technical challenges of combining Scala, JRuby and Voldemort, at such scale.

Dio Synodinos
on Oct 11, 2010