Open in app
Home
Notifications
Lists
Stories

Write
Xiaohu Li
Xiaohu Li

Home

Published in Tinder Tech Blog

·Sep 19, 2019

How We Improved Our Performance Using ElasticSearch Plugins: Part 2

Written By: Daniel Geng, Software Engineer | Pierre Poitevin, Senior Software Engineer| Xiaohu Li, Engineering Manager We introduced the architecture and baseline performance benefits of the ES plugin in Part 1. In this post, we will focus on a specific customization that removes one of the largest bottlenecks in the…

Elasticsearch

7 min read

How We Improved Our Performance Using ElasticSearch Plugins: Part 2
How We Improved Our Performance Using ElasticSearch Plugins: Part 2

Published in Tinder Tech Blog

·Sep 4, 2019

How We Improved Our Performance Using ElasticSearch Plugins: Part 1

Written By: Pierre Poitevin, Senior Software Engineer|Daniel Geng, Software Engineer | Xiaohu Li, Engineering Manager Problems The Tinder Eng team has recently been working on integrating machine learning (ML) algorithms into the Tinder recommendation system. The Tinder recommendation system is what is used to provide users with recommendations, that the users…

Elasticsearch

12 min read

How We Improved Our Performance Using ElasticSearch Plugins: Part 1
How We Improved Our Performance Using ElasticSearch Plugins: Part 1

Published in Tinder Tech Blog

·May 29, 2019

Geosharded Recommendations Part 2: Architecture

Authors: Frank Ren|Director, Backend Engineering, Xiaohu Li|Manager, Backend Engineering, Devin Thomson| Lead, Backend Engineer, Daniel Geng|Backend Engineer We covered the sharding mechanism in our previous post, in which we laid the theoretical foundation of geosharded clusters. In part 2, we are going to explain how we built a high-performing, scalable…

Elasticsearch

7 min read

Geosharded Recommendations Part 2: Architecture
Geosharded Recommendations Part 2: Architecture
Xiaohu Li

Xiaohu Li

Help

Status

Writers

Blog

Careers

Privacy

Terms

About

Knowable