<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:media="http://search.yahoo.com/mrss/"><channel><title>Search on Shaowen Chen's Website</title><link>https://www.chenshaowen.com/en/tags/search/</link><description>Recent content in Search on Shaowen Chen's Website</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>&amp;copy;2016 - {year}, All Rights Reserved.</copyright><lastBuildDate>Wed, 29 May 2024 00:00:00 +0000</lastBuildDate><sy:updatePeriod>weekly</sy:updatePeriod><atom:link href="https://www.chenshaowen.com/en/tags/search/atom.xml" rel="self" type="application/rss+xml"/><item><title>Deploying Elasticsearch on Memory Storage - 100M+ Records, Full-Text Search in 100ms</title><link>https://www.chenshaowen.com/en/blog/deploy-elasticsearch-using-memory-storage.html</link><pubDate>Wed, 29 May 2024 00:00:00 +0000</pubDate><atom:modified>Wed, 29 May 2024 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/deploy-elasticsearch-using-memory-storage.html</guid><description>1. Mount a Memory Storage Directory on the Host Create a directory to mount 1 mkdir /mnt/memory_storage Mount the tmpfs filesystem 1 mount -t tmpfs -o size=800G tmpfs /mnt/memory_storage Storage is allocated on demand, so using 100G of storage only consumes 100G of memory. The host node has 2T of memory, and here 800G is allocated to store Elasticsearch data.</description><dc:creator>微信公众号</dc:creator><category>Elasticsearch</category><category>High Performance</category><category>Full-Text Search</category><category>Operations</category><category>Storage</category><category>Search</category></item><item><title>Haystack Full-Text Search</title><link>https://www.chenshaowen.com/en/blog/haystack-full-text-search.html</link><pubDate>Fri, 21 Jul 2017 13:00:03 +0000</pubDate><atom:modified>Fri, 21 Jul 2017 13:00:03 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/haystack-full-text-search.html</guid><description>A quick word on the project requirements: the team needed to publish documentation externally. The documents are written in Markdown and need to be published as HTML. At first we used an Nginx + Jekyll solution. As the documentation grew, the document system developed a strong need for search. I</description><dc:creator>微信公众号</dc:creator><category>Django</category><category>Python</category><category>Data</category><category>Design</category><category>Search</category><category>R&amp;D</category></item></channel></rss>