<?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>Elasticsearch on Shaowen Chen's Website</title><link>https://www.chenshaowen.com/en/tags/elasticsearch/</link><description>Recent content in Elasticsearch 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/elasticsearch/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>Using JuiceFS to Store Elasticsearch Data</title><link>https://www.chenshaowen.com/en/blog/store-elasticsearch-data-in-juicefs.html</link><pubDate>Wed, 22 May 2024 00:00:00 +0000</pubDate><atom:modified>Wed, 22 May 2024 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/store-elasticsearch-data-in-juicefs.html</guid><description>1. Storage Options There are three storage approaches:
Isolate by directory and share a single JuiceFS Elasticsearch nodes share one JuiceFS instance, mounting different Elasticsearch nodes through subdirectories.
/0/ corresponds to node Node-0
/1/ corresponds to node Node-1
/2/ corresponds to node Node-2
The main advantage of this approach is that it is easy to scale and simple to configure.</description><dc:creator>微信公众号</dc:creator><category>Kubernetes</category><category>JuiceFS</category><category>Elasticsearch</category><category>Storage</category><category>Operations</category></item><item><title>Deploying the Elasticsearch Stack on a Kubernetes Cluster</title><link>https://www.chenshaowen.com/en/blog/how-to-deploy-the-elasticsearch-stack-on-kubernetes.html</link><pubDate>Wed, 06 Jul 2022 00:00:00 +0000</pubDate><atom:modified>Wed, 06 Jul 2022 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/how-to-deploy-the-elasticsearch-stack-on-kubernetes.html</guid><description>If you use Logstash to centrally receive the log input from Filebeat, it easily creates a single point of bottleneck; if you use Kafka to receive the log input from Filebeat, the timeliness of the logs is not guaranteed. Here we output the logs collected by Filebeat directly to Elasticsearch.</description><dc:creator>微信公众号</dc:creator><category>Kubernetes</category><category>Elasticsearch</category><category>Logging</category><category>Operations</category><category>ELK</category><category>Monitoring</category></item></channel></rss>