2021년 2월 17일 (수) 08:57에 Pythagoras0님의 편집

2021-02-17T08:57:44Z

Pythagoras0: /* 메타데이터 */ 새 문단

2020-12-26T13:21:06Z

메타데이터: 새 문단

Pythagoras0: /* 노트 */ 새 문단

2020-12-16T06:32:34Z

노트: 새 문단

새 문서

== 노트 ==

* Use Bitnami’s Elasticsearch cluster configuration, which provisions multiple nodes the cloud-native APIs.<ref name="ref_77a5">[https://bitnami.com/stack/elasticsearch Elasticsearch]</ref>
* we included also the XPack endpoints of Elasticsearch.<ref name="ref_af56">[https://packagist.org/packages/elasticsearch/elasticsearch elasticsearch/elasticsearch]</ref>
* If you are using Elasticsearch 1.x or 2.x, prefer using the Elasticsearch-PHP 2.0 branch.<ref name="ref_af56" />
* Searching is a hallmark of Elasticsearch, so let's perform a search.<ref name="ref_af56" />
* Due to the dynamic nature of Elasticsearch, the first document we added automatically built an index with some default settings.<ref name="ref_af56" />
* ElasticSearch is an open source, RESTful search engine built on top of Apache Lucene and released under an Apache license.<ref name="ref_a014">[https://whatis.techtarget.com/definition/ElasticSearch Definition from WhatIs.com]</ref>
* On the Integrations Page you will see the Elasticsearch plugin available if the previous steps were successful.<ref name="ref_2345">[https://documentation.solarwinds.com/en/Success_Center/appoptics/Content/kb/host_infrastructure/integrations/elasticsearch.htm Elasticsearch]</ref>
* Select the Elasticsearch plugin to open the configuration menu in the UI, and enable the plugin.<ref name="ref_2345" />
* All Elasticsearch metrics are tagged with hostname .<ref name="ref_2345" />
* Elasticsearch, a horizontally scalable search engine that provides a Google-like search experience and near real-time results.<ref name="ref_8d6a">[https://www.nuxeo.com/integration/elasticsearch/ ElasticSearch for ECM and DAM | Connectors]</ref>
* The following is the bare minimum to get Elasticsearch working in a Debian/Ubuntu Operating System environment.<ref name="ref_5a86">[https://moodle.org/plugins/search_elastic Moodle plugins directory: Elastic]</ref>
* Some Elasticsearch providers such as AWS have a limit on how big the HTTP payload can be.<ref name="ref_5a86" />
* To create the index and populate Elasticsearch with your site's data, run this CLI script.<ref name="ref_5a86" />
* It is common to see Elasticsearch implementations using an Elasticsearch file indexing plugin rather than a stand alone service.<ref name="ref_5a86" />
* Elasticsearch (link resides outside ibm.com) is an open source search and analytics engine based on the Apache Lucene library.<ref name="ref_4545">[https://www.ibm.com/cloud/learn/elasticsearch What is Elasticsearch?]</ref>
* Elasticsearch makes it easy to add more capacity and reliability to your nodes and clusters.<ref name="ref_4545" />
* Elasticsearch scales with your enterprise and supports cross-cluster replication (CCR) on an index-by-index basis.<ref name="ref_4545" />
* One of the defining features of Elasticsearch is its compatibility with a variety of plugins and integrations.<ref name="ref_4545" />
* You can do many types of simple or complex Elasticsearch queries to visualize logs or metrics stored in Elasticsearch.<ref name="ref_d5be">[https://grafana.com/docs/grafana/latest/datasources/elasticsearch/ Elasticsearch]</ref>
* Here you can specify a default for the time field and specify the name of your Elasticsearch index.<ref name="ref_d5be" />
* The Elasticsearch query editor allows you to select multiple metrics and group by multiple terms or filters.<ref name="ref_d5be" />
* The Elasticsearch data source supports two types of queries you can use in the Query field of Query variables.<ref name="ref_d5be" />
* We’ll focus on the main arena of Elasticsearch: search.<ref name="ref_348a">[https://stackify.com/elasticsearch-tutorial/ Elasticsearch Tutorial: Your Detailed Guide to Getting Started]</ref>
* Elasticsearch is an open source, document-based search platform with fast searching capabilities.<ref name="ref_348a" />
* Elasticsearch runs on a clustered environment.<ref name="ref_348a" />
* Elasticsearch can run those shards on separate nodes to distribute the load across servers.<ref name="ref_348a" />
* This post is part 1 of a 4-part series about monitoring Elasticsearch performance.<ref name="ref_d532">[https://www.datadoghq.com/blog/monitor-elasticsearch-performance-metrics/ How to monitor Elasticsearch performance]</ref>
* In this post, we’ll cover how Elasticsearch works, and explore the key metrics that you should monitor.<ref name="ref_d532" />
* Elasticsearch is an open source distributed document store and search engine that stores and retrieves data structures in near real-time.<ref name="ref_d532" />
* Before we start exploring performance metrics, let’s examine what makes Elasticsearch work.<ref name="ref_d532" />
* At GitHub, we use Elasticsearch as the main technology backing our search services.<ref name="ref_819d">[https://github.blog/2019-03-05-vulcanizer-a-library-for-operating-elasticsearch/ Vulcanizer: a library for operating Elasticsearch]</ref>
* There are plenty of excellent Elasticsearch libraries, both official and community driven.<ref name="ref_819d" />
* Vulcanizer is a Go library for interacting with an Elasticsearch cluster.<ref name="ref_819d" />
* Elastic (former Elasticsearch) allows you to start small, but will grow with your business.<ref name="ref_6d97">[https://findwise.com/en/technology/elastic-elasticsearch Elastic (Elasticsearch)]</ref>
* We can help you get started with Elasticsearch at both the application code level as well as at the infrastructure level.<ref name="ref_6d97" />
* Elasticsearch is an open-source search server, based on the Lucene search library.<ref name="ref_141a">[https://cloud.google.com/monitoring/agent/plugins/elasticsearch Elasticsearch plugin]</ref>
* Monitoring does not automatically detect Elasticsearch.<ref name="ref_141a" />
* The services discovered are displayed on the Elasticsearch Services page in the Resources menu.<ref name="ref_141a" />
* The Elasticsearch plugin requires version 5.5.0-315 or later of the monitoring agent.<ref name="ref_141a" />
* For Elasticsearch 7.0 and later, use the major version 7 ( 7.x.y ) of the library.<ref name="ref_5858">[https://pypi.org/project/elasticsearch/ elasticsearch]</ref>
* For Elasticsearch 6.0 and later, use the major version 6 ( 6.x.y ) of the library.<ref name="ref_5858" />
* For Elasticsearch 5.0 and later, use the major version 5 ( 5.x.y ) of the library.<ref name="ref_5858" />
* For Elasticsearch 2.0 and later, use the major version 2 ( 2.x.y ) of the library, and so on.<ref name="ref_5858" />
* You must install Elasticsearch before installing Magento Commerce or Magento Open Source 2.4.0.<ref name="ref_9721">[https://devdocs.magento.com/guides/v2.4/install-gde/prereq/elasticsearch.html Magento 2 Developer Documentation]</ref>
* As of Magento 2.4, all installations must be configured to use Elasticsearch as the catalog search solution.<ref name="ref_9721" />
* Magento 2.4.x is tested with Elasticsearch 7.6.x only.<ref name="ref_9721" />
* The Magento application and Elasticsearch are installed on different hosts.<ref name="ref_9721" />
* This is where Elasticsearch comes in, as it’s often the engine that powers such experiences.<ref name="ref_c020">[https://sematext.com/guides/elasticsearch/ Elasticsearch Tutorial: What it is, How it Works & Use Cases]</ref>
* Elasticsearch is a free, open-source search and analytics engine based on the Apache Lucene library.<ref name="ref_c020" />
* Elasticsearch can be used to search all kinds of data.<ref name="ref_c020" />
* Elasticsearch is often used for storing data that needs to be sliced and diced, grouped by various dimensions, and such.<ref name="ref_c020" />
* Elasticsearch provides the ability to subdivide your index into multiple pieces called shards.<ref name="ref_147e">[https://towardsdatascience.com/an-overview-on-elasticsearch-and-its-usage-e26df1d1d24a An Overview on Elasticsearch and its usage]</ref>
* Although search engine at its core, users started using Elasticsearch for logs and wanted to easily ingest and visualize them.<ref name="ref_147e" />
* Kibana lets you visualize your Elasticsearch data and navigate the Elastic Stack.<ref name="ref_147e" />
* Elasticsearch can be used in so various ways that is difficult for me to capture all the most interesting use cases.<ref name="ref_147e" />
* Instead, users of this package need only send and receive data frames to Elasticsearch resources.<ref name="ref_c5bd">[https://cran.r-project.org/web/packages/elasticsearchr/vignettes/quick_start.html elasticsearchr: a Lightweight Elasticsearch Client for R]</ref>
* When not testing on your laptop, Elasticsearch usually comes in clusters of nodes (usually there are at least 3).<ref name="ref_c5bd" />
* In Elasticsearch a ‘row’ of data is stored as a ‘document’.<ref name="ref_c5bd" />
* Note, that ‘types’ are being slowly phased-out and in Elasticsearch v7.x there will only be indices.<ref name="ref_c5bd" />
* As of GDAL 2.1, Elasticsearch 1.X and, partially, 2.X versions are supported (5.0 known not to work).<ref name="ref_0298">[https://gdal.org/drivers/vector/elasticsearch.html Elasticsearch: Geographically Encoded Objects for Elasticsearch — GDAL documentation]</ref>
* Opening dataset name syntax¶ Starting with GDAL 2.1, the driver supports reading existing indices from a Elasticsearch host.<ref name="ref_0298" />
* (GDAL >= 3.1) Can be used to specify HTTP headers, typically for authentication purposes, that must be passed to Elasticsearch.<ref name="ref_0298" />
* Each mapping type inside a Elasticsearch index will be considered as a OGR layer.<ref name="ref_0298" />
* ; } } catch ( IOException exp ) { throw new RuntimeException ( "An error when execute Elasticsearch: " + exp .<ref name="ref_4330">[https://docs.platform.sh/configuration/services/elasticsearch.html Elasticsearch (Search service) · Platform.sh Documentation]</ref>
* toString (); } } const elasticsearch = require ( "elasticsearch" ); const config = require ( "platformsh-config" ).<ref name="ref_4330" />
* The Elasticsearch library lets you connect to multiple hosts.<ref name="ref_4330" />
* # Create an Elasticsearch client object.<ref name="ref_4330" />
* The amount of resources (memory, CPU, storage) will vary greatly, based on the amount of data being indexed into the Elasticsearch cluster.<ref name="ref_8daa">[https://docs.gitlab.com/ee/integration/elasticsearch.html Elasticsearch integration]</ref>
* There are specific scenarios where this isn’t true, but GitLab.com isn’t using Elasticsearch in an exceptionally CPU-heavy way.<ref name="ref_8daa" />
* When possible use SSDs, whose speed is far superior to any spinning media for Elasticsearch.<ref name="ref_8daa" />
* Keep in mind, these are minimum requirements for Elasticsearch.<ref name="ref_8daa" />
* Managing and scaling Elasticsearch can be difficult and requires expertise in Elasticsearch setup and configuration.<ref name="ref_5259">[https://aws.amazon.com/elasticsearch-service/the-elk-stack/what-is-elasticsearch/ What is Elasticsearch? – Amazon Web Services]</ref>
* Elasticsearch’s role is so central that it has become synonymous with the name of the stack itself.<ref name="ref_c7d2">[https://logz.io/blog/elasticsearch-tutorial/ What is Elasticsearch: Tutorial for Beginners]</ref>
* This Elasticsearch tutorial provides new users with the prerequisite knowledge and tools to start using Elasticsearch.<ref name="ref_c7d2" />
* Initially released in 2010, Elasticsearch (sometimes dubbed ES) is a modern search and analytics engine which is based on Apache Lucene.<ref name="ref_c7d2" />
* This Elasticsearch tutorial could also be considered a NoSQL tutorial.<ref name="ref_c7d2" />
* Additional advanced Elasticsearch settings for large deployments can be configured outside the System Console in the config.json file.<ref name="ref_6329">[https://docs.mattermost.com/deployment/elasticsearch.html Elasticsearch (E20) — Mattermost 5.29 documentation]</ref>
* If you expect your Mattermost server to have more than 2.5 million posts, we recommend using Elasticsearch for optimum search performance.<ref name="ref_6329" />
* Elasticsearch allows you to search large volumes of data quickly, in near real time, by creating and managing an index of post data.<ref name="ref_6329" />
* You can use this Prometheus exporter to monitor various metrics about Elasticsearch: justwatchcom/elasticsearch_exporter.<ref name="ref_6329" />
* Authentication¶ You can configure the client to use Elasticsearch’s API Key for connecting to your cluster.<ref name="ref_fa8e">[https://elasticsearch-py.readthedocs.io/ Python Elasticsearch Client — Elasticsearch 7.10.0 documentation]</ref>
* Please note this authentication method has been introduced with release of Elasticsearch 6.7.0 .<ref name="ref_fa8e" />
* Elasticsearch.js provides support for, and is regularly tested against, Elasticsearch releases 0.90.12 and greater.<ref name="ref_76be">[https://www.npmjs.com/package/elasticsearch elasticsearch]</ref>
* We also test against the latest changes in several branches in the Elasticsearch repository.<ref name="ref_76be" />
* To tell the client which version of Elasticsearch you are using, and therefore the API it should provide, set the apiVersion config param.<ref name="ref_76be" />
* var elasticsearch = require ( ' elasticsearch ' ) ; var client = new elasticsearch .<ref name="ref_76be" />
* Elasticsearch is a search engine based on the Lucene library.<ref name="ref_3315">[https://en.wikipedia.org/wiki/Elasticsearch Elasticsearch]</ref>
* Elasticsearch is developed in Java.<ref name="ref_3315" />
* Elasticsearch can be used to search all kinds of documents.<ref name="ref_3315" />
* Elasticsearch uses Lucene and tries to make all its features available through the JSON and Java API.<ref name="ref_3315" />
* But the truth is, all of these answers are correct and that’s part of the appeal of Elasticsearch.<ref name="ref_d7c5">[https://www.knowi.com/blog/what-is-elastic-search/ Elasticsearch: What it is, How it works, and what it’s used for]</ref>
* We’ll answer that in this post by understanding what Elasticsearch is, how it works, and how it’s used.<ref name="ref_d7c5" />
* Elasticsearch is a distributed, open-source search and analytics engine built on Apache Lucene and developed in Java.<ref name="ref_d7c5" />
* In Elasticsearch, a document can be more than just text, it can be any structured data encoded in JSON.<ref name="ref_d7c5" />
* While the concepts apply specifically to Elasticsearch, they are also important to understand when operating the stack as a whole.<ref name="ref_6005">[https://logz.io/blog/10-elasticsearch-concepts/ 10 Elasticsearch Concepts You Need to Learn]</ref>
* The following is still relevant to legacy versions of Elasticsearch.<ref name="ref_6005" />
* Elasticsearch types were used within documents to subdivide similar types of data wherein each type represents a unique class of documents.<ref name="ref_6005" />
* You can have as many indices defined in Elasticsearch as you want.<ref name="ref_6005" />
* Ask most folks to describe Elasticsearch, and you’ll get a variety of answers.<ref name="ref_62f0">[https://qbox.io/blog/what-is-elasticsearch What is Elasticsearch, and How Can I Use It?]</ref>
* They might know how to use Elasticsearch — but it’s hard to get them to provide clear, concise, and accurate answers.<ref name="ref_62f0" />
* Elasticsearch is a distributed analytics and search engine built over Apache Lucene, a Java-based search and indexing library.<ref name="ref_62f0" />
* To provide high read and write performance, Elasticsearch uses optimized data structures for various data types.<ref name="ref_62f0" />
* We are pleased to announce the release of Open Distro for Elasticsearch 1.12.0.<ref name="ref_9c67">[https://opendistro.github.io/for-elasticsearch/ Open Distro for Elasticsearch]</ref>
* Elasticsearch 를 RDBMS 와 비유를 하면서, Index 는 Database, Type 은 Table 과 유사하다고 생각했었다.<ref name="ref_b055">[https://brunch.co.kr/@springboot/182 Elasticsearch 공부를 시작하면서]</ref>
===소스===
<references />

@@ 108번째 줄: / 108번째 줄: @@
   <references />
-== 메타데이터 ==
+==메타데이터==
 ===위키데이터===
 * ID :  [https://www.wikidata.org/wiki/Q3050461 Q3050461]

← 이전 판		2020년 12월 26일 (토) 13:21 판
107번째 줄:		107번째 줄:
	===소스===		===소스===
	<references />		<references />
		+
		+	== 메타데이터 ==
		+
		+	===위키데이터===
		+	* ID : [https://www.wikidata.org/wiki/Q3050461 Q3050461]

일래스틱서치 - 편집 역사

2021년 2월 17일 (수) 08:57에 Pythagoras0님의 편집

Pythagoras0: /* 메타데이터 */ 새 문단

Pythagoras0: /* 노트 */ 새 문단