Back2Basics: Introduction to Elasticsearch

Elasticsearch
_Elasticsearch is a highly scalable open-source full-text search and analytics engine. It allows you to store, search, and analyse big volumes of data quickly and in near real time. _
Elasticsearch provides near real-time search and analytics for all types of data. Whether you have structured or unstructured text, numerical data, or geospatial data, it can efficiently store and index it in a way that supports fast searches. You can go far beyond simple data retrieval and aggregate information to discover trends and patterns in your data. And as your data and query volume grows, the distributed nature of Elasticsearch enables your deployment to grow seamlessly right along with it.

#elasticsearch #database #back2basics

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Back2Basics: Introduction to Elasticsearch

Elasticsearch
_Elasticsearch is a highly scalable open-source full-text search and analytics engine. It allows you to store, search, and analyse big volumes of data quickly and in near real time. _
Elasticsearch provides near real-time search and analytics for all types of data. Whether you have structured or unstructured text, numerical data, or geospatial data, it can efficiently store and index it in a way that supports fast searches. You can go far beyond simple data retrieval and aggregate information to discover trends and patterns in your data. And as your data and query volume grows, the distributed nature of Elasticsearch enables your deployment to grow seamlessly right along with it.

#elasticsearch #database #back2basics

Elasticsearch 7.x Backup — “Snapshot & Restore” on AWS S3

In 2016 I wrote an Article about Elasticsearch Backup, it had and still has quite good interests from people. I decided to start a new series of articles with the Backup topic as the main argument.

The old article covered Snapshot & Restore functionalities based on Elasticsearch 2.4.x and the upcoming version, the 5.0. As it was 4 years ago I choose to refresh this tutorial and making it the first of a series of more.

I will prepare a small article on how to use the snapshot & restore functionality with different cloud-provider. This article is based on Elasticsearch 7.x, it doesn’t mean it couldn’t work on older versions but I focused on the latest one.

Elasticsearch Snapshot & Restore

Elasticsearch has a smart solution to backup single indices or entire clusters to remote shared filesystem or S3 or HDFS. The snapshot ES creates does not so resource consuming and is relatively small.

The idea behind these snapshots is that they are not “archive” in a strict sense, these snapshots can only be read by a version of Elasticsearch that is capable to read the index version stored inside the snapshot.

So you can follow this quick scheme if you want to restore ES snapshots :

• A snapshot of an index created in 6.x can be restored to 7.x.
• A snapshot of an index created in 5.x can be restored to 6.x.
• A snapshot of an index created in 2.x can be restored to 5.x.
• A snapshot of an index created in 1.x can be restored to 2.x.

Snapshots of indices created with ES 1.x cannot be restored to 5.x or 6.x, snapshots of indices created in 2.x cannot be restored to 6.x or 7.x, and snapshots of indices created in 5.x cannot be restored to 7.x or 8.x.

#elasticsearch-snapshot #elasticsearch-plugins #elasticsearch #backup #elasticsearch-backup #aws

Introduction to Spring Data Elasticsearch 4.1

Getting started with the latest version of Spring Data Elasticsearch 4.1 using Elasticsearch 7 as a NoSQL database.

Preface

I was recently playing around with Spring Data Elasticsearch (the Spring Data project for Elasticsearch) and came across several issues. One of these was a lack of up-to-date articles. This led me to share my experience using the latest Elasticsearch 7 and Spring Data Elasticsearch 4.1. I hope that my advice can help others gain insight into the tool and how to effectively use it for a variety of reasons.

In this Article, You Will Learn

• What Elasticsearch and Spring Data Elasticsearch are.
• Basic Elasticsearch cluster setup via Docker (including management and monitoring tool).
• How to configure Spring Data Elasticsearch in a project.
• How to use Spring Data Elasticsearch to upload and access Elasticsearch data.
• What are some pitfalls related to Elasticsearch usage?

First, I will briefly explain the purpose of Elasticsearch.

#java #tutorial #elasticsearch #spring data #elasticsearch tutorial #spring data tutorial

Elasticsearch Tutorial | Elasticsearch For Beginners

Hello! I’ve been building using Elasticsearch recently so thought it would be cool to do a quick tutorial on how it works. Hope you enjoy it!

Timestamps:
0:00 - Intro
0:12 - What is Elasticsearch
0:51 - Running Elasticsearch
2:09 - APIs/Queries
11:15 - Kibana Bonus Tips
13:37 - Thank You For Watching!

#elasticsearch #elasticsearch tutorial

Writing .Net Core Application’s Log into ElasticSearch with NLog

We could write all types of log into ElasticSearch by configuring our application.

As the first step, you need to create an empty web application(.net core) in Visual studio.

Now right click on the project and select** Add new Item** and search config to find Web Configuration File option. Set nlog.config as the file name.

Write the below code into the newly added config file.

XML

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<?xml version="1.0" encoding="utf-8" ?>

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<nlog xmlns="http://www.nlog-project.org/schemas/NLog.xsd"

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      xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

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      autoReload="true"> 

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  <extensions>

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    <add assembly="NLog.Targets.ElasticSearch"/>

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  </extensions>

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  <targets async="true"> 

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    <target name="elastic"

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            xsi:type="ElasticSearch"

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            index="YourAppName" uri="http://192.168.50.60:9200" 

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            layout ="API:SpecificName |${longdate}|${event-properties:item=EventId_Id}|${uppercase:${level}}|${logger}|${message} ${exception:format=tostring}|url: ${aspnet-request-url}|action: ${aspnet-mvc-action}" >

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    </target> 

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  </targets>

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  <rules>

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    <!--All logs, including from Microsoft-->

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    <!--<logger name="*" minlevel="Trace" writeTo="allfile" />

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    <logger name="*" minlevel="Trace" writeTo="ownFile-web" />

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    <logger name="*" minlevel="Trace" writeTo="database" />-->

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    <logger name="*" minlevel="Trace" writeTo="elastic" />

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  </rules>

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</nlog>

Before set the logging config, we should install some related packages, For this purpose, select NugetPackageManager from Tools menu and after that select PackageManagerConsole. We could write all types of log into ElasticSearch by configuring our application.

As the first step, you need to create an empty web application(.net core) in Visual studio.

Now right click on the project and select Add new Item and search config to find Web Configuration File option. Set nlog.config as the file name.

Write the below code into the newly added config file.

XML

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<nlog xmlns=“http://www.nlog-project.org/schemas/NLog.xsd”
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     xmlns:xsi=“http://www.w3.org/2001/XMLSchema-instance”
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     autoReload=“true”>
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   <target name=“elastic”
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           xsi:type=“ElasticSearch”
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           index=“YourAppName” uri=“http://192.168.50.60:9200”
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           layout =“API:SpecificName |${longdate}|${event-properties:item=EventId_Id}|${uppercase:${level}}|${logger}|${message} ${exception:format=tostring}|url: ${aspnet-request-url}|action: ${aspnet-mvc-action}” >
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   <!–
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   –>
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Before set the logging config, we should install some related packages, For this purpose, select NugetPackageManager from Tools menu and after that select PackageManagerConsole.

#programming #elasticsearch #nlog #.net core #.net #elasticsearch