{"id":3926,"date":"2023-11-04T23:13:56","date_gmt":"2023-11-04T23:13:56","guid":{"rendered":"http:\/\/localhost:10003\/working-with-elasticsearch-for-search-and-analytics\/"},"modified":"2023-11-05T05:48:28","modified_gmt":"2023-11-05T05:48:28","slug":"working-with-elasticsearch-for-search-and-analytics","status":"publish","type":"post","link":"http:\/\/localhost:10003\/working-with-elasticsearch-for-search-and-analytics\/","title":{"rendered":"Working with Elasticsearch for search and analytics"},"content":{"rendered":"<p>Elasticsearch is a distributed search and analytics engine that is used to index, search, and analyze large volumes of data quickly and in real-time. Elasticsearch is built on top of Apache Lucene, which is a high-performance indexing and search library. Elasticsearch provides a simple and powerful REST API that allows users to interact with their data through search queries, aggregations, and more.<\/p>\n<p>In this tutorial, we will cover the basics of working with Elasticsearch and provide you with a step-by-step guide on how to set up Elasticsearch on your own machine, index data, and perform basic search and aggregation queries.<\/p>\n<h2>Prerequisites<\/h2>\n<p>Before getting started, you\u2019ll need the following:<\/p>\n<ul>\n<li>A basic understanding of REST APIs<\/li>\n<li>A machine running Ubuntu 18.04 (or any other recent Linux distribution)<\/li>\n<li>Java 8 or later installed on your computer<\/li>\n<li>Elasticsearch installed on your machine<\/li>\n<\/ul>\n<p>For the purpose of this tutorial, we\u2019ll be installing Elasticsearch on Ubuntu 18.04.<\/p>\n<h2>Step 1: Install Elasticsearch<\/h2>\n<p>The first step to getting started with Elasticsearch is to install it on your machine. Here are the steps for installing Elasticsearch on Ubuntu 18.04:<\/p>\n<h3>1.1: Install Java 8 or Later<\/h3>\n<p>Elasticsearch is built on top of Java, so you&#8217;ll need to install Java 8 or later on your machine. Here&#8217;s how to install Java 8:<\/p>\n<pre><code class=\"language-bash\">sudo apt-get update\nsudo apt-get install openjdk-8-jdk\n<\/code><\/pre>\n<p>Once you&#8217;ve installed Java, you can verify the installation by running the following command:<\/p>\n<pre><code class=\"language-bash\">java -version\n<\/code><\/pre>\n<h3>1.2: Download and Install Elasticsearch<\/h3>\n<p>The next step is to download and install the Elasticsearch package that matches the version of Java you&#8217;ve installed. Here&#8217;s how to download and install the Elasticsearch package:<\/p>\n<pre><code class=\"language-bash\">wget https:\/\/artifacts.elastic.co\/downloads\/elasticsearch\/elasticsearch-7.9.3-linux-x86_64.tar.gz\ntar -xzf elasticsearch-7.9.3-linux-x86_64.tar.gz\ncd elasticsearch-7.9.3\n.\/bin\/elasticsearch\n<\/code><\/pre>\n<p>This will start Elasticsearch on your machine.<\/p>\n<h2>Step 2: Index Data<\/h2>\n<p>Once Elasticsearch is installed, you can start indexing data. In Elasticsearch, data is stored in indices, which are similar to tables in a relational database. Here&#8217;s how to create an index and add data to it:<\/p>\n<h3>2.1: Create an Index Mapping<\/h3>\n<p>Before you can start indexing data, you&#8217;ll need to define a mapping for your index. A mapping defines the fields that your index will contain and their data types. Here&#8217;s an example mapping for a blog post index:<\/p>\n<pre><code class=\"language-json\">PUT \/blog_post\n{\n  \"mappings\": {\n    \"properties\": {\n      \"title\": {\n        \"type\": \"text\"\n      },\n      \"content\": {\n        \"type\": \"text\"\n      },\n      \"tags\": {\n        \"type\": \"keyword\"\n      },\n      \"date\": {\n        \"type\": \"date\"\n      }\n    }\n  }\n}\n<\/code><\/pre>\n<p>This mapping defines four fields: <code>title<\/code>, <code>content<\/code>, <code>tags<\/code>, and <code>date<\/code>. The <code>title<\/code> and <code>content<\/code> fields are of type <code>text<\/code>, which means that they can contain full-text search data. The <code>tags<\/code> field is of type <code>keyword<\/code>, which means that it can be used for keyword-based search queries. The <code>date<\/code> field is of type <code>date<\/code>, which means that it can be used for date-based search queries.<\/p>\n<h3>2.2: Index Data<\/h3>\n<p>Now that you have a mapping for your index, you can start indexing data. Here&#8217;s how to index a blog post:<\/p>\n<pre><code class=\"language-json\">PUT \/blog_post\/_doc\/1\n{\n  \"title\": \"Getting started with Elasticsearch\",\n  \"content\": \"Elasticsearch is a distributed search and analytics engine that is used to index, search, and analyze large volumes of data.\",\n  \"tags\": [\"elasticsearch\", \"tutorial\", \"search\"],\n  \"date\": \"2020-11-18\"\n}\n<\/code><\/pre>\n<p>This will create a new document in the <code>blog_post<\/code> index with an ID of <code>1<\/code>.<\/p>\n<h2>Step 3: Search and Analyze Data<\/h2>\n<p>Now that you&#8217;ve indexed some data, you can start querying it. In Elasticsearch, search and analytics are performed using the REST API, which allows you to send search queries and aggregations to Elasticsearch.<\/p>\n<h3>3.1: Simple Search Query<\/h3>\n<p>Here&#8217;s an example of a simple search query that searches for blog posts that contain the word <code>elasticsearch<\/code> in the title or content:<\/p>\n<pre><code class=\"language-json\">GET \/blog_post\/_search\n{\n  \"query\": {\n    \"match\": {\n      \"title\": \"elasticsearch\"\n    }\n  }\n}\n<\/code><\/pre>\n<p>This query uses the <code>match<\/code> query to search for the term <code>elasticsearch<\/code> in the <code>title<\/code> field. Elasticsearch will return any documents that contain the term <code>elasticsearch<\/code> in the <code>title<\/code> field.<\/p>\n<h3>3.2: Aggregations<\/h3>\n<p>Elasticsearch also supports aggregations, which allow you to summarize and analyze data. Here\u2019s an example of a simple aggregation that counts the number of blog posts for each tag:<\/p>\n<pre><code class=\"language-json\">GET \/blog_post\/_search\n{\n  \"aggs\": {\n    \"tags\": {\n      \"terms\": {\n        \"field\": \"tags\"\n      }\n    }\n  }\n}\n<\/code><\/pre>\n<p>This query uses the <code>terms<\/code> aggregation to group the documents by their <code>tags<\/code> field. Elasticsearch will return a list of all the unique tags in the <code>tags<\/code> field, along with the number of documents that have each tag.<\/p>\n<h2>Conclusion<\/h2>\n<p>In this tutorial, we\u2019ve covered the basics of working with Elasticsearch, including how to install Elasticsearch, index data, and perform basic search and aggregation queries. Elasticsearch is a powerful tool for search and analytics, and it\u2019s used by some of the world\u2019s largest companies to index and analyze large volumes of data. With Elasticsearch, you can search, filter, and aggregate your data in real-time, making it an essential tool for any modern data-driven organization.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Elasticsearch is a distributed search and analytics engine that is used to index, search, and analyze large volumes of data quickly and in real-time. Elasticsearch is built on top of Apache Lucene, which is a high-performance indexing and search library. Elasticsearch provides a simple and powerful REST API that allows <a href=\"http:\/\/localhost:10003\/working-with-elasticsearch-for-search-and-analytics\/\" class=\"btn btn-link continue-link\">Continue Reading<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_import_markdown_pro_load_document_selector":0,"_import_markdown_pro_submit_text_textarea":"","footnotes":""},"categories":[1],"tags":[384,387,193,355,385,383,386,382],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.5 (Yoast SEO v21.5) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Working with Elasticsearch for search and analytics - Pantherax Blogs<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"http:\/\/localhost:10003\/working-with-elasticsearch-for-search-and-analytics\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Working with Elasticsearch for search and analytics\" \/>\n<meta property=\"og:description\" content=\"Elasticsearch is a distributed search and analytics engine that is used to index, search, and analyze large volumes of data quickly and in real-time. 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