Elasticsearch Tutorial

Getting Started, Use-cases, Basics, and Actionable Tips

Introduction

Elasticsearch is the most popular open-source search and analytics engine. One of the factors that has contributed greatly to its popularity is Elasticsearch's ability to deliver realtime search results for all types of data including textual, numerical, geospatial, structured, and unstructured. On top of this, Elasticsearch allows users to analyze huge volumes of search data in milliseconds. Elasticsearch also offers businesses flexibility of hosting on their own or with a cloud provider.

Use-cases of Elasticsearch

Thanks to its support of the wide variety of data mentioned earlier, businesses have been able to implement Elasticsearch for multiple applications ranging from backend operations to storefront search. Thanks to its versatile nature and realtime search speed capabilities, Elasticsearch has been a key piece in helping users find information.

Below are some common use-cases of Elasticsearch:

App Search

Any apps that have the need for access, retrieval, and reporting of data will be a great fit for Elasticsearch. Delivering relevant search results at each keystroke goes a long way in keeping users engaged in the app as more often than not, search is the primary form of navigation.

Website Search

From media publishers, e-commerce stores to enterprise sites, Elasticsearch is gaining popularity as the best solution for accurate searches. Coupled with the fact that it includes document search, product search, blog search, people search, and many others, it's not surprising to see many of the most-visited sites in the world use Elasticsearch.

Business Analytics

The Elastic Stack (Elasticsearch, Logstash, Kibana, and Beats) comes with built-in options that serve a business tool. In some cases, there might be a learning curve involved, but with services like appbase.io offering out-of-the-box search term and click analytics, even non-technical users can perform analytics on Elasticsearch data without prior knowledge of the Elastic Stack.

Geospatial Search

Elasticsearch saves location as latitude and longitude and these to help personalize search results involving distances. Many retail businesses and aggregators can use this to streamline their online shopping experiences by showing visitors an updated catalog depending on their live location.

Logging

Elasticsearch lets you centralize your data making it easy for businesses to scale. Data is grabbed from a variety of inputs regardless of its format or complexity. All this data is parsed and converted into a common format and using visualization tools delivers operational insights.

In this article, we will talk about Elasticsearch from the perspective of building an application or site search. There is a lot that goes into making a completely fleshed out search solution, and we will address how Elasticsearch helps one create a complete search solution.

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How Elasticsearch affects search experience

So, we see that more and more businesses are adapting Elasticsearch, but what functionalities are making it a viable option for them to switch:

Search speed

Elasticsearch is built on Lucene which excels at performing full-text searches. It also lets you combine data from many types of searches, from structured, unstructured, geo, to metric. The realtime nature of Elasticsearch also enables records to be searchable within just a minute of being indexed and thus minimizing latency.

Search relevance

Elasticsearch lets you fine-tune setting to help your search to provide the most relevant search results. This way, results that are more likely to keep users engaged rank higher. Though implementing these changes can be a challenge for businesses, with appbase.io's dashboard, business teams can configure and test their search settings in realtime.

Distributed search

Elasticsearch was built to help businesses scale. Having a distributed architecture means that replicas of your data and serve as backup copies in case of any hardware failures. This can be a complex tasks for businesses with lots of data, but Elasticsearch APIs handle this automatically.

Analytics

Elasticsearch is a great tool for measuring and optimizing performance metrics. Users will be able to filter data basis on not only popular searches but also track click and conversion data and presents this data visually for monitoring. While this requires integrations with different plugins, appbase.io can offer this functionality right out-of-the box.

Ecosystem

Elasticsearch comes with well-documented APIs and that has made it possible for developers to customize their implementation. It also has a great ecosystem of UI components that has been instrumental in helping businesses build and go-live faster.

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How does Elasticsearch handle your data

Here we will explain some concepts that will give you a better understanding of the Elasticsearch backend:

Documents

A document is the basic unit of information that is stored and indexed by Elasticsearch. This data has many fields including numbers, text strings, dates, etc in the JSON format. Each document has a unique ID and the fields are mapped so that they can be fetched when a search query is made.

Indices

An index is a collection of documents that have similar in structure making it like a database. Each index has a unique name which serves as a reference during search, update or delete operations.

Inverted Index

An inverted index stores text in a structure that allows for quick full-text searches. It splits documents into individual search terms and then maps each search term to the relevant documents. This serves as a quick point of reference to find the best matches even in large datasets.

Mapping

Mapping defines how your data is stored in an index. It's possible to extend the capability of your mapped attributes by adding new fields at any time. Changing existing fields, however, requires re-indexing. Elasticsearch defines strings, numbers, geo-point data, etc. as data types which later function as "keywords" for searching, retrieving, and sorting processes.

Shards

With Elasticsearch, you can create subsets of an Index. These subsets are called Shards. You can consider each shard to be an independent index. This is part of the distributed nature of Elasticsearch as your data is replicated across different shards to ensure redundancy. These replicas also protect against hardware failures while increasing the capacity of the server to process searching and retrieving request.

Node

A node is a single server that stores your data and is part of indexing and search functions. Multiple nodes can run on a single physical server, VM, or container. There are three types of nodes whose purpose will become clear once you understand upcoming Clusters as well.

Types of Nodes

Master Node - This is responsible for all cluster-wide operations like creating/deleting an index and adding/removing nodes. Client Node - Forwards cluster requests to the master node and data-related requests to data nodes. Data Node - Stores data and executes data-related operations such as search and aggregation.

Clusters

A cluster is a group of one or more nodes which are connected as part of the Elasticsearch processes. Nodes discover each other in a cluster by their shared cluster name. The strength of an Elasticsearch cluster lies in the distribution of processes across the nodes in the cluster.

Configuring Elasticsearch with appbase.io

Businesses are using Elasticsearch to solve many challenges that they are facing. Having the added flexibility of having on-premises or cloud deployment makes it the perfect fit for teams of all sizes. Running Elasticsearch as a self-managed service, however, can be resource intensive for many businesses. Usually, this task is handled by an in-house Elasticsearch team which can assess hardware requirements and manage clusters.

This is where having a fully managed service like appbase.io comes in. We give businesses access to all the components they need so that they can focus on building a fantastic search experience. Teams no longer have to worry about knowing the Elastic stack inside-out as they can configure search settings and access search analytics via a point and click dashboard.

Appbase.io provides the search stack for building modern apps

Onboarding appbase.io

You can start with appbase.io in just 3 steps:

  1. Create your account here
  2. Pick a pricing plan and data center for your Cluster
  3. Create an Index and import data in JSON or .csv. Alternatively, you can import data from an existing Elasticsearch index.

There is more that goes into making a unique search experience than the search relevance. With appbase.io, users can set query rules, hide or promote results, optimize search results, conduct A/B tests, craft UI components, use Role-Based Access Control, create filters, and much, much more.

User Experience: Building an easy-to-use search experience

Accessibility of Search across devices

Deliver a seamless search experience across devices with UI components that scale with device resolutions.

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Search as you type and Auto-Suggestions

Set search functionalities via a point-and-click dashboard. Search across multiple data sources simultaneously (categories, products, etc.).

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Faceted Search to guide users

Easily add different facets to your search and help navigation and create a unique search experience for your users.

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Business Experience: Leveraging search analytics to drive engagement

Actionable Analytics to help optimize

Optimize your search with appbase.io thanks to a visual analytics dashboard. Capture popular searches, click to conversion ratios, click positions, etc. in realtime.

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Easily set Search Relevancy

Control search relevancy from the appbase.io dashboard in realtime. Set weights to boost attribute relevance. Add typo-tolerance and synonyms to minimize end-user frustration.

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Extend your search relevance with Query Rules

Set "if-this, then-that" rules via the dashboard to promote a result, hide specific results, change search behavior, add facets and more.

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A/B Testing search strategy

Create A/B Tests quickly and analyze performance by integrating with your preferred analytics tools like Optimizely, Google Optimize, or VWO.

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Developer Experience: Utilizing tools to make it easier to implement and scale

Building new features

Whether you are building web or mobile search, appbase.io has built industry-leading UI components that help developers go-live 10x faster.

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Access Control for search

Create multiple intent-specific keys and pair with specialized roles to segment users. Strengthen your security by restricting IPs and using HTTP Referers.

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Multi-Language Search

Appbase.io supports over 39 languages for your search engine. Configure stop words, stemming exceptions and diacritics settings.

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Flexibility in Deployment

Run as a fully managed service or bring your own Elasticsearch. You can even run appbase.io as a Docker container on your cloud or on your premises.

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Get the best of Elasticsearch

Have full control over your Elasticsearch cluster. Visualize with Kibana and choose from any of the addons available in the Elasticsearch ecosystem.

Pick your Elasticsearch

A fully managed cluster with no compromises. Choose your version, nodes, data center region.

Visualize with Kibana

Use Kibana to get insights with rich Elasticsearch visualizations.

Add-ons

Choose from the popular Elasticsearch ecosystem plugins and tools to be deployed alongside your Elasticsearch.

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