Top 10 Elasticsearch interview questions and answers for 2022

Do you want to work with the top US companies? Or, do you want to hire a Silicon Valley standard professional? This comprehensive list of Elasticsearch interview questions is curated with the aim of not only helping developers in acing their interviews but also assisting employers in evaluating the candidates adequately. Go through these questions to get some idea about the type of Elasticsearch interview questions that you can ask or be asked.

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Elasticsearch is an open-search analytics solution that emphasizes speed, scale, and relevance. Since its initial release, Elasticsearch has quickly become the most popular and commonly used tool for log analytics, full-text search, security intelligence, business analytics, and operational intelligence use cases. With services like ingestion, enrichment, storage, analysis, and visualization, the tool is transforming how the world uses data.

You must go through these interview questions on Elasticsearch to ace your interview. These questions can be highly beneficial in assessing the candidates’ technical skills. If you're looking to hire Elasticsearch developers to be a part of your development team, these Elasticsearch interview questions can be helpful.

So, whether you are a candidate actively looking for Elasticsearch interview questions and answers for preparation or a recruiter looking for an Elasticsearch professional, the following list of Elasticsearch interview questions will be of great use for you.

Top 10 Elasticsearch interview questions and answers

1.

Point out the functions that you can perform on Elasticsearch documents


This is one of the basic Elasticsearch interview questions that you can kick off your interview process with. Elasticsearch performs the following basic functions: indexing, searching, fetching, updating, and deleting documents.

2.

What is Elasticsearch Cluster and Node?


As the name implies, an Elasticsearch cluster is a collection of one or more nodes that are working together as one. Since the cluster is distributive and decentralized in nature, scaling up your needs with a higher availability rate and improved productivity even in cases of minor setbacks becomes seamless.

On the other hand, a node is an Elasticsearch server that starts executing the moment you run an instance of Elasticsearch. By default, they can handle HTTP and transport traffic. Each node is assigned with one or more roles that explain its responsibility and functionality in the cluster. For instance, data nodes store the data, and master nodes manage the cluster activities and cluster state.

3.

What are the different types of Node in Elasticsearch?


As mentioned in the above answer, each node is assigned with one or more roles where all nodes know about each other in the cluster. As a result, they can forward client requests to the appropriate node as needed. You can assign the nodes their roles by setting up node.roles in Elasticsearch.yml. However, if you don’t set nodes.roles, by default, nodes are assigned the following roles –

  • master
  • data
  • data_content
  • data_hot
  • data_warm
  • data_cold
  • data_frozen
  • ingest
  • ml
  • remote_cluster_client
  • transform

When setting nodes.roles, make sure to crosscheck that nodes are assigned with roles that your cluster needs. For instance, master and data roles are a must for every cluster.

4.

Explain SHARDS, REPLICAS, and index.


Shards - To improve the fetching result during data search, you can divide indexed data into smaller chunks, called shards. As the number of documents increases, processing becomes slower, and consequently, responding to a request gets delayed. To avoid this delay, you can use shards.

Replicas - Each shard is divided into two copies for high availability and fault tolerance purposes. These copies are known as replicas.

Index - An index is similar to a database in a relational database. It utilizes the concept of replicas and shards to distribute data around the cluster.

5.

How do you create, delete, list, and query Indices in Elasticsearch?


  • Command to create a new index – PUT /test_index?pretty
  • Command to delete index -DELETE /test_index?pretty
  • Command to list all index names and their basic information – GET _cat/indices?v
  • Command to query an index – GET test_index/_search
  • Command to query multiple indices – GET test_index1, test_index2/ _search

6.

List the configuration management tool supported by Elasticsearch.


  • Important configuration management tools supported by Elasticsearch are –
  • Puppet – puppet-Elasticsearch
  • Chef – cookbook-Elasticsearch
  • Ansible – ansible-elastic search

7.

What is an Analyzer? Explain the different built-in Analyzers that are available on Elasticsearch.


The analyzer is built of tokenizers and filters that can be used to transform data internally for it to be indexed. Elasticsearch offers a wide range of built-in Analyzers that can be utilized in any index without requiring further configuration –

  • Standard Analyzer – It is used to divide the text into terms on word boundaries (as defined by the Unicode Text Segmentation Algorithm)
  • Simple Analyzer – It divides texts into terms, each instance, whenever it identifies a character that is not a letter. Furthermore, it also lowercases all terms.
  • Whitespace Analyzer – It divides texts into terms, each instance, whenever it identifies any whitespace character. Unlike Simple Analyzer, it does not lower cases terms.
  • Stop Analyzer – It is similar to Simple Analyzer, with the only difference being that it also supports the removal of stop words.
  • Keyword Analyzer – It is basically a ‘’noop’’ Analyzer that welcomes whatever text it is given and yields the same text as a single term.
  • Pattern Analyzer – It splits the text into terms with the help of regular expression and supports lower-casing and stop words.
  • Language Analyzer- Elasticsearch supports various language-specific Analyzers such as English or French.
  • Fingerprint Analyzer- this specialist Analyzer can create a fingertip that can be utilized to detect duplicates.

8.

What is cluster health, and how do you check it?


You can ask this Elasticsearch interview question for experienced to assess the candidate’s technical skill. As the name suggests, cluster health returns a simple status on the cluster’s health. The status usually is – green, yellow, or red. Red indicates that a specific shard is not available in the cluster, yellow implies that a primary shard is available, but replicas are not, and lastly, green means all shards are available.

Command to check cluster health – GET / _cat/health?v

9.

Explain Painless and its benefits in Elasticsearch.


Painless is a secure and default scripting language explicitly designed for Elasticsearch. It offers the following benefits –

  • Safety – Painless ensures high-level security for your cluster. It maintains a fine-grained allowlist. Anything that does not fall under the allow list throws a compilation error.
  • Performance – Since it compiles directly into JVM bytecode, it can utilize all possible optimization offered by JVM. Additionally, it avoids any features that need additional and slower checks at runtime.
  • Simplicity – Painless extends Java syntax to improve readability and remove boilerplate. It implements simple syntax that anyone with some basic coding experience can get the hang of.

10.

What are the benefits of attributes- enabled, index, and store?


If you want to store a field without indexing it, you can use the ‘enabled’ attribute. It causes Elasticsearch to skip the parsing of the field’s contents altogether. The ‘index’ attribute oversees the indexing of field values and is useful for searching purposes. On the other hand, the ‘store’ attribute means field values are stored and will return the values when requested.

Wrapping up

Regardless of being experienced or fresher, you must prepare Elasticsearch interview questions that can be asked during the interview. Similarly, it is essential for hiring managers to prepare for interview questions on Elasticsearch to accurately evaluate candidates, create a positive candidate experience, and promote their brand.

However, it is equally vital for recruiters to search for talent that makes the rest of the team feel at home. Thus, apart from technical Elasticsearch interview questions, soft-skill-based interview questions are also important. So, you must prepare for answering questions about your leadership skills, communication skills, team skills, etc., apart from the technical Elasticsearch interview questions.

If you want to build a team of world-class Elasticsearch developers, contact Turing today. If you're an experienced Elasticsearch developer searching for a new opportunity, Turing.com is a great place to start.

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Ahmed
Ahmed
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Ahmed is a software developer with 8 years of experience in developing web applications on different cloud infrastructures (AWS, Azure, and GCP). He has experience in building and deploying microservices and serverless apps on various platforms through different CI/CD tools.
Expertin
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  • Elasticsearch
  • Python
  • Microservices
  • Docker
Also worked with
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  • DevOps
  • AWS
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Ossaija
Ossaija
Elasticsearch Developer
Ossaija has 7 years of software engineering experience. He has an expert level understanding of Javascript, NodeJs, ReactJs and Python.
Expertin
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  • Node.js
  • JavaScript
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Experience
7 years
Availability
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Tarun
Tarun
Elasticsearch Developer
Tarun has a proven track record of working as a Lead Cloud Platform Engineer, and Subject Matter Expert (SME) on hybrid multi-cloud technologies (AWS/Azure/GCP).
Expertin
  • AWS
  • Azure
  • Elasticsearch
  • JavaScript
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Dmitry
Dmitry
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Dmitry is a tech leader, cloud architect and site reliability engineer with over two decades of intense professional experience strictly adhering to DevOps methodology.
Expertin
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  • DevOps
  • Docker
  • Ansible
  • Terraform
Also worked with
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Experience
20 years
Availability
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Alex
Alex
Elasticsearch Developer
Alex is a senior full-stack web developer with 14 years of experience working with companies ranging from small startups to large scale enterprises. He has worked on creating custom tools, improving existing ones, and creating mobile apps and websites.
Expertin
  • Elasticsearch
  • Node.js
  • PHP/MySQL
  • jQuery
  • Bootstrap
Also worked with
  • Laravel
  • AWS Lambda
  • React
  • Django
Experience
14 years
Availability
Full-time
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