Elasticsearch Interview Questions and Answers

06 Feb 2023, 29 Questions

Elasticsearch is a real-time and evenly distributed search engine that supports RESTful searching and analysis based upon the Apache Lucene full-text search engine. It has distributed and full-field real-time analytics storage. Along with Logstash and Kibana, Elasticsearch is widely used. In the field of Elasticsearch during the last few years, ’ maximum competition is created. Hence, it becomes mandatory to know the most common Elasticsearch interview questions if you are willing to build a career in this segment. Elasticsearch is broadly used by major platforms. Most important among them are Wikipedia, Netflix, IFTTT, Accenture, Hip chat, Fujitsu, Stack Overflow, and Medium.

Elasticsearch is also document-oriented enables the storage of data and then their indexing so that the content becomes easily searchable. Elasticsearch entirely works over the HTTP interface and JSON documents, and altogether it is developed in Java programming language. It is known that the Elasticsearch server uses the port range around 9200 to 9300. In order to check if the server is running, you just need to type the URL of any corresponding homepage which is primarily followed in reference to the port number. Looking for a reliable piece of information, take a follow-up through these Elasticsearch interview questions.

About Elasticsearch

It is built upon Apache Lucene a full-text search engine
Document orientation stores the data which are structured JSON documents
Text support it supports full-text search indexing to provide faster results
Supports it supports auto-completion and instant results.
APIs Elasticsearch supports restful APIs for the retrieval of data and records
Serves Elasticsearch search the cross-platform
Developed and written in it is developed in Java language
License Apache license 2.0
Developed by Shay Banon
Elasticsearch is also an open source software

Most Frequently Asked Elasticsearch Interview Questions

Here in this article, we will be listing frequently asked Elasticsearch Interview Questions and Answers with the belief that they will be helpful for you to gain higher marks. Also, to let you know that this article has been written under the guidance of industry professionals and covered all the current competencies.

Q1. How to create a node in Elasticsearch?

In Elasticsearch, the nodes are added to enhance the quality and reliability of the cluster. There can be of the master node to control the entire cluster and also a basic data node. In order to add a node follows the steps-

  • You have to set up a new Elasticsearch instance
  • Specify its name in the cluster.name attribute
  • Begin the Elasticsearch and node will be created

Note: This is one of the basic Elasticsearch interview questions but an important one.

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Q2. What is a split brain problem in Elasticsearch?

Split brain is a consequence that generates when the master nodes in the cluster fail. In the bunch of clusters if any master node fails, then the slave node can choose a new master note for the effective functionality. In case the former one gets restore or comes into the functioning again, then it leads to the conflict. This problem also rises when communication is failed among the nodes.

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Q3. What is an Elasticsearch query? Explain the types of queries?

Elasticsearch has its own query domain where the queries can be defined in the JSON format. Elasticsearch serves domain specific language DSL queries that make it easy to resolve real-world queries. Broadly Elasticsearch is divided into the following two different types of queries which ultimately solve multiple other queries associated with them. The list of them is-

  • Full-text queries - this includes the multi-match query, match phrase prefix query, match query, common terms query and many more
  • Term level queries - this includes the term query, term set query, existing query, ids query, wildcard query, and lot more.
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Q4. What is a Type in Elasticsearch?

In Elasticsearch, Type signifies the class of similar data. It can signify a name for making and is beneficial for the abstractions or for indicating the similar yet not identical data.

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Q5. What is a cluster in Elasticsearch?

Cluster is a collection of one or multiple servers which consists of the data and also serves the federated indexing across all the different nodes. By default, a cluster can be identified by a significant name, i.e., Elasticsearch.

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Q6. What are the advantages of Elasticsearch?

Being the open source and highly distributive network Elasticsearch has many advantages.

  • It is a document-oriented platform
  • Elasticsearch supports multiple search options
  • A large number of complicated queries can be executed speedily with Elasticsearch
  • In order to avoid the chance of data loss, Elasticsearch manages the record.
  • Elasticsearch also supports indexing and multi-tenancy
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Q7. What is Elasticsearch? How does it work?

Elasticsearch is a full-text searchable engine which is based on Lucerne. Generally, Elasticsearch was released as an open source platform which was developed in JavaScript under the Apache license terms. Using the phrase "multi-tenant and capable full-text search," Elasticsearch can be justified shortly. It has an HTTP interface for web and schema-free JSON files. As it is developed in Javascript, it can index the documents in variedly diverse formats.

Elasticsearch promotes the indexing of documents targeting the repository. Elasticsearch stores and executes the data as it converts the initial form of files into the internal documents and secures them with the basic data structure resembling with the JSON objects.

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Q8. How to install elasticsearch on windows?

Below mentioned are a few steps to install Elasticsearch in windows -

  • Download the zip file from relevant sources(websites)
  • Install it and launch through GUI
  • Carefully select the configuration and logs directories
  • Now choose to install it as service or manually
  • Finish the configuration steps carefully; it will be followed as cluster name, node, etc
  • Select the plug-in
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Q9. What is the ingest node in Elasticsearch?

In Elasticsearch, an ingest node is a type of note that can be utilized during the documentation process before indexing. It is a part of the Elasticsearch cluster, and it intercepts the index request and bulk applying the transformation and later passes it back to the index.

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Q10. What is a quorum in Elasticsearch?

The quorum by default, is set to action.write_onsistency. in case the quorum is not fulfilled then the index returns after the timeout with an error. Elasticsearch documentation follows the rule for write_consiatency level in quorum as quorum(>replicas/2+1).

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Q11. How to create an Elasticsearch user?

In order to create an Elasticsearch user, you have to follow the below mentioned steps

  • With the help of Elasticsearch built-in user, log in to 'Kibana.'
  • Follow the management/security and user page
  • Select 'create a new user.'
  • Click over the ‘create new user’ and select "logstash_internal user.
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Q12. What is the difference between Elasticsearch and Logstash?
  • Elasticsearch is the open source search engine platform whereas Logstash is a server-side data processing platform.
  • Logstash can process the data from multiple sources all at once and transforms them accordingly. Elasticsearch, on the other hand, stores the complex entities as JSON documents.
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Q13. What are mappings in Elasticsearch?

The basic outline of the documents or files that are stored in the index is known as mapping. Mapping signifies the data type in the specific fields and format representing the documents and their rules dynamically.

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Q14. What are shards? How many shards should Elasticsearch indexes have?

Shards are the statements or smaller portion of the nodes which manage the data in an index. Actually, this indexing is done in order to overcome the limitations associated with the resources, especially like ram or CPU for the scalability. In order to resolve this, data is fragmented into different portions, which are administered by a different node or Elasticsearch. By default, the Elasticsearch index has 5 shards, which are primary and 1 replica. Thus, in total, each index has 10 shards.

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Q15. What is a document in reference to the Elasticsearch? What can basic operations be performed on a document?

In Elasticsearch a document refers to the row with the relatable database. More or less, they are similar. The major difference among them is that in each document an index can have a variant structure but comprising the same data type for similar fields is required. Whereas, in a document, every field or structure having different data can exist multiple times.

Fields can also contain different documents at the same time. Elasticsearch is a document-oriented search engine platform where the documents are stored in sequence.

  • Documents can be indexed (document updating occurs here)
  • Right after indexing documents can be searched, sort or filtered around
  • Documents can also be retrieved
  • Full-text search or query resolution can also be done with documents.
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Q16. What is dynamic mapping in Elasticsearch?

Dynamic mapping allows the user to index documents without unnecessary configurations for the field name. Rather it will be added automatically through the Elasticsearch with any other predefined custom rules.

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Q17. What is Elasticsearch analyzer?

The constituent of analyzers includes a tokenizer which is preceded by the Char filters and 1 or 0 token filters. On the name of API or any other mapping definition, the analytical module also refers to the analyzers. In Elasticsearch, analyzers are already provided which are ready for the user to apply. Users are also allowed to create custom analyzers and built token filters or characters accordingly.

Elasticsearch interview question on your own to get a better understanding.

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Q18. How to enable authentication in Elasticsearch?

In order to enable the authentication in Elasticsearch, follow the steps-

  • Stop Kibana
  • Stop the Elasticsearch
  • Follow settings and add xpack.security.enabled to the ES_PATH_CONF/ elasticsearch.yml file
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Q19. What is REPLICAS in Elasticsearch?

As Elasticsearch is a full-text distributed search engine, each index in it splits to multiple forms. It comprises five shards and one replica for each specific index. Replica serves the queries as requests, and each of them corresponds to the primary shared in the cluster. When the index is created the number of replicas per index can be defined. They exist in order to provide availability and fault tolerance.

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Q20. What is routing in Elasticsearch?

The determination of document allocation in the specific SHARD is known as routing. Routing gets automatically handled, and the default scheme hashes the document ID and utilizes it in order to find SHARD.

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Q21. What is filter Elasticsearch?

In the Elasticsearch analyzer, the text which is passed through a character is obtained by the character filter. This can be edited as by deleting, adding, or shifting the characters in a number of ways. In the Elasticsearch analyzer, the tokens which are forwarded are obtained by the token filters. It can be edited by deleting or altering them.

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Q22. How do I speed up Elasticsearch?

Try the below-mentioned tips-

  • Use the bulk requests
  • Index buffer size
  • Use the fastest hardware
  • Disable for the initial notes
  • Increase the refresh interval
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Q23. What is the query DSL Elasticsearch?

Query DSL is actually a flexible and expressive search language that the Elasticsearch utilizes in order to expose the sparkling side of Lucene with a JSON interface. It simplifies the queries and transforms them to be more accurate and flexible and easy to debug.

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Q24. What is Elasticsearch inverted index?

In order to speed up the full-text searches, an inverted index is designed. It consists of a bunch of unique words that usually appear in the documents, and for every specific word, there is a list in which it appears.

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Q25. How does Elasticsearch work with Kibana?

The open source data visualization plug-in is known as the commander in Elasticsearch. It enhances the visual capacities on the top of the index over the Elasticsearch cluster. It also allows the user to create the lines, bar, and scatter plots for any of the charts or maps over the large volume of the data.

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Q26. What is fuzzy search Elasticsearch?

Fuzzy search is actually a process in which web page location document location is identified resembling with the search argument. It also serves even if the argument is not relevant with the search correspondent for the particular information.

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Q27. Name the software which is required to install Elasticsearch?

Using the JavaScript Elasticsearch is built and developed. Using the below-mentioned software, it can be installed.

  • The advanced and latest version of Java its series
  • Another version of Java 1.8.0_131
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Q28. How a user can create an index in the Elasticsearch cluster?

And index can be easily created in the Elasticsearch cluster all you have to do is use the command PUT prior to the index name. You will be permitted to create the index, and you can also add multiple other indexes if you need. Once it is done, you have to apply the command POST before the index name.

Note: The above question is a very important question when it comes to Elasticsearch interview questions.

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Q29. What is the aggregation working in Elasticsearch?

In Elasticsearch, the aggregated data structures based on the search queries are provided by the aggregation hierarchy or framework. There are multiple aggregations available which have different outputs and functioning. Aggregation in Elasticsearch is a functional unit that binds the analytical details for the particular set of data information.

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After these basic details on Elasticsearch, let’s move to the Elasticsearch interview questions and their answers.


Using the common interface with JSON and HTTP, Shay Banon authored Elasticsearch in Java programming language. In February 2010, Elastic NV developed a stable version of Elaticsearch. Currently, version 7.1.1 is in the market which was released on May 28, 2019.

  • Elasticsearch is compatible with any platform
  • It is a Near real-time (NRT) which makes it easily searchable
  • The cluster of Elasticsearch is evenly distributed, which increase its scalability.
  • It supports multiple documents
  • Elasticsearch efficiently deals with the managed documents
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