Elasticsearch Quiz - MCQ Questions and Answers

Elasticsearch is a distributed, open-source search and analytics engine built on Apache Lucene. It is used for various applications, including full-text search, logging, monitoring, and analytics. This quiz will test your basic understanding of Elasticsearch concepts, architecture, and features.

Let’s begin with these multiple-choice questions (MCQs) to test your knowledge of Elasticsearch.

1. What is Elasticsearch primarily used for?

a) Relational database management

b) Full-text search and analytics

c) File storage

d) Video streaming

Answer:

b) Full-text search and analytics

Explanation:

Elasticsearch is primarily used for full-text search and analytics, allowing users to search and analyze large volumes of data in near real-time.

2. What technology is Elasticsearch built on?

a) Apache Hadoop

b) Apache Spark

c) Apache Lucene

d) Apache Kafka

Answer:

c) Apache Lucene

Explanation:

Elasticsearch is built on top of Apache Lucene, a powerful library for full-text indexing and searching.

3. In Elasticsearch, what is an index?

a) A collection of documents

b) A single document

c) A method for caching queries

d) A backup of a database

Answer:

a) A collection of documents

Explanation:

An index in Elasticsearch is a collection of documents, and each index can store multiple types of documents.

4. What is a document in Elasticsearch?

a) A table in a database

b) A JSON object representing a piece of data

c) A single entry in a log file

d) A relational record

Answer:

b) A JSON object representing a piece of data

Explanation:

In Elasticsearch, a document is a JSON object that represents a specific piece of data, and each document is stored in an index.

5. What is a shard in Elasticsearch?

a) A type of query

b) A basic unit of storage that allows horizontal scaling

c) A backup of an index

d) A part of the Elasticsearch client

Answer:

b) A basic unit of storage that allows horizontal scaling

Explanation:

A shard is a basic unit of storage in Elasticsearch that allows an index to be divided into smaller pieces, enabling horizontal scaling and distribution across nodes.

6. What is a replica shard in Elasticsearch?

a) A backup of a primary shard

b) A write-only shard

c) A cache for query results

d) A shard stored on the same node as the primary

Answer:

a) A backup of a primary shard

Explanation:

A replica shard is a copy of a primary shard, and it helps to provide fault tolerance by storing a backup on a different node.

7. What query language does Elasticsearch use?

a) SQL

b) SPARQL

c) Elasticsearch Query DSL

d) MongoDB Query Language

Answer:

c) Elasticsearch Query DSL

Explanation:

Elasticsearch uses its own domain-specific language, Elasticsearch Query DSL (Domain-Specific Language), for querying data in a flexible and powerful way.

8. What is Kibana?

a) A backup tool for Elasticsearch

b) A web-based tool for visualizing and managing Elasticsearch data

c) A type of Elasticsearch node

d) A tool for migrating data to Elasticsearch

Answer:

b) A web-based tool for visualizing and managing Elasticsearch data

Explanation:

Kibana is an open-source web-based tool used for visualizing, analyzing, and managing Elasticsearch data, providing features such as dashboards and reporting.

9. What is an Elasticsearch node?

a) A cluster of servers

b) A single server or instance that is part of an Elasticsearch cluster

c) A backup of an index

d) A type of Elasticsearch query

Answer:

b) A single server or instance that is part of an Elasticsearch cluster

Explanation:

An Elasticsearch node is a single server or instance that is part of an Elasticsearch cluster and stores data and participates in indexing and search operations.

10. What is an Elasticsearch cluster?

a) A single node running Elasticsearch

b) A group of nodes working together to store and search data

c) A way to store documents in a single table

d) A set of backup nodes

Answer:

b) A group of nodes working together to store and search data

Explanation:

An Elasticsearch cluster is a group of one or more nodes working together to store data and provide search capabilities, allowing for scalability and fault tolerance.

11. What is a "mapping" in Elasticsearch?

a) A blueprint for how data is stored in an index

b) A method for joining documents

c) A way to query data

d) A strategy for distributing nodes

Answer:

a) A blueprint for how data is stored in an index

Explanation:

A mapping defines the schema for an index in Elasticsearch, specifying how documents and their fields are stored and indexed.

12. What is the default port for Elasticsearch?

a) 80

b) 9200

c) 443

d) 8080

Answer:

b) 9200

Explanation:

The default port for Elasticsearch is 9200 for HTTP communication.

13. What is the role of the master node in an Elasticsearch cluster?

a) Storing data and handling search requests

b) Managing cluster-wide settings and operations

c) Handling backup and recovery operations

d) Indexing data

Answer:

b) Managing cluster-wide settings and operations

Explanation:

The master node is responsible for managing cluster-wide operations, including creating or deleting indexes and tracking nodes in the cluster.

14. How does Elasticsearch achieve horizontal scaling?

a) By adding more memory to nodes

b) By distributing shards across multiple nodes

c) By increasing CPU power

d) By using cloud storage

Answer:

b) By distributing shards across multiple nodes

Explanation:

Elasticsearch achieves horizontal scaling by distributing shards across multiple nodes, allowing the data and query load to be balanced across the cluster.

15. What is an inverted index in Elasticsearch?

a) A list of all documents in an index

b) A mapping from terms to the documents that contain them

c) A way to store metadata

d) A method for optimizing searches

Answer:

b) A mapping from terms to the documents that contain them

Explanation:

An inverted index is a data structure used in Elasticsearch to map search terms to the documents that contain them, which makes full-text search efficient.

16. What is "reindexing" in Elasticsearch?

a) Modifying the mapping of an existing index

b) Copying documents from one index to another

c) Caching query results for faster retrieval

d) Backing up an index to a different node

Answer:

b) Copying documents from one index to another

Explanation:

Reindexing in Elasticsearch refers to the process of copying documents from one index to another, often used when updating mappings or restructuring data.

17. What is a snapshot in Elasticsearch?

a) A real-time query of an index

b) A backup of an index or cluster at a point in time

c) A collection of shards

d) A replica of a node

Answer:

b) A backup of an index or cluster at a point in time

Explanation:

A snapshot in Elasticsearch is a backup of an index or cluster at a specific point in time, which can be stored and restored when needed.

18. What is a filter in Elasticsearch queries used for?

a) To sort query results

b) To exclude certain documents from search results without affecting the score

c) To modify the ranking of search results

d) To remove duplicate documents

Answer:

b) To exclude certain documents from search results without affecting the score

Explanation:

Filters in Elasticsearch are used to exclude documents from search results without calculating a relevance score, making them more efficient for certain types of queries.

19. How does Elasticsearch handle multi-field search?

a) By concatenating fields into a single field

b) By using multi-field queries that search across multiple fields

c) By normalizing all fields

d) By sorting results based on field length

Answer:

b) By using multi-field queries that search across multiple fields

Explanation:

Elasticsearch allows multi-field queries, which enable users to search across multiple fields simultaneously, providing more comprehensive search results.

20. How does Elasticsearch support real-time search and indexing?

a) By using a single thread for indexing

b) By indexing documents in near real-time and making them searchable as soon as possible

c) By storing indexes in-memory only

d) By using distributed databases for indexing

Answer:

b) By indexing documents in near real-time and making them searchable as soon as possible

Explanation:

Elasticsearch supports near real-time indexing, meaning documents are made searchable almost immediately after they are indexed, providing fast search results.

These questions cover the fundamental concepts of Elasticsearch, including indexing, querying, and cluster management. Understanding these basics will help you use Elasticsearch effectively in search and analytics applications.