Top 50 FAQs for Elastic

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1. What is Elastic?

Ans:- Elastic is a search and analytics engine that provides solutions for various use cases like full-text search, logging, and data analysis.

2. What is Elasticsearch?

Ans:- Elasticsearch is an open-source, distributed search and analytics engine that is part of the Elastic Stack.

3. What is the Elastic Stack?

Ans:- The Elastic Stack, also known as ELK Stack, is a collection of open-source products for searching, analyzing, and visualizing data.

4. What are the main components of the Elastic Stack?

Ans:- The main components include Elasticsearch, Logstash, and Kibana (ELK). Beats are also commonly used for data shipping.

5. How does Elasticsearch work?

Ans:- Elasticsearch stores and indexes data in a distributed manner, allowing for fast and efficient searching, aggregations, and analytics.

6. What is Logstash?

Ans:- Logstash is a server-side data processing pipeline that ingests data from multiple sources, transforms it, and sends it to a desired destination.

7. What is Kibana?

Ans:- Kibana is a visualization and exploration tool that interacts with Elasticsearch data, providing a user-friendly interface for data analysis.

8. What is Beats in the Elastic Stack?

Ans:- Beats are lightweight data shippers that send data from various sources to Elasticsearch or Logstash.

9. What types of data can Elastic handle?

Ans:- Elastic is versatile and can handle various types of data, including structured and unstructured data.

10. How is data indexed in Elasticsearch?

Ans:- Data in Elasticsearch is indexed based on JSON documents, allowing for flexible and dynamic schemas.

11. What is an index in Elasticsearch?

Ans:- An index in Elasticsearch is a collection of documents that share a common structure.

12. How are search queries performed in Elasticsearch?

Ans:- Elasticsearch uses a powerful query language called Elasticsearch Query DSL for searching and filtering data.

13. What are shards in Elasticsearch?

Ans:- Shards are the basic units of storage in Elasticsearch, and an index can be divided into multiple shards for scalability.

14. How is security implemented in the Elastic Stack?

Ans:- Elastic Stack provides security features like authentication, authorization, and encryption to protect data and access.

15. What is X-Pack?

Ans:- X-Pack is a set of premium features and extensions for the Elastic Stack, providing additional functionality like security, monitoring, and machine learning.

16. What is the license model for Elastic Stack?

Ans:- As of version 7.11, the Elastic Stack is licensed under the Server Side Public License (SSPL).

17. How to install Elasticsearch?

Ans:- Installation instructions for Elasticsearch can be found on the official Elastic website.

18. How to configure Logstash?

Ans:- Logstash is configured using a configuration file where input, filter, and output plugins are defined.

19. How to create visualizations in Kibana?

Ans:- Kibana provides a user interface for creating visualizations such as charts, graphs, and dashboards.

20. Can Elasticsearch be used for time-series data?

Ans:- Yes, Elasticsearch is commonly used for indexing and querying time-series data.

21. What is the role of an analyzer in Elasticsearch?

Ans:- Analyzers in Elasticsearch are used during indexing to tokenize and index text fields.

22. How to handle data backup and recovery in Elasticsearch?

Ans:- Elastic provides various mechanisms for data backup and recovery, including snapshots and restore functionality.

23. What is the role of a mapping in Elasticsearch?

Ans:- A mapping in Elasticsearch defines the data type and properties of fields in an index.

24. How to perform aggregations in Elasticsearch?

Ans:- Aggregations in Elasticsearch allow for the analysis and summarization of data.

25. What is the role of the Ingest Node in Elasticsearch?

Ans:- The Ingest Node is a node in Elasticsearch that allows for the pre-processing of documents before indexing.

26. How to scale Elasticsearch horizontally?

Ans:- Horizontal scaling in Elasticsearch involves adding more nodes to the cluster to distribute the data and workload.

27. What is the purpose of the Cluster Coordination and Master nodes?

Ans:- Cluster Coordination and Master nodes are responsible for managing the cluster state and coordinating activities.

28. How does Elasticsearch handle conflicts during indexing?

Ans:- Elasticsearch uses a versioning system to handle conflicts during indexing.

29. Can Elasticsearch be integrated with other databases?

Ans:- Yes, Elasticsearch can be integrated with various databases and data sources.

30. How to secure Elasticsearch and Kibana?

Ans:- Security in Elasticsearch and Kibana involves setting up authentication, authorization, and encryption.

31. What is the role of a template in Elasticsearch?

Ans:- Templates in Elasticsearch allow for the pre-configuration of index settings and mappings.

32. What is the difference between a query and a filter in Elasticsearch?

Ans:- Queries in Elasticsearch are used for full-text search, while filters are used for exact matching and filtering.

33. How to upgrade Elasticsearch to a new version?

Ans:- Upgrading Elasticsearch involves careful planning and following the upgrade instructions provided by Elastic.

34. How to handle schema changes in Elasticsearch?

Ans:- Elasticsearch’s dynamic mapping allows for flexible handling of schema changes.

35. What is the purpose of the _source field in Elasticsearch?

Ans:- The _source field in Elasticsearch stores the original JSON document that was indexed.

36. How to perform a full-text search in Elasticsearch?

Ans:- Full-text search in Elasticsearch is performed using the Query DSL, which supports various types of queries.

37. What is the role of the Discovery Node in Elasticsearch?

Ans:- Discovery Nodes are responsible for detecting and maintaining the list of nodes in the cluster.

38. How does Elasticsearch handle tokenization and analysis of text fields?

Ans:- Elasticsearch uses analyzers to break down text into individual tokens and applies filters to process those tokens.

39. What are the common challenges in Elasticsearch performance tuning?

Ans:- Performance tuning may involve optimizing queries, increasing hardware resources, and adjusting index settings.

40. Can Elasticsearch be used for geospatial data?

Ans:- Yes, Elasticsearch supports geospatial data and provides geospatial queries and aggregations.

41. What is the role of the Master-eligible node in Elasticsearch?

Ans:- Master-eligible nodes can become master nodes and participate in cluster coordination.

42. How does the Elasticsearch cluster handle node failures?

Ans:- Elasticsearch is designed to handle node failures gracefully through mechanisms like shard replication and allocation.

43. What is the purpose of the Snapshot and Restore feature in Elasticsearch?

Ans:- The Snapshot and Restore feature allows for the backup and recovery of Elasticsearch data.

44. How to monitor an Elasticsearch cluster?

Ans:- Elasticsearch provides monitoring APIs, and third-party tools like the Elastic Stack’s X-Pack offer additional monitoring capabilities.

45. What are the common best practices for securing an Elasticsearch cluster?

Ans:- Best practices include securing network access, enabling authentication, and configuring role-based access control.

46. How to handle index aliasing in Elasticsearch?

Ans:- Index aliasing allows for the association of one or more indices with a single alias, providing flexibility in managing indices.

47. What is the role of the Snapshot Repository in Elasticsearch?

Ans:- The Snapshot Repository is a location where Elasticsearch stores its snapshots, typically in a remote file system or cloud storage.

48. How to handle index rollover for time-series data in Elasticsearch?

Ans:- Index rollover is a technique used to manage time-series data by creating new indices based on predefined conditions.

49. What is the purpose of the Mappings API in Elasticsearch?

Ans:- The Mappings API allows for the dynamic management of index mappings.

50. How to optimize storage usage in Elasticsearch?

Ans:- Techniques for optimizing storage usage include using appropriate data types, compressing data, and optimizing mappings.

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