Cassandra Interview Questions and Answers for freshers

1. What is Cassandra?

   • Answer: Cassandra is a free and open-source, distributed, wide-column store, NoSQL database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.

2. What are the key features of Cassandra?

   • Answer: Key features include scalability, high availability, fault tolerance, linear scalability, data consistency options (e.g., strong, eventual), and flexible schema.

3. Explain the concept of distributed databases. How does Cassandra utilize this?

   • Answer: Distributed databases store data across multiple servers. Cassandra uses this by partitioning data across many nodes, enabling high availability and scalability. If one node fails, others continue operating.

4. What is a data model in Cassandra?

   • Answer: Cassandra uses a wide-column store model. Data is organized into keyspaces, column families (tables), rows (identified by a primary key), and columns (name-value pairs).

5. Explain the concept of keyspaces in Cassandra.

   • Answer: Keyspaces are the highest level of organization in Cassandra, analogous to databases in relational databases. They provide a way to logically group related column families.

6. What are column families in Cassandra?

   • Answer: Column families are similar to tables in relational databases. They group rows with similar characteristics and are the primary unit of data organization within a keyspace.

7. What is a primary key in Cassandra?

   • Answer: The primary key uniquely identifies a row in a column family. It can be composed of a partition key and a clustering key.

8. Explain the difference between partition key and clustering key.

   • Answer: The partition key determines how data is distributed across nodes. The clustering key orders rows within a partition on a single node.

9. What is consistency in Cassandra?

   • Answer: Consistency refers to how quickly data changes made on one node are reflected on other nodes. Cassandra offers different consistency levels (e.g., ONE, QUORUM, LOCAL_QUORUM, ALL) to balance consistency and availability.

10. Explain the concept of read and write consistency levels in Cassandra.

    • Answer: Read and write consistency levels control the number of replicas that must acknowledge a read or write operation before it's considered successful. Higher consistency levels improve data accuracy but can reduce availability.

11. What is replication in Cassandra?

    • Answer: Replication is the process of copying data to multiple nodes for fault tolerance and high availability. Cassandra supports various replication strategies (e.g., SimpleStrategy, NetworkTopologyStrategy).

12. Explain different replication strategies in Cassandra.

    • Answer: SimpleStrategy replicates data across a fixed number of nodes. NetworkTopologyStrategy replicates data based on data center and rack awareness for better fault tolerance.

13. What is data modeling in Cassandra? Why is it important?

    • Answer: Data modeling involves designing the structure of your data in Cassandra. It's crucial for optimal performance, scalability, and efficient data retrieval.

14. How does Cassandra handle data distribution and partitioning?

    • Answer: Cassandra uses the partition key to distribute data across nodes using consistent hashing. Data within a partition is stored together on a single node.

15. What is CQL (Cassandra Query Language)?

    • Answer: CQL is the query language used to interact with Cassandra. It's similar to SQL but with differences tailored to Cassandra's wide-column store model.

16. Write a CQL query to create a keyspace.

    • Answer: CREATE KEYSPACE mykeyspace WITH replication = {'class': 'SimpleStrategy', 'replication_factor': 3};

17. Write a CQL query to create a table.

    • Answer: CREATE TABLE mytable (id int PRIMARY KEY, name text, age int);

18. Write a CQL query to insert data into a table.

    • Answer: INSERT INTO mytable (id, name, age) VALUES (1, 'John Doe', 30);

19. Write a CQL query to retrieve data from a table.

    • Answer: SELECT * FROM mytable WHERE id = 1;

20. What are some common Cassandra data modeling best practices?

    • Answer: Design for wide rows, minimize the number of partitions accessed per query, use appropriate data types, avoid excessive column mutations, and consider data locality.

21. How does Cassandra handle failures?

    • Answer: Cassandra handles failures through replication and fault tolerance. If a node fails, the data is still available from its replicas. The system automatically recovers.

22. What is the role of the gossip protocol in Cassandra?

    • Answer: The gossip protocol is used for node discovery, failure detection, and data consistency management within the Cassandra cluster.

23. What are some tools used for managing and monitoring Cassandra?

    • Answer: Tools include Nodetool (command-line utility), cqlsh (CQL shell), and monitoring systems like Grafana and Prometheus.

24. Explain the concept of compaction in Cassandra.

    • Answer: Compaction merges smaller SSTables (Sorted String Tables, data files) into larger ones, improving read performance and reducing storage space.

25. What are some common performance tuning techniques for Cassandra?

    • Answer: Techniques include optimizing data modeling, adjusting heap size, using appropriate consistency levels, and tuning compaction strategy.

26. How does Cassandra handle schema changes?

    • Answer: Cassandra allows for flexible schema changes. Adding new columns or modifying existing ones is generally non-disruptive to ongoing operations.

27. What are some advantages of using Cassandra over relational databases?

    • Answer: Advantages include superior scalability, high availability, fault tolerance, and better handling of massive datasets and high write loads.

28. What are some limitations of using Cassandra?

    • Answer: Limitations include its NoSQL nature (complex joins are difficult), potential for data inconsistency depending on chosen consistency levels, and the need for careful data modeling.

29. What are the different types of Cassandra data types?

    • Answer: Cassandra offers various data types like ascii, bigint, blob, boolean, counter, decimal, double, float, inet, int, text, timestamp, uuid, varchar, and more.

30. Explain the concept of lightweight transactions in Cassandra.

    • Answer: Lightweight transactions (LWTs) allow for conditional updates to data within a single partition. They are useful for preventing race conditions in specific scenarios.

31. How does Cassandra handle data backups and recovery?

    • Answer: Backups can be performed using tools like sstableloader and nodetool. Recovery involves restoring the backups to restore data to a previous point in time.

32. What is the difference between Cassandra and other NoSQL databases like MongoDB?

    • Answer: Cassandra is a wide-column store designed for high availability and scalability, while MongoDB is a document database with a different data model and focus on flexible schema.

33. Describe a scenario where Cassandra would be a good choice for a database.

    • Answer: A good scenario would be a high-volume, high-availability application like a social media platform, a large e-commerce website, or a system processing IoT sensor data.

34. Describe a scenario where Cassandra would NOT be a good choice for a database.

    • Answer: Cassandra might not be a good choice for applications requiring complex joins or ACID properties across multiple partitions or if the data size is relatively small and doesn't require high scalability.

35. What is the role of the `ALLOW FILTERING` clause in CQL?

    • Answer: `ALLOW FILTERING` allows queries that filter on clustering columns, but these queries can be significantly less efficient than queries that filter on the partition key. It should be used sparingly.

36. Explain the concept of tombstones in Cassandra.

    • Answer: Tombstones mark deleted data. They are eventually removed during compaction but can temporarily affect storage space and performance.

37. How does Cassandra handle schema updates? Is there downtime?

    • Answer: Schema updates are usually non-disruptive; there's typically no downtime. Cassandra allows adding columns and other schema changes online.

38. Explain the concept of hinted handoff in Cassandra.

    • Answer: Hinted handoff allows writes to be stored temporarily on a different node if the target node is down. Once the target node recovers, the data is transferred.

39. What are some common Cassandra anti-patterns to avoid?

    • Answer: Anti-patterns include using too many clustering columns, overly wide rows, poorly designed partition keys, and neglecting proper data modeling.

40. What is the use of the `COUNTER` data type in Cassandra?

    • Answer: The `COUNTER` data type is used to store incrementing and decrementing values atomically, ideal for counters and metrics.

41. How can you improve query performance in Cassandra?

    • Answer: By optimizing data modeling, using appropriate data types, leveraging the partition key effectively, and avoiding `ALLOW FILTERING` unless absolutely necessary.

42. What are some security considerations for Cassandra?

    • Answer: Security considerations include proper authentication, authorization, encryption of data at rest and in transit, and regular security audits.

43. Explain the concept of Cassandra's token range.

    • Answer: Cassandra uses token ranges to distribute data across nodes. Each node is responsible for a specific range of tokens, which are derived from the partition key.

44. What is the role of the `nodetool` command?

    • Answer: `nodetool` is a command-line utility for managing and monitoring Cassandra clusters. It allows performing various administrative tasks.

45. Explain the concept of materialized views in Cassandra.

    • Answer: Materialized views pre-compute and store the results of queries, improving performance for frequently accessed data subsets.

46. What are some common monitoring metrics for Cassandra?

    • Answer: Common metrics include CPU usage, memory usage, disk space, read/write latency, and compaction performance.

47. How does Cassandra handle updates to data?

    • Answer: Cassandra updates data by overwriting existing data with new values. There is no in-place modification of individual column values.

48. What are the advantages of using a distributed database like Cassandra?

    • Answer: Advantages include scalability, high availability, fault tolerance, and the ability to handle large volumes of data and high write loads.

49. What are some potential challenges in managing a large Cassandra cluster?

    • Answer: Challenges include ensuring data consistency across nodes, managing schema updates, handling failures effectively, and monitoring performance.

50. Explain the concept of "write-ahead logging" in Cassandra.

    • Answer: Write-ahead logging ensures data durability by writing data to a log file before writing to disk, preventing data loss in case of crashes.

51. How can you troubleshoot performance issues in a Cassandra cluster?

    • Answer: Troubleshooting involves analyzing logs, monitoring metrics, using `nodetool` commands, and examining query performance through profiling.

52. What are the different ways to deploy Cassandra?

    • Answer: Cassandra can be deployed on bare metal servers, virtual machines, or in cloud environments like AWS, Azure, or GCP.

53. How does Cassandra handle data deletion?

    • Answer: Cassandra deletes data by marking it as deleted using a tombstone. The actual removal happens during compaction.

54. What is the importance of using appropriate data types in Cassandra?

    • Answer: Using appropriate data types is crucial for efficient data storage, retrieval, and query performance.

55. Explain the difference between a local quorum and a quorum in Cassandra.

    • Answer: Quorum involves a majority of nodes across the entire cluster, while local quorum refers to a majority of nodes within a single data center.

56. What is the role of the Cassandra seed nodes?

    • Answer: Seed nodes provide an initial set of nodes for new nodes to join the cluster during bootstrapping.

57. How can you monitor the health of a Cassandra cluster?

    • Answer: By monitoring metrics like CPU, memory, disk I/O, and network usage using tools like Nodetool and monitoring systems.

58. What is the purpose of the `gc_grace_seconds` setting in Cassandra?

    • Answer: `gc_grace_seconds` determines how long tombstones are retained before being deleted, balancing data consistency and storage.

59. How does Cassandra's architecture contribute to its high availability?

    • Answer: Cassandra's decentralized architecture, replication, and fault tolerance mechanisms contribute to its high availability.

60. What are some best practices for designing partition keys in Cassandra?

    • Answer: Best practices include choosing a partition key that evenly distributes data, avoids hot spots, and aligns with query patterns.

61. How can you optimize Cassandra for read performance?

    • Answer: By designing for wide rows, minimizing partition key access, choosing suitable consistency levels, and optimizing compaction strategy.

62. How can you optimize Cassandra for write performance?

    • Answer: By reducing the number of partitions written to, using lightweight transactions where appropriate, and optimizing the partition key distribution.

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