Apache Cassandra Interview Questions and Answers for freshers

1. What is Apache Cassandra?

   • Answer: Apache 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 distribution across multiple nodes, tunable consistency levels, and support for large datasets.

3. Explain the concept of data modeling 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. Understanding data access patterns is crucial for efficient modeling.

4. What is a keyspace in Cassandra?

   • Answer: A keyspace is a top-level container for tables (column families) in Cassandra. It's similar to a database in relational databases.

5. What is a column family in Cassandra?

   • Answer: A column family (often referred to as a table) is a collection of rows sharing the same structure. It's where data is actually stored.

6. What is the primary key in Cassandra?

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

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

   • Answer: The partition key determines which node in the cluster will store a given row. The clustering key orders rows within a partition.

8. What is consistency in Cassandra?

   • Answer: Consistency refers to how up-to-date the data is across different nodes. Cassandra offers various consistency levels to balance consistency and availability.

9. Explain different consistency levels in Cassandra.

   • Answer: Examples include ONE, QUORUM, LOCAL_QUORUM, EACH_QUORUM, ALL. They specify the number of replicas that must acknowledge a write operation before it's considered successful. ONE is the least consistent, ALL is the most consistent but potentially slower.

10. What is replication in Cassandra?

    • Answer: Replication ensures data redundancy and high availability by storing copies of data on multiple nodes. This protects against data loss in case of node failures.

11. Explain different replication strategies in Cassandra.

    • Answer: Examples include SimpleStrategy and NetworkTopologyStrategy. SimpleStrategy replicates data across a specified number of nodes. NetworkTopologyStrategy considers data center awareness for better fault tolerance.

12. What is CQL (Cassandra Query Language)?

    • Answer: CQL is the primary query language used to interact with Cassandra. It's similar to SQL but with some key differences.

13. Write a CQL query to create a keyspace.

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

14. Write a CQL query to create a table.

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

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

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

16. Write a CQL query to select data from a table.

    • Answer: SELECT * FROM mytable; or SELECT name, age FROM mytable WHERE id = uuid();

17. What is data modeling best practices in Cassandra?

    • Answer: Design your primary key to support your query patterns, avoid wide rows, use appropriate data types, consider denormalization for improved performance, and understand the implications of different consistency levels.

18. How does Cassandra handle node failures?

    • Answer: Cassandra is designed to be fault-tolerant. When a node fails, the other nodes continue to operate, and the data is automatically replicated from the remaining replicas.

19. What is gossip protocol in Cassandra?

    • Answer: The gossip protocol is an efficient mechanism for nodes in a Cassandra cluster to communicate with each other and maintain cluster membership information, health status and data location.

20. What is the role of the Cassandra coordinator node?

    • Answer: The coordinator node is responsible for handling client requests and directing them to the appropriate nodes holding the data. It doesn't store data itself.

21. Explain the concept of hinted handoff in Cassandra.

    • Answer: Hinted handoff is a mechanism that allows Cassandra to temporarily store writes to a node that is currently unavailable. Once the node comes back online, the data is transferred.

22. What is tombstone in Cassandra?

    • Answer: A tombstone is a marker indicating that a column or row has been deleted. It remains for a configurable time (GC grace period) before being completely removed.

23. How to handle data consistency issues in Cassandra?

    • Answer: Choose the appropriate consistency level for your application's needs, use lightweight transactions (LWTs) when appropriate, and understand the tradeoffs between consistency and availability.

24. What is the difference between Cassandra and other NoSQL databases (e.g., MongoDB)?

    • Answer: Cassandra is a distributed, wide-column store database, optimized for high availability and scalability. MongoDB is a document database, offering more flexibility in schema but potentially less scalability and availability than Cassandra.

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

    • Answer: Optimize data modeling for query patterns, adjust heap size and other JVM settings, use appropriate consistency levels, ensure sufficient network bandwidth, and monitor cluster health.

26. How to monitor Cassandra cluster health?

    • Answer: Use tools like nodetool (command-line tool), JMX monitoring, and various third-party monitoring solutions to track metrics like CPU utilization, memory usage, disk I/O, and network latency.

27. What is compaction in Cassandra?

    • Answer: Compaction is a process that merges multiple small SSTables (Sorted Strings Tables) into larger, more efficient ones, improving read performance and reducing storage space.

28. Explain different types of compaction strategies in Cassandra.

    • Answer: SizeTieredCompactionStrategy (STCS) and LeveledCompactionStrategy (LCS) are common strategies. STCS is generally easier to manage but LCS can be more efficient in certain scenarios.

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

    • Answer: Using overly wide rows, neglecting data modeling best practices, not understanding consistency levels, and inefficient query patterns.

30. How do you troubleshoot connectivity issues in a Cassandra cluster?

    • Answer: Check network connectivity between nodes, verify firewall settings, review Cassandra logs for errors, and use nodetool to check cluster status and node health.

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

    • Answer: nodetool, cqlsh (CQL shell), JMX, Grafana, Prometheus, and various third-party monitoring tools.

32. How does Cassandra handle schema changes?

    • Answer: Cassandra allows for schema changes online without downtime using ALTER TABLE statements. However, careful planning is needed to avoid disrupting applications.

33. What is the difference between a read repair and a hinted handoff?

    • Answer: Read repair corrects inconsistencies between replicas during read operations, while hinted handoff buffers writes to unavailable nodes.

34. What is the role of the commit log in Cassandra?

    • Answer: The commit log is a write-ahead log that ensures data durability. All writes are first written to the commit log before being written to the memtable.

35. Explain the concept of memtable in Cassandra.

    • Answer: The memtable is an in-memory data structure that stores recently written data before it's flushed to disk as an SSTable.

36. What is an SSTable in Cassandra?

    • Answer: An SSTable (Sorted Strings Table) is an on-disk storage file that holds sorted data from a flushed memtable.

37. How does Cassandra achieve high availability?

    • Answer: High availability is achieved through replication, automatic failure detection, and the ability for nodes to seamlessly take over the responsibilities of failed nodes.

38. What is the purpose of using a counter column in Cassandra?

    • Answer: Counter columns are used to efficiently store and increment numerical values, such as counters or statistics.

39. How do you handle large data volume in Cassandra?

    • Answer: By distributing the data across multiple nodes, employing efficient data modeling, utilizing appropriate consistency levels, and optimizing query patterns.

40. Explain the concept of token in Cassandra.

    • Answer: Tokens are numerical representations of data partitions that determine which node in the cluster is responsible for storing a particular partition.

41. What are some common Cassandra security considerations?

    • Answer: Secure network configuration, authentication and authorization using appropriate mechanisms, data encryption, and regular security audits.

42. How do you back up and restore Cassandra data?

    • Answer: Use tools like `nodetool` for snapshots, or utilize third-party backup and restore solutions. The approach depends on the scale and complexity of your cluster.

43. What is the difference between Cassandra and traditional RDBMS?

    • Answer: Cassandra is a NoSQL database designed for horizontal scalability and high availability. RDBMS uses a relational model, typically with a fixed schema, and is generally not as scalable.

44. What are some use cases for Apache Cassandra?

    • Answer: Time series data, real-time analytics, social media feeds, online gaming, fraud detection, and other applications requiring high availability and scalability.

45. How would you troubleshoot slow queries in Cassandra?

    • Answer: Analyze query execution plans, check for inefficient data modeling, ensure proper indexing, monitor resource utilization (CPU, memory, I/O), and consider using tracing tools.

46. What are the advantages of using Cassandra over other NoSQL databases like HBase?

    • Answer: Cassandra offers better scalability and availability than HBase, and is generally easier to manage, especially for large clusters. HBase can be more efficient for some specific workloads requiring high-frequency updates.

47. Describe your experience with Cassandra (if any).

    • Answer: (This requires a personalized answer based on the candidate's experience. If they lack practical experience, they can discuss projects, coursework, or tutorials that demonstrate their understanding.)

48. Explain your understanding of Cassandra's architecture.

    • Answer: (This requires a detailed explanation covering nodes, replication, gossip protocol, coordinator nodes, and data flow. Again, a personalized response based on knowledge is needed.)

49. How familiar are you with different Cassandra drivers?

    • Answer: (Mention specific drivers like the Java driver, Python driver, etc. and describe any experience with them.)

50. How would you approach designing a Cassandra schema for a specific application (e.g., a social media platform)?

    • Answer: (This requires a detailed explanation of how the candidate would approach data modeling based on the requirements of a specific application. They should demonstrate an understanding of primary keys, partition keys, clustering keys, and data access patterns.)

51. What are your preferred methods for testing Cassandra applications?

    • Answer: (Discuss unit testing, integration testing, performance testing, and any relevant tools or frameworks.)

52. How would you handle data migration from a relational database to Cassandra?

    • Answer: (Discuss strategies like using ETL tools, incremental migration, and considerations for data transformation and schema mapping.)

53. What are some of the challenges you anticipate when working with Cassandra in a production environment?

    • Answer: (Discuss potential challenges such as data modeling complexities, performance tuning, managing large clusters, and handling failures.)

54. How do you stay up-to-date with the latest developments in Apache Cassandra?

    • Answer: (Mention resources like the official Apache Cassandra website, blogs, community forums, conferences, and any relevant online communities.)

55. Are you familiar with Cassandra's support for secondary indexes? Explain their use cases and potential drawbacks.

    • Answer: (Discuss the purpose of secondary indexes, when to use them, and their impact on performance. Mention the limitations compared to traditional indexes in RDBMS.)

56. Describe your experience with any scripting languages used in conjunction with Cassandra administration or development (e.g., Python, shell scripting).

    • Answer: (This requires a personalized answer reflecting the candidate's scripting skills and experience in automating Cassandra tasks.)

57. What are your thoughts on the trade-offs between consistency and availability in distributed systems like Cassandra?

    • Answer: (This is a conceptual question requiring a discussion of CAP theorem and how Cassandra addresses these trade-offs.)

58. Explain how Cassandra handles data partitioning and its impact on performance.

    • Answer: (Explain the concept of data partitioning, how it affects read and write performance, and the importance of choosing a proper partition key.)

59. How familiar are you with the concept of materialized views in Cassandra?

    • Answer: (Discuss the purpose of materialized views, when to use them, and the impact on storage and performance. Explain how they can improve query performance for certain access patterns.)

60. How would you design a Cassandra schema for a system that needs to track user activity on a website, including events like logins, page views, and purchases?

    • Answer: (Detailed schema design illustrating primary and clustering keys considering data access patterns.)

61. What is your approach to debugging performance issues in a Cassandra application?

    • Answer: (Explain systematic approach to debugging, including performance monitoring, query analysis, log review, profiling tools, and code inspection.)

62. Discuss the role of garbage collection in Cassandra and its impact on performance.

    • Answer: (Explain garbage collection mechanisms, how they impact performance, and tuning options for optimizing garbage collection.)

63. How does Cassandra handle schema updates without downtime? Explain the process.

    • Answer: (Describe the process of using `ALTER TABLE` statements and the underlying mechanisms that ensure minimal disruption during schema modifications.)

64. Describe your experience working with Cassandra's distributed architecture in a team environment.

    • Answer: (This question calls for a personalized response based on experience. If they lack experience, they can outline how they would collaborate effectively in a team setting on a Cassandra project.)

65. Explain how you would troubleshoot a Cassandra node that is consistently lagging behind the rest of the cluster.

    • Answer: (Outline a systematic diagnostic process to identify the root cause of the lagging node, including resource monitoring, log analysis, and potential hardware/software issues.)

66. What aspects of Cassandra's architecture make it suitable for handling large-scale, high-velocity data ingestion?

    • Answer: (Discuss aspects like its distributed nature, data partitioning, efficient write paths, and commit log mechanisms that enable efficient handling of high-volume data streams.)

67. What is your preferred approach to managing Cassandra's configuration in a production environment?

    • Answer: (Discuss configuration management tools and strategies, emphasizing best practices for managing Cassandra's YAML or JSON configuration files across multiple nodes.)

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