Cassandra Interview Questions & Answers

Basic Concepts:

1. What is Apache Cassandra?

   • A: Apache Cassandra is a highly scalable, distributed NoSQL database management system designed to handle large amounts of data across multiple commodity servers without a single point of failure.

2. Explain the CAP theorem and how it relates to Cassandra.

   • A: The CAP theorem states that a distributed system cannot simultaneously provide all three guarantees: Consistency, Availability, and Partition Tolerance. Cassandra is designed to be highly available and partition-tolerant, prioritizing availability over strict consistency.

3. How does Cassandra achieve high availability?

   • A: Cassandra achieves high availability through a distributed architecture with no single point of failure. Data is replicated across multiple nodes, and each node in the cluster is capable of serving read and write requests.

4. What is eventual consistency in Cassandra?

   • A: Eventual consistency in Cassandra means that, given enough time, all replicas of a piece of data will converge to the same value. It allows for immediate availability and is suitable for scenarios where consistency can be compromised for performance.

5. What is the key difference between Apache Cassandra and traditional relational databases?

   • A: Cassandra is a NoSQL database designed for distributed, horizontally scalable architectures, while traditional relational databases are often designed for vertical scaling on a single server.

Data Modeling:

6. Explain the concept of a partition key in Cassandra.

   • A: A partition key is a field or set of fields that determines the distribution of data across nodes in a Cassandra cluster. All rows with the same partition key are stored together on the same node.

7. What is a compound primary key in Cassandra?

   • A: A compound primary key in Cassandra consists of multiple columns, where one or more columns are used as the partition key and the remaining columns form the clustering key.

8. How does Cassandra handle writes?

   • A: Cassandra uses a write-ahead log and a distributed commit log to ensure durability. Writes are first written to a commit log and then to an in-memory structure called the memtable. Eventually, data is flushed to SSTables on disk.

9. Explain the concept of a secondary index in Cassandra.

   • A: A secondary index in Cassandra allows querying data based on a non-primary key column. However, using secondary indexes can lead to performance issues and should be used judiciously.

10. What is denormalization in the context of Cassandra?

    • A: Denormalization in Cassandra involves storing redundant copies of data to optimize read performance. It is done to minimize the need for complex joins and improve query response times.

Architecture and Cluster Management:

11. How does Cassandra handle read requests?

    • A: Cassandra reads are served by querying multiple nodes in parallel. The coordinator node gathers the data from the required replicas and responds to the client.

12. What is a snitch in Cassandra?

    • A: A snitch is a component in Cassandra that determines the proximity and location of nodes in the cluster. It is used to optimize data distribution and minimize latency.

13. Explain the role of the Gossip Protocol in Cassandra.

    • A: The Gossip Protocol is used by Cassandra nodes to communicate with each other and share information about the state of the cluster, including membership changes, node health, and network topology.

14. How does Cassandra ensure fault tolerance?

    • A: Cassandra achieves fault tolerance by replicating data across multiple nodes. Each node in the cluster is responsible for a range of data, and replicas are distributed to other nodes to ensure redundancy.

15. What is a hinted handoff in Cassandra?

    • A: A hinted handoff occurs when a node is temporarily unavailable, and another node temporarily stores the write request on its behalf. Once the node becomes available, the hinted handoff is replayed.

Query Language (CQL):

16. What is CQL (Cassandra Query Language)?

    • A: CQL is a query language for interacting with Apache Cassandra, designed to resemble SQL. It provides a more SQL-like syntax for creating, querying, and managing Cassandra databases.

17. How do you create a keyspace in Cassandra using CQL?

    • A: CREATE KEYSPACE keyspace_name WITH replication = {'class': 'SimpleStrategy', 'replication_factor': N};

18. Explain the purpose of the CREATE TABLE statement in CQL.

    • A: The CREATE TABLE statement is used to define a table in Cassandra, specifying the columns, data types, and primary key.

19. How can you update data in Cassandra using CQL?

    • A: UPDATE table_name SET column1 = value1 WHERE condition;

20. What is the purpose of the SELECT statement in CQL?

    • A: The SELECT statement is used to query data from a table in Cassandra. It supports filtering based on the partition key, clustering key, and secondary indexes.

Performance Tuning:

21. How can you optimize read performance in Cassandra?

    • A: Strategies include data denormalization, using proper partition keys, using appropriate data types, and minimizing the use of secondary indexes.

22. What is compaction in Cassandra, and why is it important?

    • A: Compaction is the process of merging multiple SSTables into a single SSTable. It is important for maintaining the efficiency of data storage and improving read performance.

23. How can you scale a Cassandra cluster?

    • A: Scaling a Cassandra cluster involves adding more nodes to distribute the data and load. Horizontal scaling is the primary method, allowing the cluster to handle increased traffic.

24. Explain the role of the Snappy compression algorithm in Cassandra.

    • A: Snappy compression is used in Cassandra to compress SSTables, reducing storage requirements and improving read performance.

25. How does Cassandra handle tombstones, and why are they important?

    • A: Tombstones are markers used to signify deleted data in Cassandra. They are essential for eventual consistency and the proper functioning of distributed deletes.

Security and Authentication:

26. How does Cassandra handle authentication and authorization?
    • A: Cassandra uses roles and permissions for authentication and authorization. Authentication can be configured using mechanisms like PasswordAuthenticator or

LDAP, and roles can be assigned specific permissions.

27. What is the purpose of the DESCRIBE command in CQL?

    • A: The DESCRIBE command is used to display information about keyspaces, tables, columns, and other schema-related details.

28. How can you configure SSL/TLS in Cassandra for secure communication?

    • A: SSL/TLS can be configured in the Cassandra server by updating the cassandra.yaml file with SSL-related settings. This includes specifying the keystore and truststore files.

29. What is the purpose of the GRANT and REVOKE statements in CQL?

    • A: GRANT is used to assign specific permissions to a role, while REVOKE is used to remove those permissions.

30. How do you enable client-to-node encryption in Cassandra?

    • A: Client-to-node encryption can be enabled by configuring the client_encryption_options in the cassandra.yaml file.

Maintenance and Monitoring:

31. How can you perform backups and restores in Cassandra?

    • A: Backups can be performed using tools like nodetool or by taking snapshots. Restoration involves copying the snapshot files to the appropriate nodes.

32. What is the purpose of the nodetool utility in Cassandra?

    • A: nodetool is a command-line utility that allows administrators to perform various tasks such as monitoring, repairing, and managing a Cassandra cluster.

33. How do you monitor the performance of a Cassandra cluster?

    • A: Monitoring can be done using tools like nodetool, JMX (Java Management Extensions), and third-party monitoring solutions. Key metrics include read/write latency, compaction statistics, and node status.

34. What is compaction in Cassandra, and why is it important?

    • A: Compaction is the process of merging multiple SSTables into a single SSTable. It is important for maintaining the efficiency of data storage and improving read performance.

35. How can you repair data in Cassandra?

    • A: Data repair in Cassandra involves identifying inconsistencies between replicas and synchronizing them. It can be done using the nodetool repair command.

Advanced Concepts:

36. Explain the concept of a materialized view in Cassandra.

    • A: A materialized view in Cassandra is a precomputed table that stores the result of a SELECT query. It is used to optimize read performance for specific query patterns.

37. What is the purpose of the ALLOW FILTERING option in CQL queries?

    • A: The ALLOW FILTERING option allows querying on columns that are not part of the primary key or a secondary index. However, it can lead to performance issues and should be used judiciously.

38. How does Cassandra handle tombstones, and why are they important?

    • A: Tombstones are markers used to signify deleted data in Cassandra. They are essential for eventual consistency and the proper functioning of distributed deletes.

39. What is a lightweight transaction in Cassandra?

    • A: A lightweight transaction in Cassandra uses the IF clause in queries to ensure that a write operation is executed only if a certain condition is met.

40. Explain the role of the nodetool repair command in Cassandra.

    • A: The nodetool repair command in Cassandra is used to synchronize data between replicas, ensuring consistency and data integrity.

Industry Trends and Best Practices:

41. What are some best practices for data modeling in Cassandra?

    • A: Best practices include selecting appropriate partition keys, using denormalization for read optimization, and avoiding the use of secondary indexes in large tables.

42. How can Cassandra be integrated with other data processing frameworks like Apache Spark?

    • A: Cassandra can be integrated with Apache Spark using the Spark Connector, allowing for seamless data transfer and processing.

43. What is the role of Apache Cassandra in a microservices architecture?

    • A: Cassandra can be used as a data store in a microservices architecture, providing a scalable and highly available solution for handling large volumes of data.

44. Explain the role of the Snappy compression algorithm in Cassandra.

    • A: Snappy compression is used in Cassandra to compress SSTables, reducing storage requirements and improving read performance.

45. How can you ensure data consistency in a multi-datacenter Cassandra deployment?

    • A: Data consistency in a multi-datacenter deployment can be ensured by configuring replication strategies, adjusting consistency levels, and monitoring network latency.

Troubleshooting:

46. How do you troubleshoot performance issues in a Cassandra cluster?

    • A: Troubleshooting performance issues involves analyzing metrics, checking for network bottlenecks, reviewing logs, and using tools like nodetool.

47. What are common causes of read and write timeouts in Cassandra?

    • A: Read and write timeouts in Cassandra can be caused by factors such as slow network, high load on nodes, or inefficient data modeling.

48. How can you identify and resolve data inconsistency issues in Cassandra?

    • A: Data inconsistency issues can be identified using tools like nodetool repair and resolved by synchronizing data between replicas.

49. What is the purpose of the Cassandra stress tool?

    • A: The Cassandra stress tool is used for simulating read and write workloads on a Cassandra cluster to test its performance and identify potential issues.

50. How can you handle schema changes in a live Cassandra cluster?

    • A: Schema changes in a live Cassandra cluster can be managed using tools like cqlsh or by scripting the changes and applying them gradually to nodes.