Cassandra Interview Questions and Answers

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 distribution across multiple nodes, and high write performance.

3. Explain the concept of "wide-column store" in Cassandra.

   • Answer: A wide-column store organizes data into rows and columns, but unlike relational databases, columns within a row are grouped into column families. This allows for flexible schema and efficient handling of large, sparse datasets.

4. How does Cassandra achieve high availability?

   • Answer: Cassandra achieves high availability through replication. Data is replicated across multiple nodes in a cluster. If one node fails, the data is still accessible from other replicas.

5. What is a Cassandra cluster?

   • Answer: A Cassandra cluster is a collection of nodes working together to store and manage data. Each node contributes its storage and processing capabilities to the overall system.

6. Explain the concept of consistency and availability in Cassandra.

   • Answer: Cassandra offers a configurable trade-off between consistency and availability using its consistency levels. Strong consistency ensures all nodes see the same data immediately, but can impact availability. Quorum-based consistency balances consistency and availability.

7. What are consistency levels in Cassandra?

   • Answer: Consistency levels determine the number of replicas that must acknowledge a write operation before the operation is considered successful. Examples include ONE, TWO, THREE, QUORUM, ALL, LOCAL_ONE, LOCAL_QUORUM.

8. What is a data center in Cassandra?

   • Answer: A data center represents a physical or logical grouping of nodes within a Cassandra cluster. It's used for managing replication strategies and improving fault tolerance across geographically separated locations.

9. What is a keyspace in Cassandra?

   • Answer: A keyspace is a namespace that logically groups related column families. It's analogous to a database in a relational database management system.

10. What is a column family in Cassandra?

    • Answer: A column family is a collection of columns sharing the same properties. It is analogous to a table in a relational database, but more flexible in terms of schema.

11. What is a partition key in Cassandra?

    • Answer: The partition key is the primary key component that determines how data is distributed across nodes in the cluster. It's crucial for performance and data locality.

12. What is a clustering key in Cassandra?

    • Answer: The clustering key is an optional part of the primary key used to sort data within a partition. It helps organize data within a partition in a specific order.

13. Explain the difference between a partition key and a clustering key.

    • Answer: The partition key distributes data across nodes, while the clustering key orders data within a single partition on a node.

14. What are the different data types supported by Cassandra?

    • Answer: Cassandra supports a wide variety of data types including ascii, bigint, blob, boolean, counter, decimal, double, float, inet, int, timestamp, text, timeuuid, uuid, varchar, varint, and more.

15. What is CQL?

    • Answer: CQL (Cassandra Query Language) is the query language used to interact with Cassandra. It's similar to SQL but with features specific to Cassandra's data model.

16. How does Cassandra handle data replication?

    • Answer: Cassandra uses a configurable replication factor to determine the number of replicas created for each partition. This ensures data redundancy and high availability.

17. What are the different replication strategies in Cassandra?

    • Answer: Common replication strategies include SimpleStrategy and NetworkTopologyStrategy. SimpleStrategy replicates data across a specified number of nodes, while NetworkTopologyStrategy considers data center topology for more robust replication.

18. How does Cassandra handle data compaction?

    • Answer: Cassandra periodically performs compaction to merge smaller SSTables (Sorted String Tables) into larger ones, improving read performance and reducing storage overhead.

19. What are SSTables in Cassandra?

    • Answer: SSTables (Sorted String Tables) are immutable files that store Cassandra data on disk. They are sorted by row key, which allows for efficient data retrieval.

20. Explain the concept of hinted handoff in Cassandra.

    • Answer: Hinted handoff is a mechanism that allows Cassandra to temporarily store write requests when a node is unavailable. Once the node recovers, these hinted handoffs are replayed, ensuring data consistency.

21. What is tombstone in Cassandra?

    • Answer: A tombstone in Cassandra indicates that a row or column has been deleted. It's a marker that prevents the old data from being returned but does not immediately reclaim storage space.

22. How can you monitor a Cassandra cluster?

    • Answer: Cassandra clusters can be monitored using tools like nodetool, jmx, and various third-party monitoring solutions. These tools provide metrics on cluster health, performance, and resource utilization.

23. What are some common Cassandra performance tuning techniques?

    • Answer: Techniques include optimizing partition key design, choosing appropriate consistency levels, configuring proper replication strategies, adjusting heap size, and ensuring sufficient disk I/O.

24. How do you troubleshoot performance issues in Cassandra?

    • Answer: Troubleshooting involves analyzing logs, monitoring metrics, checking for resource bottlenecks (CPU, memory, disk I/O), examining query performance, and reviewing the schema design.

25. What is the role of the commitlog in Cassandra?

    • Answer: The commitlog is a write-ahead log that ensures data durability. All writes are appended to the commitlog before being written to the SSTables.

26. How does Cassandra handle schema changes?

    • Answer: Cassandra's schema is flexible and allows for schema changes without downtime. New columns can be added to existing column families without impacting existing data.

27. Explain the concept of anti-entropy in Cassandra.

    • Answer: Anti-entropy is a process that automatically detects and repairs inconsistencies between replicas. It helps maintain data consistency across the cluster.

28. What is gossip protocol in Cassandra?

    • Answer: The gossip protocol is a peer-to-peer communication mechanism used by Cassandra nodes to share information about the cluster state, including node status, data location, and other crucial metrics.

29. How does Cassandra handle data backup and recovery?

    • Answer: Cassandra provides mechanisms for backing up data, primarily through snapshots and tools like `nodetool` for creating backups. Recovery involves restoring from these backups.

30. What are some common Cassandra use cases?

    • Answer: Common use cases include handling large-scale social media feeds, managing user profiles, storing time-series data, creating recommendation engines, and supporting real-time analytics.

31. What are the advantages of using Cassandra over relational databases?

    • Answer: Advantages include better scalability, higher availability, better handling of large datasets, and higher write performance for certain workloads.

32. What are the limitations of Cassandra?

    • Answer: Limitations include less mature tooling compared to relational databases, complexity in managing large clusters, and challenges with complex joins and transactions.

33. What are some alternative NoSQL databases to Cassandra?

    • Answer: Alternatives include MongoDB, HBase, Couchbase, and Riak.

34. How does Cassandra handle data modeling?

    • Answer: Cassandra data modeling focuses on designing efficient partition keys and clustering keys to optimize read and write performance. Understanding access patterns is crucial.

35. Explain the concept of lightweight transactions in Cassandra.

    • Answer: Cassandra's lightweight transactions, using `paxos`, offer limited transaction support within a single partition. They're not designed for complex, multi-partition transactions.

36. How can you secure a Cassandra cluster?

    • Answer: Security involves using strong passwords, enabling authentication, configuring SSL/TLS encryption, managing access controls, and regularly patching vulnerabilities.

37. What is the role of the seeds nodes in Cassandra?

    • Answer: Seed nodes provide initial contact points for new nodes joining the cluster. They help bootstrap the cluster and allow other nodes to discover each other.

38. How does Cassandra handle schema updates during upgrades?

    • Answer: Cassandra's schema is typically updated incrementally using CQL statements. The process is designed to be non-disruptive.

39. What is the difference between a counter column and a regular column in Cassandra?

    • Answer: Counter columns are designed for atomic increment/decrement operations, useful for tracking metrics, while regular columns are for general-purpose data storage.

40. Explain the concept of read repair in Cassandra.

    • Answer: Read repair is a process that detects and corrects inconsistencies between replicas during read operations, ensuring data consistency.

41. What are some best practices for designing Cassandra tables?

    • Answer: Best practices include designing efficient partition keys, considering data distribution, using appropriate clustering keys, and avoiding wide rows.

42. How can you improve the performance of Cassandra queries?

    • Answer: Performance improvements involve using efficient CQL queries, optimizing data modeling, tuning the cluster, and using appropriate consistency levels.

43. What is the role of the `nodetool` command-line utility?

    • Answer: `nodetool` is a command-line interface for managing and monitoring Cassandra clusters. It allows for tasks like checking cluster health, performing repairs, and managing nodes.

44. Explain Cassandra's use of bloom filters.

    • Answer: Bloom filters help improve read performance by quickly determining if a given key exists in a particular SSTable, avoiding unnecessary disk I/O.

45. How does Cassandra handle schema validation?

    • Answer: Cassandra performs schema validation at write time, ensuring that data written to the database conforms to the defined schema.

46. What are some common Cassandra error messages and how to troubleshoot them?

    • Answer: Common errors include timeout errors, unavailable exceptions, and various connection issues. Troubleshooting involves checking cluster health, network connectivity, resource usage, and query efficiency.

47. How do you manage Cassandra's storage capacity?

    • Answer: Storage management includes monitoring disk space, configuring appropriate disk sizes, using data compaction to reduce storage overhead, and implementing data archiving strategies.

48. What are some common tools for administering Cassandra?

    • Answer: Tools include `nodetool`, JMX monitoring, and various third-party dashboards and monitoring solutions.

49. How does Cassandra handle different data types within a column family?

    • Answer: Cassandra allows different data types within a column family, though it's important to choose appropriate data types for each column to optimize storage and performance.

50. Describe Cassandra's approach to garbage collection.

    • Answer: Cassandra uses a combination of techniques to manage garbage collection, including compaction and tombstones, to reclaim storage space from deleted data.

51. Explain the concept of token in Cassandra.

    • Answer: Tokens are numerical representations of partition keys used to distribute data across nodes in the cluster. They ensure data is spread evenly across the cluster.

52. How does Cassandra handle concurrent writes to the same partition?

    • Answer: Cassandra handles concurrent writes using its Paxos-based lightweight transactions and atomic counters. Write operations within a single partition are serialized.

53. What are the implications of choosing a poorly designed partition key?

    • Answer: A poorly designed partition key can lead to data hotspots, uneven data distribution, and reduced performance, impacting both read and write operations.

54. Explain how to optimize Cassandra for read-heavy workloads.

    • Answer: Optimization involves designing efficient partition keys, using appropriate clustering keys, tuning caching settings, and considering read repair strategies.

55. How to optimize Cassandra for write-heavy workloads.

    • Answer: Optimization involves choosing appropriate consistency levels, ensuring sufficient resources (CPU, memory, disk I/O), and designing partitions to minimize write contention.

56. What are the different ways to scale Cassandra?

    • Answer: Scaling involves adding more nodes to the cluster (horizontal scaling) and increasing resources per node (vertical scaling). Horizontal scaling is generally preferred for Cassandra.

57. How does Cassandra handle failures of nodes in the cluster?

    • Answer: Cassandra is designed to tolerate node failures gracefully. Data is replicated, and the system continues to operate without disruption. Hinted handoffs ensure data consistency during recovery.

58. What is the difference between Cassandra's `SELECT` and `ALLOW FILTERING` statements?

    • Answer: `SELECT` typically queries data based on the partition key, while `ALLOW FILTERING` allows querying beyond the partition key, often leading to performance penalties.

59. What are the advantages of using Cassandra with Spark?

    • Answer: Combining Cassandra with Spark allows for efficient distributed processing of large datasets stored in Cassandra. Spark provides tools for distributed data analysis and transformation.

60. Explain the role of compaction strategies in Cassandra.

    • Answer: Compaction strategies determine how Cassandra merges smaller SSTables into larger ones. Different strategies are optimized for various workloads and storage requirements.

61. How do you handle data migration in Cassandra?

    • Answer: Migration involves using tools and strategies to move data between different Cassandra clusters or versions. This often includes techniques like incremental copying and data validation.

62. What are some best practices for monitoring Cassandra's performance?

    • Answer: Best practices involve regularly monitoring key metrics (CPU, memory, disk I/O, latency), using monitoring tools, setting up alerts, and analyzing log files.

63. How does Cassandra handle data updates?

    • Answer: Updates involve writing new data to the database, potentially overwriting existing data. Cassandra manages this efficiently by using its write-ahead log and compaction.

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