Commonly asked Cassandra famous interview questions and answers.

1. What is Apache Cassandra?
   • Apache Cassandra is a distributed NoSQL database system designed to handle large amounts of data across many commodity servers, providing high availability and fault tolerance with no single point of failure.
2. What are the key features of Apache Cassandra?
   • Some of the key features of Apache Cassandra include:
     • Scalability and high availability
     • Distributed architecture with no single point of failure
     • Tunable consistency
     • Support for multiple data centers
     • Automatic data partitioning and replication
     • Column-family based data model
     • Built-in support for map/reduce operations
     • Support for CQL (Cassandra Query Language) and SQL-like syntax

3. How does Cassandra provide fault tolerance?
   • Cassandra provides fault tolerance through its distributed architecture and data replication.
   • Data is automatically partitioned and replicated across multiple nodes, with each node responsible for a portion of the data.
   • If a node fails, the data it was responsible for is automatically replicated to other nodes in the cluster, ensuring that data is still available even in the event of a node failure.
4. What is a cluster in Cassandra?
   • A cluster in Cassandra is a group of nodes that work together to store and manage data.
   • A cluster can consist of one or more nodes, with each node responsible for a portion of the data.
   • Cassandra uses a gossip protocol to keep track of the nodes in the cluster and ensure that data is distributed and replicated properly.
   • A cluster can consist of multiple data centers and can span multiple geographic regions.
   • A Cassandra cluster is designed to be distributed and scalable, and can span multiple data centers or geographic regions.
   • Nodes in a cluster communicate with each other using the gossip protocol and the CQL protocol.
   • Each node in the cluster is responsible for a subset of the data, and the cluster as a whole provides fault tolerance and high availability.
5. What is a keyspace in Cassandra?
   • A keyspace in Cassandra is a namespace that defines how data is distributed across nodes in a cluster.
   • Each keyspace contains one or more column families, which define the structure and properties of the data stored in that keyspace.
   • A keyspace in Cassandra is a container that holds column families, which are the basic units of data storage in Cassandra.
   • A keyspace can be thought of as a namespace that defines the data replication strategy, data compression settings, and other configuration options for the column families it contains.
   • A keyspace in Cassandra is similar to a database in a relational database system.
   • Each keyspace in Cassandra has a replication strategy that determines how data is replicated across nodes in the cluster.
   • Keyspaces can be created and managed using CQL statements or using a client library for a programming language such as Java, Python, or Node.js.
   • A keyspace in Cassandra is a logical container for one or more tables.
   • A keyspace defines the replication strategy and replication factor for the tables that it contains, as well as other configuration settings such as compaction and compression settings.
   • A keyspace can be thought of as roughly equivalent to a database in a traditional RDBMS.
6. What is a column family in Cassandra?
   • A column family in Cassandra is a collection of columns that are stored together as a unit.
   • Each row in a column family has a key that uniquely identifies that row.
   • Column families can be used to model a variety of data structures, including key-value stores, time series data, and more.
   • A column family in Cassandra is a collection of rows that share the same schema.
   • Each row in a column family can have a different set of columns, and the columns themselves can have different data types.
   • Column families are the basic units of data storage in Cassandra.
   • A column family in Cassandra is similar to a table in a relational database system.
   • Each column family in Cassandra has a set of columns and a primary key that is used to uniquely identify rows.
   • Column families can be created and managed using CQL statements or using a client library for a programming language such as Java, Python, or Node.js.
7. What is the CAP theorem and how does it relate to Cassandra?
   • The CAP theorem is a concept in distributed computing that states that it is impossible for a distributed system to provide more than two out of the following three guarantees: consistency, availability, and partition tolerance.
   • Cassandra is designed to provide partition tolerance and availability, with tunable consistency. This means that in the event of a network partition, Cassandra will continue to function and provide availability, but may sacrifice some consistency guarantees.
8. What is a node in Cassandra?
   • A node in Cassandra is a single instance of the Cassandra software running on a machine.
   • Nodes work together to store and manage data in a distributed fashion, with each node responsible for a portion of the data.
9. What is a token in Cassandra?
   • A token in Cassandra is a randomly generated value that is used to determine the placement of data in a distributed cluster.
   • Each node in the cluster is assigned a range of tokens, and data is assigned to nodes based on the token ranges.
   • Tokens are used to determine the placement of data within the cluster and to ensure that data is evenly distributed across nodes.
   • A token in Cassandra is a numeric value that represents the position of a node in the cluster’s partitioner range.
   • Tokens are used to determine the placement of data in the cluster and to route queries to the correct node.
   • Each node in the cluster is assigned one or more tokens, and the partitioner ensures that data is distributed evenly across the cluster.
   • A token in Cassandra is a 64-bit integer that represents the position of a node in the ring.
     • The token value is used to determine which node is responsible for storing a particular piece of data in a distributed cluster.
     • Each node is assigned one or more contiguous ranges of tokens, and data is stored on the node whose token range includes the token value of the data’s partition key.
   • A token in Cassandra is a 128-bit value that is assigned to each node in the cluster based on its position in the partitioner’s token ring.
     • Tokens are used to determine the ownership of data and the location of replicas within the cluster.
     • Each row of data is assigned a token based on its partition key, and the primary replica for that data is the node that owns the token with the closest value.
     • Additional replicas are assigned to the next nodes in a clockwise direction around the token ring.
     • By using tokens to distribute data across the cluster, Cassandra can ensure that data is evenly distributed and that each node is responsible for a roughly equal portion of the data.

10. How does Cassandra handle data replication?
    • Cassandra handles data replication by automatically replicating data to multiple nodes in a cluster.
    • The replication factor for a keyspace determines the number of copies of each piece of data that will be stored in the cluster.
    • When a node fails, the data it was responsible for is automatically replicated to other nodes in the cluster, ensuring that data is still available.
11. What is hinted handoff in Cassandra?
    • Hinted handoff in Cassandra is a mechanism that allows writes to be temporarily stored on a node if the primary replica for that data is not available.
      • Once the primary replica becomes available again, the write is forwarded to the primary replica. Hinted
    • Hinted handoff in Cassandra is a mechanism that allows a node to temporarily store write requests if the destination node for that data is unavailable.
      • Once the destination node becomes available, the hinted handoff is replayed to ensure that the data is written to the correct node.
    • Hinted handoff in Cassandra is a mechanism that is used to ensure that writes are not lost in the event of a node failure or network partition.
      • When a write request is made to a node that is not currently available, the node will store a hint about the write in its local storage.
      • When the node becomes available again, it will check for any stored hints and replay the writes to the appropriate nodes in the cluster.
      • Hinted handoff is used to ensure that writes are eventually propagated to all replicas of the data.
12. What is a commit log in Cassandra?
    • A commit log in Cassandra is a write-ahead log that records all changes to data before they are written to disk.
      • The commit log provides durability guarantees for data, allowing Cassandra to recover data in the event of a node failure.
    • A commit log in Cassandra is a durable log of write operations that is used to ensure data durability and recoverability in the event of a node failure.
      • The commit log is a critical component of Cassandra’s architecture and is used to ensure that data is not lost in the event of a node failure.
    • A commit log in Cassandra is a log of all changes made to the database.
      • The commit log is used to ensure durability and consistency of the data, even in the event of a node failure or other system failure.
      • When data is written to Cassandra, it is first written to the commit log, and then written to the appropriate memtable.
      • The commit log is stored on disk and is replicated across nodes in the cluster to provide fault tolerance.
13. What is compaction in Cassandra?
    • Compaction in Cassandra is the process of merging multiple SSTables (sorted string tables) into a single SSTable.
      • Compaction is used to ensure that data is organized efficiently and to reclaim disk space by removing obsolete or deleted data.
    • Compaction in Cassandra is the process of merging smaller SSTables (sorted string tables) into larger ones to reduce the number of files on disk and improve read performance.
      • Compaction is a critical process in Cassandra that ensures that data is efficiently stored on disk and available for read operations.
    • Compaction in Cassandra is the process of merging and purging SSTables (sorted string tables) in order to free up disk space and improve performance.
    • When new data is written to Cassandra, it is stored in a new SSTable.
      • Over time, as more data is written, multiple SSTables may be created for the same partition.
      • Compaction merges these SSTables into a single, more efficient SSTable.
      • There are several different types of compaction in Cassandra, including size-tiered compaction, leveled compaction, and date-tiered compaction.
    • Compaction in Cassandra is the process of merging multiple SSTables into a single, larger SSTable.
      • Compaction is used to reduce the number of SSTables that are stored on disk and to improve read performance by reducing the amount of random I/O that is required to retrieve data.
      • Compaction is also used to remove deleted or expired data from SSTables, freeing up disk space and improving write performance.
14. What is a tombstone in Cassandra?
    • A tombstone in Cassandra is a marker that indicates that a piece of data has been deleted.
      • Tombstones are used to ensure that deleted data is not resurrected in the event of a node failure or during compaction.
    • A tombstone in Cassandra is a special marker that is used to indicate that a column or row has been deleted.
      • Tombstones are used to ensure that deleted data is propagated to all replicas in the cluster and that no data is resurrected accidentally.
      • Tombstones are also used to support read repair and hinted handoff in Cassandra.
    • A tombstone in Cassandra is a marker that is used to indicate that a particular piece of data has been deleted.
      • When data is deleted in Cassandra, a tombstone is created to ensure that the deleted data is eventually removed from all replica nodes.
      • Tombstones are kept in the system until the data has been purged through the process of compaction.
      • Tombstones can be problematic in some situations, as they can lead to increased disk usage and slower read performance.
    • A tombstone in Cassandra is a marker that is used to indicate that a particular row or column has been deleted.
      • Tombstones are created when a delete operation is performed, and are used to ensure that deleted data is properly replicated to all replicas in the cluster.
      • Tombstones are also used during compaction to ensure that deleted data is not resurrected.
      • In general, tombstones should be deleted as soon as possible to avoid performance problems and disk space issues.
15. What is a Bloom filter in Cassandra?
    • A Bloom filter in Cassandra is a probabilistic data structure that is used to determine whether a particular piece of data exists in a given SSTable.
      • Bloom filters are used to reduce disk I/O by eliminating the need to read entire SSTables to check for the presence of data.
    • A Bloom filter in Cassandra is a probabilistic data structure that is used to quickly determine whether an element is likely to be present in a set.
      • Bloom filters are used by Cassandra to avoid performing disk reads for data that is not present on a node.
      • Bloom filters are not 100% accurate, but they have a very low rate of false negatives.
    • A bloom filter in Cassandra is a probabilistic data structure that is used to improve read performance by reducing the number of disk seeks required to find data.
      • Bloom filters are small in size and are stored in memory, and they allow Cassandra to quickly determine whether a particular SSTable might contain a given key.
      • Bloom filters are used in conjunction with the partition summary and index to speed up the process of locating data on disk.
    • A Bloom filter in Cassandra is a probabilistic data structure that is used to quickly determine whether a particular row exists in an SSTable or not.
      • A Bloom filter is essentially a bit array that is used to represent a set of values.
      • When a value is inserted into the Bloom filter, a hash function is used to generate a set of bit positions in the array.
      • These bits are then set to 1.
      • To check whether a value exists in the Bloom filter, the same hash function is applied to the value, and the corresponding bit positions in the array are checked.
      • If all of the bits are set to 1, then the value may be in the set (but not guaranteed), otherwise it is definitely not in the set.
      • Bloom filters are used in Cassandra to quickly eliminate SSTables that do not contain a particular row, reducing the amount of disk I/O that is required for read operations.

16. What is the role of a partition key in Cassandra?
    • A partition key in Cassandra is used to determine the placement of data within a cluster.
    • Each row in a column family is identified by a partition key, which is hashed to determine which node in the cluster is responsible for storing and managing that data.
17. What is a secondary index in Cassandra?
    • A secondary index in Cassandra is an index that is created on a non-partition key column in a column family.
    • Secondary indexes can be used to allow for efficient queries on columns that are not part of the partition key.
    • Secondary indexes can be used to efficiently retrieve data based on the value of a non-primary key column.
    • However, secondary indexes come with a performance cost, as they can impact write performance and increase disk usage.
    • Secondary indexes allow for faster lookups of data based on criteria other than the primary key.
    • In Cassandra, it is generally recommended to use secondary indexes sparingly and to consider denormalizing data or using materialized views instead.
    • Secondary indexes in Cassandra are used to support fast queries on columns that are not part of the primary key.
    • Secondary indexes can be created using the CREATE INDEX statement in CQL or using a client library for a programming language such.
18. How does Cassandra handle consistency?
    • Cassandra provides tunable consistency, allowing users to specify the level of consistency they require for a given read or write operation.
    • Users can choose from a variety of consistency levels, including strong consistency, eventual consistency, and others.
19. What is CQL?
    • CQL (Cassandra Query Language) is a SQL-like language that is used to interact with Cassandra databases.
    • CQL allows users to create, read, update, and delete data in Cassandra using a familiar syntax.
20. What is the role of a coordinator in Cassandra?
    • The coordinator in Cassandra is responsible for routing client requests to the appropriate nodes in the cluster.
    • The coordinator is also responsible for ensuring that the requested level of consistency is achieved for each operation.
21. What is a materialized view in Cassandra?
    • A materialized view in Cassandra is a denormalized view of data that is created by precomputing the results of a query and storing them in a separate table.
    • Materialized views can be used to improve query performance by reducing the number of data reads required to satisfy a query.
    • A materialized view in Cassandra is a table that is created based on the data stored in one or more existing tables.
    • Materialized views are used to denormalize data and to improve query performance by precomputing and storing the results of complex queries.
    • Materialized views are updated automatically whenever the underlying data changes, making them a powerful tool for building scalable and efficient data models.
    • Materialized views in Cassandra are used to improve query performance by precomputing results and storing them in a separate table.
    • Materialized views are automatically updated as the base table is updated, ensuring that the view always reflects the latest data.
    • Materialized views can be created and managed using CQL statements or using a client library for a programming language such as Java, Python, or Node.js.
22. What is a snitch in Cassandra?
    • A snitch in Cassandra is responsible for determining the topology of a cluster and reporting this information to other nodes in the cluster.
    • Snitches are used to ensure that data is placed on nodes in a way that ensures high availability and fault tolerance.
    • A snitch in Cassandra is a component that determines how nodes are organized and how data is replicated in the cluster.
    • Snitches are responsible for mapping IP addresses to nodes and determining the replication factor for keyspaces.
      • Cassandra comes with several built-in snitches, and custom snitches can also be developed.
    • A snitch in Cassandra is a component that is responsible for determining the topology of the cluster and for mapping nodes to datacenters and racks.
      • The snitch is used by Cassandra to determine which nodes to replicate data to in order to achieve the desired replication factor.
      • There are several snitch implementations available in Cassandra, each with different trade-offs in terms of performance and complexity.
    • A snitch in Cassandra is a component that is responsible for determining the network topology of the cluster.
      • The snitch is used to determine the location of nodes in the cluster, and to ensure that nodes communicate with each other in an efficient and fault-tolerant manner.
      • The snitch is also used to determine which nodes are considered to be “local” for the purposes of routing queries, and which nodes are considered to be “remote”.
      • Cassandra provides several different snitch implementations that are optimized for different network topologies, such as rack-aware snitches for datacenters that are organized into racks.

23. What is a replica in Cassandra?
    • A replica in Cassandra is a copy of data that is stored on a different node in the cluster.
    • Replicas are used to ensure high availability and fault tolerance by ensuring that multiple copies of data are available in case a node fails.
    • A replica in Cassandra is a copy of a partition that is stored on multiple nodes in a cluster.
    • Replicas are used to provide fault tolerance and to ensure that data is always available, even if some nodes in the cluster fail.
    • The number of replicas that are stored for each partition is configurable, and is typically set to three.
    • When a node fails, the replicas for its partitions can be promoted to primary replicas on other nodes in the cluster.
24. What is a snappy compression in Cassandra?
    • Snappy compression is a data compression algorithm that is used in Cassandra to compress data before it is written to disk.
    • Snappy compression can significantly reduce the amount of disk space required to store data and can also reduce network bandwidth usage during data transfer.
    • Snappy compression provides a good balance between compression ratio and performance and is used by default in Cassandra for data compression.
25. What is a read repair in Cassandra?
    • A read repair in Cassandra is a mechanism that is used to ensure that data is consistent across all replicas in the cluster.
      • When a read repair is triggered, Cassandra checks all replicas for a given piece of data and updates any replicas that do not have the latest version of that data.
    • In Cassandra, a read repair is a mechanism that is used to ensure consistency in read operations by repairing any inconsistencies between replicas of a piece of data.
      • When a read operation returns inconsistent results, the coordinator node responsible for the read will trigger a read repair to query all replicas of the data and update any out-of-sync replicas.
    • A read repair in Cassandra is a process that is used to ensure data consistency across replicas when performing read operations.
      • When a read operation is performed, Cassandra checks whether the data is consistent across all replicas.
      • If the data is not consistent, Cassandra will perform a read repair by sending updated data to the replicas that have inconsistent data.
      • Read repairs are performed automatically by Cassandra and are designed to ensure that read operations return consistent data even in the presence of replica inconsistencies.

26. What is a write repair in Cassandra?
    • A write repair in Cassandra is a mechanism that is used to ensure that data is consistent across all replicas in the cluster.
    • When a write repair is triggered, Cassandra updates all replicas for a given piece of data to ensure that they all have the same version of that data.
27. What is a virtual node (vnode) in Cassandra?
    • A virtual node (vnode) in Cassandra is a mechanism that is used to simplify cluster management and improve performance.
      • Virtual nodes allow Cassandra to automatically distribute data across nodes and can also improve data locality by ensuring that data is placed on nodes that are close to each other.
    • A virtual node (vnode) in Cassandra is a mechanism that allows a single physical node to represent multiple nodes in the cluster.
      • Each virtual node is assigned a token range, and the physical node is responsible for storing data for all of the virtual nodes that it represents.
      • Vnodes are used to improve the distribution of data in the cluster and to simplify node management.

28. What is the purpose of a gossip protocol in Cassandra?
    • The gossip protocol in Cassandra is used to disseminate information about the state of the cluster to other nodes in the cluster.
    • The gossip protocol is used to ensure that nodes are aware of changes in the cluster topology, such as the addition or removal of nodes, and to ensure that data is placed on the correct nodes.
29. What is a batch statement in Cassandra?
    • A batch statement in Cassandra is a group of write statements that are executed atomically.
      • Batch statements can be used to improve write performance by reducing the number of network round-trips required to write data to Cassandra.
      • However, batch statements can also increase the risk of write failures and should be used judiciously.
    • A batch statement in Cassandra is a mechanism for executing multiple write operations as a single atomic operation.
      • Batch statements can be used to improve write throughput by reducing the overhead of network and disk I/O, and by ensuring that multiple updates are either applied together or not at all.
      • Batch statements can be executed asynchronously or synchronously, and can include multiple types of write operations (e.g. inserts, updates, and deletes).
    • A batch statement in Cassandra is a statement that is used to group multiple CQL statements together into a single atomic operation.
      • Batch statements can be used to improve performance and reduce network overhead when executing multiple operations on the same partition.
      • Batch statements can be executed using the CQL BATCH keyword or using a client library for a programming language such as Java, Python, or Node.js.

30. What is a lightweight transaction (LWT) in Cassandra?
    • A lightweight transaction (LWT) in Cassandra is a type of transaction that provides strong consistency guarantees.
    • LWTs are used to ensure that only one client can write to a given row at a time, preventing conflicts and ensuring that the latest version of the data is always stored in Cassandra.
31. What is a compaction strategy in Cassandra?
    • A compaction strategy in Cassandra is a set of rules that determines how SSTables are merged during compaction.
      • Compaction strategies can be configured to prioritize read performance, write performance, or disk space usage, depending on the needs of the application.
      • There are several built-in compaction strategies in Cassandra, and custom strategies can also be developed.
    • In Cassandra, a compaction strategy is a configurable policy that is used to determine how SSTables are merged and compacted to reduce disk space usage and improve query performance.
      • Compaction strategies can be configured based on a variety of criteria, such as the number of SSTables or the amount of disk space used.

32. What is a coordinator node in Cassandra?
    • A coordinator node in Cassandra is the node that is responsible for receiving client requests and routing them to the appropriate nodes in the cluster.
    • The coordinator node is typically the node that is closest to the client in terms of network latency, but it can also be explicitly specified in the client driver configuration.
33. What is a gossip protocol in Cassandra?
    • The gossip protocol in Cassandra is a peer-to-peer communication protocol that is used to share information about nodes in the cluster.
    • Gossip is used to detect node failures, propagate schema changes, and update the partitioner ring.
    • The gossip protocol is a critical component of Cassandra’s architecture and is responsible for ensuring that the cluster remains in a consistent state.
34. What is the difference between a row and a column in Cassandra?
    • In Cassandra, a row is a collection of columns that are stored together and identified by a unique row key.
    • Each row can have a different number of columns, and the columns themselves can have different data types.
    • A column in Cassandra represents a single unit of data and consists of a name, a value, and a timestamp.
    • Columns are grouped together into column families or tables, which are defined by a schema.
35. What is a compaction in Cassandra?
    • Compaction in Cassandra is the process of merging multiple SSTables (sorted string tables) into a single SSTable to improve read performance and reduce disk space usage.
      • Cassandra uses a background process called the compaction process to perform compaction automatically.
      • There are several types of compaction strategies available in Cassandra, each with different trade-offs in terms of read and write performance, disk space usage, and I/O efficiency.
    • Compaction in Cassandra is the process of merging multiple SSTables (sorted string tables) into a single, larger SSTable.
      • Compaction is used to remove tombstones and obsolete data, and to reduce the number of SSTables that need to be read in order to satisfy a read request.
      • There are several different types of compaction in Cassandra, including size-tiered compaction, leveled compaction, and date-tiered compaction.
    • Compaction in Cassandra is the process of merging and removing SSTables in order to reclaim disk space and improve read performance.
      • Cassandra uses a “compaction strategy” to determine how and when to perform compactions.
      • There are several different compaction strategies available in Cassandra, each with different tradeoffs between disk space usage, read performance, and write performance.
      • Compaction typically involves merging multiple SSTables into a single SSTable, removing deleted or expired data, and optimizing the data layout for read performance.

36. What is a consistency level in Cassandra?
    • A consistency level in Cassandra is a parameter that determines the level of consistency that is required for a read or write operation to be considered successful.
    • Consistency levels are used to ensure that reads and writes are performed correctly in a distributed system where data can be replicated across multiple nodes.
    • Cassandra provides several consistency levels, ranging from “ONE” (where only one replica node needs to respond) to “ALL” (where all replica nodes need to respond).
37. What is a key space in Cassandra?
    • A keyspace in Cassandra is a logical container for a set of tables that share a common replication strategy and configuration.
    • A keyspace is similar to a database in a relational database management system (RDBMS) and can be thought of as a namespace for organizing data.
    • Each keyspace has a replication factor that determines the number of replicas that are used to store data in the cluster.
38. What is a CQL (Cassandra Query Language)?
    • CQL (Cassandra Query Language) is a SQL-like language that is used to interact with Cassandra.
    • CQL is designed to be easy to use and to provide a familiar syntax for developers who are already familiar with SQL.
    • CQL supports all of the basic CRUD (create, read, update, delete) operations, as well as more advanced features like batch operations, counters, and collections.
39. What is the gossip protocol in Cassandra?
    • The gossip protocol in Cassandra is a decentralized protocol used by nodes in a cluster to discover and share information about the state of the cluster.
    • Each node periodically sends and receives gossip messages containing information about its own state (e.g. which tokens it owns, which nodes it has recently seen) and the state of other nodes in the cluster.
    • The gossip protocol is used by Cassandra for a variety of tasks, such as detecting node failures and calculating load-balancing strategies.
40. What is a token range in Cassandra?
    • A token range in Cassandra is a contiguous range of token values that is assigned to a node in the cluster.
      • Token ranges are used to partition the data in the cluster and to determine which nodes are responsible for storing and serving particular pieces of data.
      • Each node is responsible for storing the data whose partition key falls within its assigned token range.
    • A token range in Cassandra is a range of tokens that is assigned to a node in a cluster.
      • Each node in a Cassandra cluster is responsible for a set of token ranges, which are calculated based on the node’s position in the ring and the number of nodes in the cluster.
      • Token ranges are used to ensure that data is distributed evenly across the cluster, and to allow for efficient routing of read and write requests.