Mastering Cassandra: Essential NoSQL Database Interview Questions

This comprehensive guide prepares you for Cassandra interviews by covering a wide range of core concepts and advanced features. We explore Cassandra's architecture, data model, and key advantages in handling massive datasets. This resource provides detailed answers to frequently asked Cassandra interview questions, including those on data replication, consistency levels, and the use of CQL (Cassandra Query Language). Learn about essential components like keyspaces, nodes, data centers, commit logs, memtables, and SSTables. Prepare for in-depth discussions on Cassandra's design goals, its comparison with other NoSQL databases, and various administration and management tools. This guide will equip you with the knowledge to confidently tackle any Cassandra interview.

Top Cassandra Interview Questions and Answers

What is Cassandra?

Cassandra is a highly scalable, distributed, NoSQL database management system. Designed for handling massive datasets with high availability and fault tolerance, it's known for its ability to handle large volumes of data across multiple machines without a single point of failure. It's open-source and particularly well-suited for applications needing high performance and reliability.

Cassandra's Programming Language

Cassandra is written in Java. Its flexible schema design and ability to scale horizontally make it ideal for big data applications.

Cassandra's Origin

Originally developed at Facebook by Avinash Lakshman and Prashant Malik, Cassandra was designed to handle the large-scale data requirements of the Facebook inbox search.

Cassandra Query Language (CQL)

Cassandra uses its own query language, CQL (Cassandra Query Language), which is similar to SQL but has its own syntax and capabilities. CQL provides a way to interact with and manage data within the Cassandra database.

Benefits of Using Cassandra

  • Real-time performance: Handles high-volume queries efficiently.
  • Scalability: Easily scales horizontally to handle growing data needs.
  • High Availability: Data replication ensures continuous operation even if some nodes fail.
  • No Single Point of Failure: Data is distributed across multiple nodes.

Cassandra Data Storage

Cassandra stores data in a distributed fashion across multiple nodes in a cluster. Data is organized into tables (column families) and further divided into keyspaces for management and replication.

Cassandra's Design Goals

Cassandra was designed to handle massive data workloads reliably across a distributed network, without being dependent on a single point of failure. Its key design goal was to provide high availability and scalability.

Types of NoSQL Databases

NoSQL databases are categorized into several types:

  • Document Stores: Store data in JSON-like documents (MongoDB, CouchDB).
  • Key-Value Stores: Store data as key-value pairs (Redis, Voldemort).
  • Column Stores: Store data in columns (Cassandra, HBase).
  • Graph Stores: Store data as nodes and relationships (Neo4j, Giraph).

Key Components of Cassandra Data Models

  • Keyspace: A namespace that groups related tables and manages data replication.
  • Table (Column Family): A collection of rows and columns.
  • Columns: Data values within a row.
  • Rows: Identified by a primary key.
  • Cluster: A collection of nodes.
  • Nodes: Individual machines in the cluster.

Other Important Cassandra Components

  • Node: A single server instance running Cassandra.
  • Datacenter: A logical grouping of nodes.
  • Commit Log: A write-ahead log used for data durability and recovery.
  • Memtable: An in-memory data structure that stores writes before they're flushed to disk.
  • SSTable (Sorted Strings Table): On-disk storage for data.
  • Bloom Filter: Used to quickly check for the existence of data.

Keyspaces in Cassandra

A keyspace is a namespace that provides a way to logically separate data within a Cassandra cluster. It determines how data is replicated across nodes.

Composite Keys in Cassandra

Composite keys combine multiple columns to form the primary key. This improves data organization and query performance.

  • Row Key: Uniquely identifies a row.
  • Clustering Columns: Order rows within a partition.

Data Replication in Cassandra

Data replication in Cassandra involves making copies of data on multiple nodes. This improves data availability and fault tolerance. Replication strategies control how and where data is replicated.

Nodes in Cassandra

A node is a physical server machine running a Cassandra instance.

Data Centers in Cassandra

Data centers are logical groupings of nodes, often used for geographic distribution and improved availability.

Commit Log in Cassandra

The commit log is a write-ahead log that ensures data durability. All write operations are recorded in the commit log before being written to the memtable.

Column Family in Cassandra

In Cassandra, a column family is equivalent to a table in a relational database. It is a collection of rows, where each row is identified by a key and contains multiple columns.

Consistency in Cassandra

Consistency refers to how up-to-date the data is across all replicas. Cassandra offers tunable consistency levels:

  • Eventual Consistency: Data is eventually consistent across all replicas. There is a delay before data becomes consistent.
  • Strong Consistency: Data is immediately consistent. This requires satisfying the condition: R + W > N (where R is the number of replicas to read, W is the number of replicas to write, and N is the total number of replicas).

Tunable Consistency in Cassandra

Cassandra's tunable consistency allows you to choose the level of consistency that best suits your application's needs, balancing consistency with performance and availability.

Creating a Keyspace in Cassandra

CQL Syntax

CREATE KEYSPACE my_keyspace WITH replication = {'class': 'SimpleStrategy', 'replication_factor': 3};

Column Family in Cassandra (Reiterated)

A column family in Cassandra is similar to a table in a relational database; it's a collection of rows, each identified by a row key and containing multiple columns.

Write Operations in Cassandra

Cassandra performs writes in two stages: first to the commit log (for durability), then to the memtable (in-memory storage). Once the memtable is full, it's flushed to disk as an SSTable.

Memtable in Cassandra

The memtable is an in-memory store for newly written data. It's sorted by key and improves write performance.

SSTable (Sorted Strings Table) in Cassandra

SSTables are on-disk storage files created from flushed memtables. They are immutable, meaning once data is written to an SSTable, it cannot be changed.

SSTables vs. Relational Tables

Unlike relational tables, SSTables are immutable. Cassandra uses multiple SSTables, and it creates an index for efficient data retrieval.

Cassandra Management Tools

  • DataStax OpsCenter: A web-based management and monitoring tool for Cassandra clusters.
  • SPM (System Performance Monitor): Monitors Cassandra and other big data platform metrics.

SPM Features

  • Metric and event correlation.
  • Distributed tracing.
  • Real-time graphs.
  • Alerting.

Clusters in Cassandra

A Cassandra cluster is a collection of nodes working together to store and manage data. Data is distributed across nodes for high availability and scalability.

ALTER KEYSPACE

The ALTER KEYSPACE command modifies the properties of an existing keyspace, such as its replication strategy.

Cassandra CQLSH

cqlsh is the command-line shell for interacting with Cassandra using the CQL language.

Node, Cluster, Datacenter in Cassandra

Node Cluster Datacenter
A single server running Cassandra. A collection of nodes working together. A logical grouping of nodes, often for geographic reasons.

Cassandra CQL Collections

Cassandra supports collection types:

  • SET (unordered, unique elements).
  • LIST (ordered, allows duplicates).
  • MAP (key-value pairs).

Bloom Filter in Cassandra

A Bloom filter is a probabilistic data structure used to test whether an element is a member of a set. It helps speed up data retrieval by quickly determining whether a data element exists on disk before performing a disk read.

Data Deletion in Cassandra

Deleting data in Cassandra involves marking rows as deleted by setting their columns to tombstones (special values). These tombstones are eventually removed through compaction.

SuperColumns in Cassandra

Supercolumns (deprecated in recent versions) grouped multiple columns together under a single supercolumn name.

Column vs. SuperColumn

Column SuperColumn
Stores a single value. Groups multiple columns under a single name. (Generally not recommended for new projects.)

Hadoop, HBase, Hive, Cassandra

These are all open-source projects within the Hadoop ecosystem, each having different capabilities. Hadoop provides distributed storage and processing, Hive offers SQL-like queries, HBase is a NoSQL column-family store, and Cassandra is another distributed NoSQL database.

void close() Method

The close() method closes an active Cassandra session.

Starting cqlsh

Use the command cqlsh to start the Cassandra command-line shell.

cqlsh Version

The command cqlsh --version displays the version information.

Cassandra on Windows

Yes, Cassandra runs on Windows.

Kundera

Kundera is an Object-Relational Mapper (ORM) for Cassandra using Java.

Thrift in Cassandra

Thrift is an RPC (Remote Procedure Call) framework used for communication between clients and the Cassandra server.

Hector in Cassandra

Hector is a Java client library for Cassandra (now largely superseded by the official Cassandra Java driver).

Cassandra Client Libraries: Hector

Hector: A Java Client for Cassandra

Hector was a popular open-source Java client library for Apache Cassandra. While largely superseded by the official Cassandra Java driver, it played a significant role in the early adoption of Cassandra. It was released under the MIT license, allowing for flexible use and modification.