Tuesday, 4 January 2022

Top 20 Apache Cassandra Interview Questions and Answers

  

                Apache recommends Cassandra as one of the most popular NoSQL distributed database management systems. Cassandra is an open-source database that is meant to store and manage enormous amounts of data without failure. Apache Cassandra is a Java database with flexible schemas that is highly scalable for Big Data models and was originally built by Facebook. There is no single point of failure with Apache Cassandra. Cassandra is a combination of column-oriented and key–value store databases, and it is one of the most popular NoSQL databases. The keyspace entity in Cassandra is the table or column family, which is the application's outermost container.

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Ques. 1): What is the purpose of Cassandra and why should you utilise it?

Answer:

Cassandra was created with the goal of handling large data workloads across several nodes with no single point of failure. Cassandra's use is influenced by a number of things.

  • It's fault-tolerant and reliable.
  • Scalability from gigabytes to petabytes
  • It's a database with columns.
  • There are no singular points of failure.
  • There isn't a requirement for a separate caching layer.
  • Schema design that is adaptable
  • It has a flexible data storage system, simple data distribution, and quick write speeds.
  • The ACID (Atomicity, Consistency, Isolation, and Durability) qualities are supported.
  • Cloud and multi-data centre capabilities
  • Compression of data

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Ques. 2): What are Cassandra's applications?

Answer:

When it comes to app development and data management, Cassandra has become the go-to solution for many businesses. Because of the ease with which an operator can work, even fresh start-ups choose it.

Cassandra is a fantastic application for collecting data from a variety of sources at a rapid rate. Cassandra could be used in an internet of things application. It might also be utilised in product and retail apps, as well as messaging, social media analytics, and even a recommendation engine.

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Ques. 3): What are the advantages of utilising Cassandra?

Answer:

  • Apache Cassandra, unlike any other database, provides near real-time speed, making the work of Developers, Administrators, Data Analysts, and Software Engineers much easier.
  • Cassandra is built on a peer-to-peer architecture rather than a master–slave design, assuring no failure.
  • It also ensures incredible flexibility by allowing numerous nodes to be added to each Cassandra cluster in any data centre. In addition, any client can send a request to any server.
  • Cassandra supports extensible scalability and can be simply scaled up and down depending on the needs. This NoSQL application does not need to be restarted while scaling because it has a high throughput for read and write operations.
  • Cassandra is also known for its powerful data replication on nodes feature, which allows users to store data in numerous locations and recover data from a different location if one node fails. The amount of copies that users want to make can be set by them.
  • When used for large datasets, it performs admirably, making it the NoSQL DB of choice for most businesses.
  • Operates on a column-oriented structure, which speeds up and simplifies the slicing process. With a column-based data model, even data access and retrieval become more efficient.
  • Furthermore, Apache Cassandra features a schema-free/schema-optional data model, which eliminates the need to display all of the columns that your application requires.
  • Learn how Cassandra vs. MongoDB can help you advance your career.

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Ques. 4): In Cassandra, explain the idea of adjustable consistency.

Answer:

Cassandra's tunable consistency is a fantastic feature that makes it a popular database among developers, analysts, and big data architects. Consistency refers to all replicas having up-to-date and synced data rows. Cassandra's adjustable consistency allows users to choose the level of consistency that best suits their needs. It encourages two types of constancy: eventual and strong consistency.

The former ensures consistency when no new updates are made to a data item, i.e., all accesses eventually return the most recently modified value. Replica convergence is a term used to describe systems that achieve eventual consistency.

For strong consistency, Cassandra supports the following condition:

R + W > N where,

N – Number of replicas

W – Number of nodes that need to agree for a successful write

R – Number of nodes that need to agree for a successful read

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Ques. 5): What is Cassandra's data storage method?

Answer:

Bytes are used to store all data.

Cassandra ensures that the bytes are encoded correctly when you specify validator.

The column is then ordered using a comparator depending on the encoding's specific ordering.

While composites are simply byte arrays with a specific encoding, each component holds a two-byte length, a byte encoded component, and a termination bit.

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Ques. 6): What is the definition of memtable?

Answer:

A memTable is a place where data is written and temporarily stored. After the data in the commit log has been completed, it is written to memtable.

In Cassandra, Memtable is a storage engine. Because each column category has its own MemTable, data in MemTable is classified into a key, and data is retrieved using the key. When the write memory is filled, the messages are automatically deleted.

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Ques. 7): Explain the Bloom Filter concept.

Answer:

Bloom filter is an off-heap (off the Java heap to native memory) data structure associated with SSTable that checks whether there is any data accessible in the SSTable before conducting any I/O disc action.

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Ques. 8): What are the functions of the shell commands "Capture" and "Consistency"?

Answer:

Cassandra has a number of Cqlsh shell commands. The command "Capture" saves the result of a command to a file, whereas the command "Consistency" shows the current consistency level or sets a new one.

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Ques. 9): What is the purpose of the read repair request?

Answer:

When the coordinator node sends requests, it checks in with the nodes to see if they have any outdated information. This data is transmitted to be read and repaired in the background before being replaced with the updated data. Read and repair requests are a way to maintain the data current while also ensuring that the requested row is consistent across all replicas.

 

Ques. 10): How does Cassandra write?

Answer:

Cassandra executes the write operation in two steps: first, it writes to a disc commit log, and then it commits to an in-memory structure called memtable. The write is complete after the two commits are successful. SSTables are used to store writes in the table structure (sorted string tables). Cassandra is more efficient when it comes to writing.

 

Ques. 11): What are the best Cassandra monitor tools?

Answer:

Despite the fact that Cassandra has built-in tolerance mechanisms, it still needs to be monitored for optimal outcomes. Cassandra utilises the following tools to keep track of its databases:

  • Solarwind server and application monitor
  • Instana
  • Instaclustr
  • AppDynamics
  • Dynatrace
  • Machine engine applications manager.

 

Ques. 12): What is Cassandra- CQL collections?

Answer:

Cassandra Multiple values can be stored in a single variable using CQL collections. CQL collections can be used in Cassandra in the following ways.

List: It is used when the order of the data needs to be maintained, and a value is to be stored multiple times (holds the list of unique elements)

SET: It is used for group of elements to store and returned in sorted orders (holds repeating elements)

MAP: It is a data type used to store a key-value pair of elements

 

Ques. 13): What is Super Column in Cassandra?

Answer:

Cassandra Super Column is a unique element consisting of similar collections of data. They are actually key–value pairs with values as columns. It is a sorted array of columns, and they follow a hierarchy when in action: keystore > column family > super column > column data structure in JSON.

Similar to the row keys, super column data entries contain no independent values but are used to collect other columns. It is interesting to note that super column keys appearing in different rows do not necessarily match and will not ever.

 

Ques. 14): Describe the CAP Theorem.

Answer:

With a strong necessity to scale systems when new resources are required, the CAP Theorem is critical to the scaling strategy's success. It's a good approach to deal with scaling in distributed systems. The Consistency, Availability, and Partition Tolerance (CAP) theorem asserts that customers can only have two of these three qualities in distributed systems like Cassandra.

It's necessary to sacrifice one of them. Consistency ensures that the client receives the most recent writing; availability ensures a sensible response in the shortest time possible; and partition tolerance ensures that the system continues to operate even if network partitions occur. AP and CP are the two alternatives available.

 

Ques. 15): What is the difference between Column and Super Column?

Answer:

Both elements work on the principle of tuples having name and value. However, the former’s value is a string, while the value of the latter is a map of columns with different data types.

Unlike Columns, Super Columns do not contain the third component of timestamp.

 

Ques. 16): What exactly is a Column Family?

Answer:

A column family, as the name implies, is a structure with an endless number of rows. A key–value pair is used to refer to these, with the key being the column name and the value being the column data. In Java, it's equivalent to a hashmap, while in Python, it's analogous to a dictionary. Remember that the columns in the rows are not confined to a specified list. Furthermore, the column family is extremely adaptable, with one row having 100 columns and the other simply having two.

 

Ques. 17): Define the management tools in Cassandra.

Answer:

DataStax OpsCenter: It is the Internet-based management and monitoring solution for Cassandra cluster and DataStax. It is free to download and includes an additional edition of OpsCenter.

SPM primarily administers Cassandra metrics and various OS and JVM metrics. Besides Cassandra, SPM also monitors Hadoop, Spark, Solr, Storm, ZooKeeper, and other Big Data platforms. The main features of SPM include correlation of events and metrics, distributed transaction tracing, creating real-time graphs with zooming, anomaly detection, and heartbeat alerting.

 

Ques. 18): In Cassandra, explain the distinctions between a node, a cluster, and a data centre.

Answer:

Cassandra is made up of several parts. A cluster is a collection of nodes that have comparable sorts of data organised together, whereas a node is a single machine running Cassandra. When serving consumers from different parts of the world, data centres are essential components. You can divide a cluster's nodes into various data centres.

 

Ques. 19): What is the purpose of the Bloom Filter in Cassandra?

Answer:

A bloom filter is a space-saving data structure for determining if an element belongs to a set. In other words, it's used to see if an SSTable contains data for a specific row. When executing a KEY LOOKUP in Cassandra, it is utilised to save IO.

 

Ques. 20): What exactly is SSTable? What makes it unique among relational tables?

Answer:

SSTable stands for 'Sorted String Table,' and it refers to a crucial Cassandra data file that supports regular written memtables. They exist for each Cassandra table and are kept on disc. Because of their immutability, SSTables do not allow the insertion or removal of data items once they have been written. Cassandra creates three different files for each SSTable: a partition index, a partition summary, and a bloom filter.