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Top Apache Storm Interview Questions and Answers (2022) | TechGeekNxt >>

Top Apache Storm Interview Questions and Answers (2022)

In this post, questions from Apache Storm Interviews will be answered for Experienced and Freshers. We're trying to share our experience and learn how to help you make progress in your career.

Apache Storm Tutorial :

  1. Apache Storm Architecture
  2. Install Apache Storm
  3. Apache Storm Interview Questions and Answers
  1. What is Apache Storm?
  2. What are some of the scenarios in which you would want to use Apache Storm?
  3. What are the features of Apache Storm?
  4. What is the architecture of Apache Storm?
  5. What are the components of Apache Storm?
  6. What is Apache Storm Topology?
  7. What is Apache Storm Stream?
  8. How to declare fields in Apache Storm component?
  9. How to emits the value from the component?

Q: What is Apache Storm?

Apache Storm is a free and open source distributed stream processing computation framework written predominantly in the Clojure programming language. Originally created by Nathan Marz and team at BackType, the project was open sourced after being acquired by Twitter.

Q: What are some of the scenarios in which you would want to use Apache Storm?

Storm can be used for the following use cases:

  1. Stream processing
    Apache Storm is used to process a stream of data in real time and update several databases. This processing takes place in real time, and the processing speed must match that of the input data speed.
  2. Continuous computation
    Apache Storm can process data streams continuously and deliver the results to clients in real time. This could require processing each message when it arrives or creating in small batches over a short period of time. Streaming trending topics from Twitter into browsers is an example of continuous computation.
  3. Distributed RPC
    Apache Storm can parallelize a complex query, allowing it to be computed in real time.
  4. Real-time analytics
    Apache Storm will analyse and react to data as it comes in from various data sources in real time.

Q: What are the features of Apache Storm?

Apache Storm is a real-time stream processing system.

  1. It is a fast and reliable processing system.
  2. It can handle large amounts of data at high speeds.
  3. It is an open source and a part of Apache projects.
  4. It helps to process big data.
  5. Apache Storm is horizontally scalable, fault tolerant.
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Q: What is the architecture of Apache Storm?

A Storm cluster uses a master-slave model, with ZooKeeper coordinating the master and slave processes. A Storm cluster is made up of the following components.

Apache Storm Architecture

  1. Nimbus

    In a Storm cluster, the Nimbus node is the master. It's in charge of distributing application code through multiple worker nodes, assigning tasks to various machines, monitoring tasks for errors, and restarting them as required.

  2. Supervisor nodes

    In a Storm cluster, the supervisor nodes are the worker nodes. Each supervisor node runs a supervisor daemon, which is in charge of building, starting, and stopping worker processes in order to complete the tasks assigned to it. A supervisor daemon, like Nimbus, is fail-safe and saves all of its states in ZooKeeper so that it can be restarted without losing any data. Normally, a single supervisor daemon manages multiple worker processes on a single machine.

  3. The ZooKeeper cluster

    Various processes in a distributed application must communicate with one another and share certain configuration information. ZooKeeper is an application that reliably provides all of these services. Storm uses a ZooKeeper cluster to organise different processes as a distributed application. In ZooKeeper, all of the cluster's states, as well as the different tasks sent to Storm, are saved. Nimbus and supervisor nodes communicate with each other through ZooKeeper rather than directly. Since all data is stored in ZooKeeper, both Nimbus and the supervisor daemons can be killed without causing the cluster to fail.

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Q:What are the components of Apache Storm?

Apache Storm is made up of three major components: Spout, Bolt and Tuple.

  1. Spout

    A spout is the source of tuples in a Storm topology. It is responsible for reading or listening to data from an external source, for example, by reading from a log file or listening for new messages in a queue and publishing them--emitting in Storm terminology into streams. A spout can emit multiple streams, each of a different schema. For example, it can read records of 10 fields from a log file and emit them as different streams of seven-fields tuples and four-fields tuples each.

  2. Bolt

    Bolts represent the processing logic unit in Storm. It processes the data received from Spout. Basically, a bolt is the processing powerhouse of a Storm topology and is responsible for transforming a stream. Ideally, each bolt in the topology should be doing a simple transformation of the tuples, and many such bolts can coordinate with each other to exhibit a complex transformation.

  3. Tuple

    The basic unit of data or single message/record that can be processed by a Storm application is called a tuple. Each tuple consists of a predefined list of fields. The value of each field can be a byte, char, integer, long, float, double, Boolean, or byte array. Storm also provides an API to define your own datatypes, which can be serialized as fields in a tuple.

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Q: What is Apache Storm Topology?

A Apache Storm Topology is a chain of stream transformations, with each node representing a spout or bolt. In a Storm topology, each node runs in parallel. You can decide how much parallelism you want for each node in your topology, and Storm will spawn that many threads across the cluster to complete the task.

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Apache Storm Topologies

Q: What is Apache Storm Stream?

The key abstraction in Storm is that of a stream. A stream is an unbounded sequence of tuples that can be processed in parallel by Storm. Each stream can be processed by a single or multiple types of bolts. Apache Storm can also be viewed as a platform to transform streams. In the preceding diagram, streams are represented by arrows. Each stream in a Storm application is given an ID and the bolts can produce and consume tuples from these streams on the basis of their ID. Each stream also has an associated schema for the tuples that will flow through it.

Q: How to declare fields in Apache Storm component?

Implement this method in every storm component.

public void declareOutputFields(OutputFieldsDeclarer declarer){
declarer.declare(new Fields("Symbol","Date","Count"));}

Q: How to emits the value from the component?

All components use a collector object to emit values.

collector.emit(new Values("AAA","29-03-21",80))

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