Apache Storm is a Clojure-based distributed stream processing computation framework. This blog provides technical interview questions for Apache Storm that were asked by an interviewer. After attending dozens of technical interviews at top-notch companies, we came up with this list.
Mindmajix as a team has got enough questions from the trainees who got their Apache Storm Training and cracked interviews at various MNCs around the world and successfully placed. From the collection of Apache Storm Interview Questions, the following are the most common questions we got are listed to make it easy for those who are willing to crack the interview with ease. All the answers to those were written by our professional experienced trainers and are tailored to meet the concepts expected by the interviewer.
Comparison | Storm | Kafka |
Data Source | Kafka and other DBs | FB and Twitter |
Data Storage | data exchange between an input to output streams | EXT4 File System/XFS |
Dependency | Independent | Depends on Zookeeper |
Inventor | ||
Language Support | All languages supported | Supports all, but Java is recommended |
Latency | Milli-Second latency | Depends upon Data Source generally less than 1-2 seconds. |
Primary Use | Stream Processing | Message Broker |
Stream processing | Micro-Batch Processing | Small-Batch Processing |
Type | Real-Time Message Processing | Distributed Messaging System |
Apache Storm is a free open source software that helps you to work with massive quantities of data including batch processing. A real-time computation system with batch processing is what makes Apache Storm ahead of other software like Hadoop, MapReduce, etc.
1.2.1 version released in February 2018
There is no specific language mentioned, as apache storm is flexible to work with any of the programming languages.
Nimbus, Zookeeper, and Supervisor are the components of Apache Storm.
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Ans: Nimbus is also known as Master Node. Nimbus is used to track the jobs of workers. All the code is distributed among the workers and allocated workers to clusters available. If at all any of the workers is needed with more resources, Nimbus has to provide extra resources to the workers.
Note: Nimbus is similar to Job Tracker in Hadoop
Zookeeper helps in communication among the storm cluster nodes. As the zookeeper is concerned only with coordination and not in messages, there exists not much workload.
The supervisor takes signals rom Nimbus through Zookeeper to execute the process. Supervisors are also known as Worker nodes.
Data can be stream of flow with three components:
First, configure spout to read the log files to emit one line and then analyze it by assigning to bolt.
All, none, local, global, field, shuffle, and direct groupings are available in apache storm.
Time specified to process a message released from the spout, and if at all the message is not processed, then the message is considered as fail.
Using the mod-proxy module, it can be used as a proxy server as well.
While working with storm topologies, ZeroMQ helps to communicate tasks with each other.
Storm kill {mindmajix_topology}
Where - mindmajix_topology is the name of the topology
In order to avoid legal or bureaucratic issues, Apache Storm avoids SSL.
Yes. To search data with titles.
There is no Java support for Apache storm.
There is no ASP support for Apache storm.
To group tuples into the unified field, a combiner aggregator is used.
Three elements collectively define the execution of tasks in the topology.
Worker processes are responsible to work with executors that belong to one or more components(i.e., spouts or bolts).
An executor is used to execute one or more processes as threads under the worker process.
Tasks refer to the number of subtasks included in the cluster to perform a whole operation of the topology. One task may contain more workers, resulting in more number of workers than total tasks together.
#threads (greater than or equals to) #tasks
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Apache Storm Training | Oct 12 to Oct 27 | View Details |
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Ravindra Savaram is a Technical Lead at Mindmajix.com. His passion lies in writing articles on the most popular IT platforms including Machine learning, DevOps, Data Science, Artificial Intelligence, RPA, Deep Learning, and so on. You can stay up to date on all these technologies by following him on LinkedIn and Twitter.