Times Internet Interview Questions, Process, and Tips

Q1. Read data from continuous stream of file
Ans. 
To read data from a continuous stream of file, we can use tools like tail or Apache Kafka.
• Tail command can be used to read the last n lines of a file and follow the growth of the file.

• Apache Kafka is a distributed streaming platform that can be used to read data from a continuous stream of files.

• We can also use programming languages like Python or Java to read data from a continuous stream of files.
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Q1. Project discussion + Java basics
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Q1. Project discussion + Behavioural questions
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Basic aptitude questions

Gave the topic on social median boon or bane

Q1. Basic cv, where do you belong from and technical question
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Q1. Why is testing required
Ans. 
Testing is required to ensure the quality and functionality of software applications.
• Identify defects and bugs in the software

• Ensure the software meets the requirements and specifications

• Verify that the software functions correctly under different scenarios

• Improve user experience and satisfaction

• Reduce the risk of software failures and issues

• Examples: Regression testing, performance testing, usability testing
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Q2. What makes the process so important
Ans. 
The process is important because it ensures quality, efficiency, and consistency in the outcome.
• Ensures quality control by following specific steps and guidelines

• Improves efficiency by streamlining tasks and reducing errors

• Maintains consistency in the outcome by standardizing procedures

• Helps in identifying and resolving issues early in the development cycle
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Q1. What is the process for creating a data pipeline in Spark to continuously monitor the number of devices that are online?
Ans. 
Creating a Spark data pipeline to monitor online devices involves data ingestion, processing, and real-time analytics.
• 1. Data Ingestion: Use Spark Streaming to ingest data from sources like Kafka or MQTT where device status updates are published.

• 2. Data Processing: Transform the incoming data using Spark's DataFrame API to filter and aggregate the number of online devices.

• 3. Real-time Analytics: Utilize Spark Structure...read more
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Q2. How can a large language model (LLM) be used to create YouTube Shorts?
Ans. 
LLMs can generate scripts, ideas, and captions for engaging YouTube Shorts content.
• Script Generation: LLMs can create concise scripts based on trending topics, e.g., a 60-second summary of a popular movie.

• Content Ideas: They can suggest creative concepts for Shorts, like '5 Quick Tips for Healthy Eating' or 'Top 3 Travel Destinations'.

• Caption and Hashtag Suggestions: LLMs can generate catchy captions and relevant hasht...read more
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