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Luxoft

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Bosch Interview Questions and Answers

Updated 25 Jul 2024
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Q1. How to merge 2 dataframes of different schema?

Ans.

To merge 2 dataframes of different schema, use join operations or data transformation techniques.

  • Use join operations like inner join, outer join, left join, or right join based on the requirement.

  • Perform data transformation to align the schemas before merging.

  • Use tools like Apache Spark, Pandas, or SQL to merge dataframes with different schemas.

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Q2. What is Pyspark streaming?

Ans.

Pyspark streaming is a scalable and fault-tolerant stream processing engine built on top of Apache Spark.

  • Pyspark streaming allows for real-time processing of streaming data.

  • It provides high-level APIs in Python for creating streaming applications.

  • Pyspark streaming supports various data sources like Kafka, Flume, Kinesis, etc.

  • It enables windowed computations and stateful processing for handling streaming data.

  • Example: Creating a streaming application to process incoming data f...read more

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Q3. Explain the Spark architecture with example

Ans.

Spark architecture includes driver, cluster manager, and worker nodes for distributed processing.

  • Spark architecture consists of a driver program that manages the execution of tasks on worker nodes.

  • Cluster manager is responsible for allocating resources and scheduling tasks across worker nodes.

  • Worker nodes execute the tasks and store data in memory or disk for processing.

  • Example: In a Spark application, the driver program sends tasks to worker nodes for parallel processing of ...read more

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Q4. What is Pyspark?

Ans.

Pyspark is a Python API for Apache Spark, a powerful open-source distributed computing system.

  • Pyspark is used for processing large datasets in parallel across a cluster of computers.

  • It provides high-level APIs in Python for Spark programming.

  • Pyspark allows seamless integration with other Python libraries like Pandas and NumPy.

  • Example: Using Pyspark to perform data analysis and machine learning tasks on big data sets.

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Q5. What is Pyspark SQL?

Ans.

Pyspark SQL is a module in Apache Spark that provides a SQL interface for working with structured data.

  • Pyspark SQL allows users to run SQL queries on Spark dataframes.

  • It provides a more concise and user-friendly way to interact with data compared to traditional Spark RDDs.

  • Users can leverage the power of SQL for data manipulation and analysis within the Spark ecosystem.

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Q6. Handling ADF pipelines

Ans.

Handling ADF pipelines involves designing, building, and monitoring data pipelines in Azure Data Factory.

  • Designing data pipelines using ADF UI or code

  • Building pipelines with activities like copy data, data flow, and custom activities

  • Monitoring pipeline runs and debugging issues

  • Optimizing pipeline performance and scheduling triggers

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More about working at Luxoft

#1 Best IT/ITES Company - 2022
HQ - Zug, Switzerland, Switzerland
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Interview Process at Bosch

based on 3 interviews
1 Interview rounds
Technical Round
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