Capgemini Gcp Data Engineer Interview Questions and Answers

I have experience working on projects involving data processing, transformation, and analysis using GCP services like BigQuery, Dataflow, and Dataproc.

• Utilized BigQuery for storing and querying large datasets

• Implemented data pipelines using Dataflow for real-time data processing

• Utilized Dataproc for running Apache Spark and Hadoop clusters for data processing

• Worked on data ingestion and transformation using Cloud Stora...read more

Shuffle partition is a data processing technique used to redistribute data across partitions in distributed computing.

• Shuffle partition helps in balancing the load across different nodes in a distributed system.

• It is commonly used in frameworks like Apache Spark during operations like groupBy and join.

• For example, when joining two large datasets, shuffle partition ensures that related data is processed together.

• Imprope...read more

You can identify file size in Python using the os module or pathlib for efficient file handling.

• Use os.path.getsize() to get the size of a file in bytes. Example: os.path.getsize('file.txt')

• Use pathlib.Path.stat() to retrieve file size. Example: from pathlib import Path; Path('file.txt').stat().st_size

• File size can also be checked using the built-in open() function with os.fstat(). Example: os.fstat(open('file.txt').fi...read more

Google Cloud Dataflow supports Java and Python for building data processing pipelines.

• Java: Widely used for building robust data pipelines; example: Apache Beam SDK for Java.

• Python: Popular for its simplicity and ease of use; example: Apache Beam SDK for Python.

• Both languages allow for the creation of batch and streaming data processing applications.

Window functions in BigQuery are used to perform calculations across a set of table rows related to the current row.

• Window functions allow you to perform calculations on a set of rows related to the current row

• They are used with the OVER() clause in SQL queries

• Common window functions include ROW_NUMBER(), RANK(), and NTILE()

• They can be used to calculate moving averages, cumulative sums, and more

Types of NoSQL databases in GCP include Firestore, Bigtable, and Datastore.

• Firestore is a flexible, scalable database for mobile, web, and server development.

• Bigtable is a high-performance NoSQL database service for large analytical and operational workloads.

• Datastore is a highly scalable NoSQL database for web and mobile applications.

Code to find max number of product by customer

• Iterate through each customer's purchases

• Keep track of the count of each product for each customer

• Find the product with the maximum count for each customer

Creating a dataframe in GCP Data Engineer

• Use the pandas library to create a dataframe

• Provide data in the form of a dictionary or list of lists

• Specify column names if needed