TCS Data Engineer Interview Questions, Process, and Tips

Pyspark coding join df union etc

Q1. Writing pyspark codes
Ans. 
Writing pyspark codes involves using PySpark API to process big data in a distributed computing environment.
• Use PySpark API to create SparkContext and SparkSession objects

• Utilize transformations like map, filter, reduceByKey, etc. to process data

• Implement actions like collect, count, saveAsTextFile, etc. to trigger computation

• Optimize performance by caching RDDs and using broadcast variables

• Handle errors and exceptions
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Q2. SQL codes with live examples
Ans. 
SQL codes with live examples
• Use SELECT statement to retrieve data from a database table

• Use WHERE clause to filter data based on specific conditions

• Use JOIN to combine rows from two or more tables based on a related column
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Q1. How to add column in a df?
Ans. 
To add a column in a df, use the df['new_column'] = value syntax.
• Use the df['new_column'] = value syntax to add a new column to a DataFrame.

• Value can be a single value, a list, or a Series.

• Example: df['new_column'] = 10
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Q2. How to optimize spark jobs?
Ans. 
Optimizing Spark jobs involves tuning configurations, optimizing code, and utilizing resources efficiently.
• Tune Spark configurations such as executor memory, cores, and parallelism

• Optimize code by reducing unnecessary shuffles, caching intermediate results, and using efficient transformations

• Utilize resources efficiently by monitoring job performance, scaling cluster resources as needed, and optimizing data storage for
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Q3. Introduce and explain your project?
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Q4. Have any idea about scoop?
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Q5. How you ingest your data in pipeline?
Ans. 
I ingest data in the pipeline using tools like Apache Kafka and Apache NiFi.
• Use Apache Kafka for real-time data streaming

• Utilize Apache NiFi for data ingestion and transformation

• Implement data pipelines using tools like Apache Spark or Apache Flink
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Tcs NQT test is very easy to give

Two coding questions were given and I was asked to solve it

Q1. Technical questions on the tech stack.
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Q2. Java and python related questions
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Q1. What's is your role in project
Ans. 
As a Data Engineer, my role in the project is to design, build, and maintain data pipelines, databases, and infrastructure to support data analytics and machine learning.
• Designing and implementing data pipelines to extract, transform, and load data from various sources

• Building and optimizing databases for storage and retrieval of large volumes of data

• Collaborating with data scientists and analysts to understand their r...read more
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Q1. How to find rank without using aggregator in Informatica
Ans. 
To find rank without using aggregator in Informatica, use the Rank transformation with a custom rank variable.
• Use Rank transformation in Informatica

• Create a custom rank variable to assign ranks based on specific criteria

• Use conditional statements in the Rank transformation to determine rank
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Q2. Difference between Partition and clustering in GCP
Ans. 
Partitioning is dividing data into smaller parts for better management, while clustering is grouping similar data together for efficient querying.
• Partitioning is used to divide data into smaller chunks based on a specific column or key, which helps in managing and querying large datasets efficiently.

• Clustering is used to group similar rows of data together physically on disk, which can improve query performance by redu...read more
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