Cognizant Data Engineer Interview Questions, Process, and Tips

Q1. Self Introduction
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Q2. About the current project
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Q3. Different types of joins in SQL
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Different types of joins in SQL include inner join, left join, right join, and full outer join.
• Inner join: Returns rows when there is a match in both tables.

• Left join: Returns all rows from the left table and the matched rows from the right table.

• Right join: Returns all rows from the right table and the matched rows from the left table.

• Full outer join: Returns rows when there is a match in either table.
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Q4. Questions related to Cloud
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Q1. Roles and responsibilities in current project
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Q2. Optimizations used in present project
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Various optimizations such as indexing, caching, and parallel processing were used in the project.
• Implemented indexing on frequently queried columns to improve query performance

• Utilized caching mechanisms to store frequently accessed data and reduce database load

• Implemented parallel processing to speed up data processing tasks

• Optimized algorithms and data structures for efficient data retrieval and manipulation
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Q3. How did you overcome out of memory issues
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I optimized code, increased memory allocation, used efficient data structures, and implemented data partitioning.
• Optimized code by identifying and fixing memory leaks

• Increased memory allocation for the application

• Used efficient data structures like arrays, hashmaps, and trees

• Implemented data partitioning to distribute data across multiple nodes
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Project description on data engineer

Python and sql questions

Q1. On Basic SQL Question
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Q2. Python coding question for knowledge check
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Q1. In hadoop what happens if a name node fails
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If a name node fails in Hadoop, the entire Hadoop cluster becomes unavailable.
• The name node is responsible for managing the metadata of the Hadoop file system.

• If the name node fails, the cluster cannot access or process any data.

• To handle name node failures, Hadoop provides mechanisms like high availability and automatic failover.

• In high availability mode, there are multiple name nodes in the cluster, and if one fails,...read more
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Q2. Spark explain cluster mode vs client mode
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Cluster mode runs the Spark driver on one of the worker nodes, while client mode runs the driver on the client machine.
• In cluster mode, the driver runs on one of the worker nodes in the cluster, while in client mode, the driver runs on the machine where the Spark application is submitted.

• Cluster mode is suitable for production environments where fault tolerance and scalability are important, while client mode is more c...read more
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Q3. What are the Optimizations you can do in spark
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Optimizations in Spark include partitioning, caching, broadcast variables, and using appropriate data structures.
• Partitioning data based on key can improve performance by reducing data shuffling

• Caching frequently accessed data in memory can avoid recomputation

• Using broadcast variables can reduce data transfer between nodes

• Choosing appropriate data structures like DataFrames or Datasets can optimize query execution

• Using...read more
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Q4. Basic SQL question
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