TCS Data Engineer Interview Questions, Process, and Tips

Arrays, String and stack questions

Q1. Introduce yourself
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I am a data engineer with 5 years of experience in designing and implementing data pipelines for various industries.
• Experienced in ETL processes and data modeling

• Proficient in programming languages like Python and SQL

• Skilled in working with big data technologies such as Hadoop and Spark
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Q2. Projects I worked on
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Q3. Some questions on data science
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Q1. About preferred location
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Q2. About Work timings
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Q1. What is the architecture of Apache Spark?
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Apache Spark architecture includes a cluster manager, worker nodes, and driver program.
• Apache Spark architecture consists of a cluster manager, such as YARN or Mesos, which allocates resources and schedules tasks.

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

• The driver program coordinates the execution of the application and interacts with the cluster manager to distribute tasks.

• Spark applications are...read more
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Simple aptitude test

Q1. Simple sql join question
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Q1. What is an internal and external table in Hive
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Internal tables store data within Hive's warehouse directory while external tables store data outside of it.
• Internal tables are managed by Hive and are deleted when the table is dropped

• External tables are not managed by Hive and data is not deleted when the table is dropped

• Internal tables are faster for querying as data is stored within Hive's warehouse directory

• External tables are useful for sharing data between diffe...read more
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Q2. What is partition and coalesce
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Partitioning is dividing a large dataset into smaller, manageable parts. Coalescing is merging small partitions into larger ones.
• Partitioning is useful for parallel processing and optimizing query performance.

• Coalescing reduces the number of partitions and can improve query performance.

• In Spark, partitioning can be done based on a specific column or by specifying the number of partitions.

• Coalescing can be used to reduc...read more
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Q3. What is repartition and bucketing
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Repartitioning and bucketing are techniques used in Apache Spark to optimize data processing.
• Repartitioning is the process of redistributing data across partitions to optimize parallelism and improve performance.

• Bucketing is a technique used to organize data into more manageable and efficient groups based on a specific column or set of columns.

• Repartitioning and bucketing can be used together to further optimize data p...read more
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Q4. What is the window function
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Window function is a SQL function that performs a calculation across a set of rows that are related to the current row.
• Window functions are used to calculate running totals, moving averages, and other calculations that depend on the order of rows.

• They allow you to perform calculations on a subset of rows within a larger result set.

• Examples of window functions include ROW_NUMBER, RANK, DENSE_RANK, and NTILE.

• Window funct...read more
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Q5. What is an anonymous function
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An anonymous function is a function without a name.
• Also known as lambda functions or closures

• Can be used as arguments to higher-order functions

• Can be defined inline without a separate declaration

• Example: lambda x: x**2 defines a function that squares its input
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Q6. What is view in SQL and dense and dense rank
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View is a virtual table created from a SQL query. Dense rank assigns a unique rank to each row in a result set.
• A view is a saved SQL query that can be used as a table

• Dense rank assigns a unique rank to each row in a result set, with no gaps between the ranks

• Dense rank is used to rank rows based on a specific column or set of columns

• Example: SELECT * FROM my_view WHERE column_name = 'value'

• Example: SELECT column_name, D...read more
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