LTIMindtree Senior Data Engineer Interview Questions, Process, and Tips

Q1. Sql query to write max salary
Ans. 
Use SQL query with MAX function to find the highest salary in a table.
• Use SELECT MAX(salary) FROM table_name;

• Make sure to replace 'salary' with the actual column name in the table.

• Ensure proper permissions to access the table.
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Q2. What is dense rank in sql
Ans. 
Dense rank in SQL assigns a unique rank to each distinct row in a result set, with no gaps between the ranks.
• Dense rank is used to assign a rank to each row in a result set without any gaps.

• It differs from regular rank in that it does not skip ranks if there are ties.

• For example, if two rows have the same value and are ranked 1st, the next row will be ranked 2nd, not 3rd.
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Q1. What is spark cluster
Ans. 
Spark cluster is a group of interconnected computers that work together to process large datasets using Apache Spark.
• Consists of a master node and multiple worker nodes

• Master node manages the distribution of tasks and resources

• Worker nodes execute the tasks in parallel

• Used for processing big data and running distributed computing jobs
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Q2. How hive works in hdfs
Ans. 
Hive is a data warehouse system built on top of Hadoop for querying and analyzing large datasets stored in HDFS.
• Hive translates SQL-like queries into MapReduce jobs to process data stored in HDFS

• It uses a metastore to store metadata about tables and partitions

• HiveQL is the query language used in Hive, similar to SQL

• Hive supports partitioning, bucketing, and indexing for optimizing queries
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Q1. Database related questions
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Q2. Sql queries and performance tuning questions.
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Codility test on SQL, Spark and Python

Technical interviewer asked on Spark, Python and SQL

Q1. What skills will you bring to this position?
Ans. 
I will bring strong programming skills, experience with big data technologies, and a deep understanding of data processing and analysis.
• Strong programming skills in languages like Python, Java, or Scala

• Experience with big data technologies such as Hadoop, Spark, and Kafka

• Deep understanding of data processing and analysis techniques

• Ability to design and implement scalable data pipelines

• Experience with cloud platforms li
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Q1. Tell us about yourself
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Q2. Python use case and sql use cases
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