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I applied via Referral and was interviewed in Apr 2024. There were 2 interview rounds.
Spark Memory management involves configuring memory allocation, monitoring memory usage, and optimizing performance.
Set memory allocation parameters in Spark configuration (e.g. spark.executor.memory, spark.driver.memory)
Monitor memory usage using Spark UI or monitoring tools like Ganglia
Optimize performance by tuning memory allocation based on workload and cluster resources
Use techniques like caching and persistence t
Spark optimization involves tuning configurations, partitioning data, using appropriate transformations, and caching intermediate results.
Tune Spark configurations based on cluster resources and workload requirements
Partition data to distribute workload evenly across nodes
Use appropriate transformations like map, filter, and reduce to minimize data shuffling
Cache intermediate results to avoid recomputation
I applied via Referral and was interviewed in Oct 2023. There was 1 interview round.
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I appeared for an interview before Nov 2020.
I appeared for an interview in Sep 2017.
I appeared for an interview in Sep 2019.
I applied via Recruitment Consultant and was interviewed before Jan 2020. There were 5 interview rounds.
I am proficient in Java, Python, and C++. I have 2 years of experience in software development. I have excellent communication skills for client interaction.
Proficient in Java, Python, and C++
2 years of software development experience
Excellent communication skills for client interaction
I applied via Naukri.com and was interviewed in Jun 2020. There was 1 interview round.
I applied via Walk-in and was interviewed before Jul 2021. There were 3 interview rounds.
Data structures and algorithms
Python etl,pandas, pyspark questions
based on 3 interviews
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