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posted on 20 Mar 2021
I applied via Walk-in and was interviewed before Mar 2020. There were 4 interview rounds.
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Broadcast and accumulator are used in Spark for efficient data sharing and aggregation across tasks.
Broadcast variables are used to efficiently distribute large read-only data to all tasks in a Spark job.
Accumulators are used for aggregating values from all tasks in a Spark job to a shared variable.
Broadcast variables help in reducing data transfer costs and improving performance.
Accumulators are used for tasks like co...
Coalesce and repartition are operations in Spark used to control the number of partitions in a DataFrame.
Coalesce reduces the number of partitions without shuffling data, while repartition reshuffles data to create a specified number of partitions.
Coalesce is more efficient when reducing partitions, as it minimizes data movement.
Repartition is useful for evenly distributing data across a specified number of partitions.
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I applied via Referral and was interviewed in Apr 2024. There were 2 interview rounds.
Python Array and List questions
20 questions of aptitude with 60 mints
2 coding questions asked moderate type
I applied via Recruitment Consulltant and was interviewed before Apr 2023. There were 3 interview rounds.
I applied via Naukri.com and was interviewed before Mar 2023. There was 1 interview round.
I was interviewed in Aug 2021.
Spark-submit, repartition vs coalesce, dag vs lineage
spark-submit is a command-line tool to submit Spark applications
repartition and coalesce are used to change the number of partitions in an RDD/DataFrame
DAG (Directed Acyclic Graph) is a logical representation of a Spark job
Lineage is the sequence of transformations that created an RDD
Repartitioning shuffles data across the network, while coalescing reduces the number...
I applied via Naukri.com and was interviewed in Jun 2022. There were 2 interview rounds.
I applied via Approached by Company and was interviewed in Jun 2022. There were 2 interview rounds.
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