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I applied via Referral and was interviewed in Sep 2024. There were 2 interview rounds.
Case study is shared two days before the interview process
Spark optimization techniques improve performance and efficiency of data processing.
Partitioning data to distribute workload evenly
Caching frequently accessed data to avoid recomputation
Using appropriate data formats like Parquet for efficient storage and retrieval
Optimizing shuffle operations by tuning parameters like shuffle partitions
Avoiding unnecessary data shuffling by using broadcast joins
Optimizations in Databricks involve tuning cluster configurations, optimizing code, and utilizing caching.
Tune cluster configurations to allocate resources efficiently
Optimize code by using efficient algorithms and data structures
Utilize caching to store intermediate results and avoid recomputation
Broadcast join is used when one of the tables is small enough to fit in memory of all the nodes in the cluster, reducing shuffle and improving performance.
Broadcast join is used to optimize join operations by broadcasting the smaller table to all nodes in the cluster.
It is beneficial when one of the tables is small enough to fit in memory of all nodes, reducing the need for shuffling data across the network.
Broadcast j...
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I applied via Naukri.com and was interviewed in Aug 2023. There was 1 interview round.
I was interviewed in Nov 2020.
I applied via Company Website and was interviewed in Oct 2024. There were 2 interview rounds.
3 sum problem was asked to complete
Take home project to design app
I applied via Company Website and was interviewed in Jun 2024. There were 2 interview rounds.
Create some kind of system design (some kind of app)
I applied via Walk-in and was interviewed in Jan 2024. There was 1 interview round.
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