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Exploring Lazy Evaluation in Apache Spark | How Spark Achieves Performance Optimizations #interview
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Exploring Lazy Evaluation in Apache Spark | How Spark Achieves Performance Optimizations #interview
Lazy evaluation in Spark refers to the mechanism where transformations on resilient distributed datasets (RDDs) are not immediately executed. Instead, Spark waits until an action is called on the RDD before executing the transformations.
Most commonly asked interview questions when you are applying for any data based roles such as data analyst, data engineer, data scientist or data manager.
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Social Media Links :
#apachespark #parallelprocessing #DataWarehouse #DataLake #DataLakehouse #DataManagement #TechTrends2024 #DataAnalysis #BusinessIntelligencen #2024 #interview #interviewquestions #interviewpreparation
Lazy evaluation in Spark refers to the mechanism where transformations on resilient distributed datasets (RDDs) are not immediately executed. Instead, Spark waits until an action is called on the RDD before executing the transformations.
Most commonly asked interview questions when you are applying for any data based roles such as data analyst, data engineer, data scientist or data manager.
Don't miss out - Subscribe to the channel for more such interesting information
Social Media Links :
#apachespark #parallelprocessing #DataWarehouse #DataLake #DataLakehouse #DataManagement #TechTrends2024 #DataAnalysis #BusinessIntelligencen #2024 #interview #interviewquestions #interviewpreparation
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Exploring Lazy Evaluation in Apache Spark | How Spark Achieves Performance Optimizations #interview
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