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PySpark Interview Questions | Azure Data Engineer #azuredataengineer #databricks #pyspark
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Q54. Explain startsWith() and endsWith() methods in PySpark.
String-based filtering is a common operation in data processing pipelines, and understanding how to efficiently use startsWith() and endsWith() will help you write cleaner and faster PySpark code.
Watch the video to master these functions and optimize your PySpark data processing!
🔥 Don't forget to subscribe for more tutorials on PySpark and big data!
Don't forget to like, comment, and subscribe for more PySpark interview tips and tutorials!
#PySpark #BigData #ApacheSpark #DataEngineering #PySparkInterviewQuestions #CloudArchitectAbhiram
String-based filtering is a common operation in data processing pipelines, and understanding how to efficiently use startsWith() and endsWith() will help you write cleaner and faster PySpark code.
Watch the video to master these functions and optimize your PySpark data processing!
🔥 Don't forget to subscribe for more tutorials on PySpark and big data!
Don't forget to like, comment, and subscribe for more PySpark interview tips and tutorials!
#PySpark #BigData #ApacheSpark #DataEngineering #PySparkInterviewQuestions #CloudArchitectAbhiram
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