Dev Standards for Spark-jobs
Too Long; Didn't Read
Discover practical strategies for standardizing the ETL process within Spark and Flink frameworks, covering key stages like reading, transforming, and writing data. Explore challenges and solutions, including data quality checks, registration, lineage building, and classification, to optimize your data processing workflows for improved efficiency and scalability.