A technical guide demonstrating how to process streaming data by integrating Spark Structured Streaming with Kafka, focusing on timestamp extraction and column derivation for data partitioning. The tu
torial provides complete implementation details from setup to validation, including code examples and best practices.
Reasons to Read -- Learn:
how to set up and configure a complete data streaming pipeline using Spark and Kafka, with detailed code examples that you can implement immediately
specific techniques for extracting and transforming timestamp data in streaming applications, including how to derive year, month, and day columns for efficient data partitioning
practical validation techniques for streaming data transformations using Spark's memory storage, helping you ensure data quality before final storage
4 min readauthor: Durga Gadiraju
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