In Spark, data is transient, meaning that once the Spark engine is shut off, all the data in memory is lost. Since Spark operates on in-memory processing, data is only available while the Spark session is active. Whether you are building an ETL pipeline or conducting analysis, data ingestion is the first crucial step.
