Description: The ‘Job Dependency’ in data processing refers to the relationship between two data processing jobs where one depends on the output of the other. This concept is fundamental in designing complex workflows, as it allows tasks to be chained efficiently. In a data processing environment, one job can generate results that are necessary for another job to execute correctly. This dependency ensures that data is processed in the correct order and that intermediate results are used appropriately. Dependencies can be simple, where one job depends on a single previous job, or complex, where multiple jobs can influence the execution of a subsequent job. Managing these dependencies is crucial for optimizing performance and efficiency in data processing, enabling users to build robust and scalable data pipelines. Additionally, visualizing these dependencies can help developers better understand the data flow and identify potential bottlenecks in the analysis process.
