The article discusses methods for counting files based on their naming conventions using Apache Spark and Scala. Specifically, it addresses the task of counting files matching a year-month pattern from filenames like 'samplefile_YYYY-MM-DD_HH_MM.xml'. The process entails setting up a Spark session, utilizing a list of years and months, and using regex to filter and count the relevant files that conform to this naming structure. The results are stored in a Spark DataFrame, enabling further analysis of the file counts.
In large-scale data processing with Apache Spark, extracting insights from file metadata is crucial, and using regex allows efficient pattern matching for filenames.
By utilizing Scala and Apache Spark, we can systematically iterate through a predetermined list of years and months, applying regex to count matching filenames.
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