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Yes, the atomicity property applies to Spark's overwrite save mode. In Spark's overwrite mode, the entire output directory is deleted and re-written with the new data. This operation is atomic, meaning that it is either completed successfully or is not executed at all, ensuring that data consistency is maintained. Therefore, if the write operation fails for any reason, the previous data is not lost and is still available.