Is spark overwrite save mode atomic?

Question

Using spark overwrite mode to write dataset deletes old files in the partitions and write the new data. Is this process atomic ? If the job fails while overwriting the data, will spark revert the old files present in the partitions ?

Answer 1

According to this post in databricks is not (emphasys mine):

It is sometimes useful to atomically overwrite a set of existing files. Today, Spark implements overwrite by first deleting the dataset, then executing the job producing the new data. This interrupts all current readers and is not fault-tolerant. With transactional commit, it is possible to “logically delete” files atomically by marking them as deleted at commit time

But they also offer an alternative to achieve atomic overwrite