val mnt_point_write="/mnt/pnt"
ord_JsonDF.write.mode("overwrite").format("json").option("header",true).json(mnt_point_write+"/Processed_file")
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure:
Task 0 in stage 114.0 failed 4 times, most recent failure:
Lost task 0.3 in stage 114.0 (TID 13876, 10.139.64.40, executor 27):
com.databricks.sql.io.FileReadException: Error while reading file dbfs:/mnt-02/AF_tab/Processed/YYYY=2019/MM=07/DD=21/part-00000-tid-677839983764655717-ahfuhaufhehfhurfawefkjfaffadfe-2685-1.c000.csv.
It is possible the underlying files have been updated.
You can explicitly invalidate the cache in Spark by running 'REFRESH TABLE tableName' command in SQL or by recreating the Dataset/DataFrame involved.
Встречаясь с вышеупомянутой проблемой. Может кто-нибудь помочь в решении вопроса, пожалуйста.