I'm attempting to run the following commands using the "%spark" interpreter in Apache Zeppelin:
val data = spark.range(0, 5)
data.write.format("delta").save("/tmp/delta-table")
Which yields this output (truncated to omit repeat output):
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 7, 192.168.64.3, executor 2): java.io.FileNotFoundException: File file:/tmp/delta-table/_delta_log/00000000000000000000.json does not exist
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.
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:127)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:177)
...
I'm unable to figure out why this is happening at all as I'm too unfamiliar with Spark. Any tips? Thanks for your help.
