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Hi All,
I have been getting the following error when reading some parquet files in a pyspark notebook.
Illegal Parquet type: INT64 (TIME(NANOS,true))
The parquet files are loaded by a copy activity in a pipeline, contained in a forEach loop, so its not easy to pull them out and manually map to say a string for later conversion.
I have done a bit of searching and it seems this was a known spark issue some time ago that was apparently rectified in Spark 3.2 ([SPARK-40819] Parquet INT64 (TIMESTAMP(NANOS,true)) now throwing Illegal Parquet type instead of aut...)
I have tried running the below in first cell of notebook.
Solved! Go to Solution.
Just an update...
I have successfully read the offending files using pandas and the fastparquet engine (after setting up a new environment to load that library).
Once read into a pandas frame, I convert to a spark df in order to continue with the rest of the notebook without having to refactor. I found I do need to run the spark.conf.set() calls above in order to write to delta tables (obviously parquet underneath).
Not elegant but is a workaround unless anyone has something else?
Just an update...
I have successfully read the offending files using pandas and the fastparquet engine (after setting up a new environment to load that library).
Once read into a pandas frame, I convert to a spark df in order to continue with the rest of the notebook without having to refactor. I found I do need to run the spark.conf.set() calls above in order to write to delta tables (obviously parquet underneath).
Not elegant but is a workaround unless anyone has something else?
HI @Kesahli,
I'm glad to hear you find the workaround, did you mind to share these codes here? I think they will help for others who faced the simalri scenario.
Regards,
Xiaoxin Sheng
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