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01-03-2024 03:05 PM - edited 01-03-2024 03:12 PM
Hi @Retired_mod I am having the same issue where i made a inner join on two spark dataframes they are running only a single node not sure how to modify to run on many nodes and same thing with when i write a 30 gb data to a delta table it is almost 3 hours still executing how we can reduce the time
it is simple join of two tables first table has 50 millon records and second table has 300k records and inner join took 20 minutes and I want to save this a new delta table
here is the code
result_df = Invoice_Data.join(Fixed_df, on=['Code', 'item_no', 'supplier_no'], how='inner')
result_df.write.option("overwriteSchema", "true").format("delta").mode("overwrite").save("abfss://data@abc.dfs.core.windows.net/features/MCA")
Attached the metrics time let me know how we can optimize it