Hello Vibhor, Thanks for the suggestion . I am looking for some other alternatives where I can use the same dataframe can be written to two destinations without re execution and cache or persist .
Can some one help me in scenario 2 ? How to make spark write to MinIO faster ? Sent from my iPhone > On May 21, 2024, at 1:18 AM, Vibhor Gupta <vibhor.gu...@walmart.com> wrote: > > > Hi Prem, > > You can try to write to HDFS then read from HDFS and write to MinIO. > > This will prevent duplicate transformation. > > You can also try persisting the dataframe using the DISK_ONLY level. > > Regards, > Vibhor > From: Prem Sahoo <prem.re...@gmail.com> > Date: Tuesday, 21 May 2024 at 8:16 AM > To: Spark dev list <dev@spark.apache.org> > Subject: EXT: Dual Write to HDFS and MinIO in faster way > > EXTERNAL: Report suspicious emails to Email Abuse. > > Hello Team, > I am planning to write to two datasource at the same time . > > Scenario:- > > Writing the same dataframe to HDFS and MinIO without re-executing the > transformations and no cache(). Then how can we make it faster ? > > Read the parquet file and do a few transformations and write to HDFS and > MinIO. > > here in both write spark needs execute the transformation again. Do we know > how we can avoid re-execution of transformation without cache()/persist ? > > Scenario2 :- > I am writing 3.2G data to HDFS and MinIO which takes ~6mins. > Do we have any way to make writing this faster ? > > I don't want to do repartition and write as repartition will have overhead of > shuffling . > > Please provide some inputs. > >
