Well if your data is skewed I don't think it can be avoided but mitigated using skew techniques.
I'd recommend you to take a look at "salted join" maybe. On Tue, 26 Jan 2021 at 11:29, rajat kumar <kumar.rajat20...@gmail.com> wrote: > Hi , > > Yes I understand its skew based problem but how can it be avoided . Could > you please suggest? > > I am in Spark2.4 > > Thanks > Rajat > > On Tue, Jan 26, 2021 at 3:58 PM German Schiavon <gschiavonsp...@gmail.com> > wrote: > >> Hi, >> >> One word : SKEW >> >> It seems the classic skew problem, you would have to apply skew >> techniques to repartition your data properly or if you are in spark 3.0+ >> try the skewJoin optimization. >> >> On Tue, 26 Jan 2021 at 11:20, rajat kumar <kumar.rajat20...@gmail.com> >> wrote: >> >>> Hi Everyone, >>> >>> I am running a spark application where I have applied 2 left joins. 1st >>> join in Broadcast and another one is normal. >>> Out of 200 tasks , last 1 task is stuck . It is running at "ANY" >>> Locality level. It seems data skewness issue. >>> It is doing too much spill and shuffle write is too much. Following >>> error is coming in executor logs: >>> >>> INFO UnsafeExternalSorter: Thread spilling sort data of 10.4 GB to disk >>> (10 times so far) >>> >>> >>> Can anyone please suggest what can be wrong? >>> >>> Thanks >>> Rajat >>> >>
