Hi Sean,
To finish the job, I did need to set spark.stage.maxConsecutiveAttempts to a
large number e.g., 100; a suggestion from Jiang Xingbo.
I haven't seen any recent movement/PRs on this issue, but I'll see if we can
repro with a more recent version of Spark.
Best regards,
Tyson
-Origi
Hi,
We are able to reproduce this bug in Spark 2.4 using the following program:
import scala.sys.process._
import org.apache.spark.TaskContext
val res = spark.range(0, 1 * 1, 1).map{ x => (x % 1000,
x)}.repartition(20)
res.distinct.count
// kill an executor in the stage t
+1 (non-binding)
Tyson Condie
From: Kazuaki Ishizaki
Sent: Thursday, May 9, 2019 9:17 AM
To: Bryan Cutler
Cc: Bobby Evans ; Spark dev list ;
Thomas graves
Subject: Re: [VOTE][SPARK-27396] SPIP: Public APIs for extended Columnar
Processing Support
+1 (non-binding)
Kazuaki Ishizaki
+1 (non-binding) for better columnar data processing support.
From: Jules Damji
Sent: Friday, April 19, 2019 12:21 PM
To: Bryan Cutler
Cc: Dev
Subject: Re: [VOTE][SPARK-27396] SPIP: Public APIs for extended Columnar
Processing Support
+ (non-binding)
Sent from my iPhone
Pardon the du
Thanks Ryan and Reynold for the information!
Cheers,
Tyson
From: Ryan Blue
Sent: Wednesday, March 6, 2019 3:47 PM
To: Reynold Xin
Cc: tcon...@gmail.com; Spark Dev List
Subject: Re: Hive Hash in Spark
I think this was needed to add support for bucketed Hive tables. Like Tyson
noted
Hi,
I noticed the existence of a Hive Hash partitioning implementation in Spark,
but also noticed that it's not being used, and that the Spark hash
partitioning function is presently hardcoded to Murmur3. My question is
whether Hive Hash is dead code or are their future plans to support reading
Dear Spark Community,
I have posted a SPIP to JIRA:
https://issues.apache.org/jira/browse/SPARK-26257
I look forward to your feedback on the JIRA ticket.
Best regards,
Tyson
There seems to be some desire for third party language extensions for Apache
Spark. Some notable examples include:
* C#/F# from project Mobius https://github.com/Microsoft/Mobius
* Haskell from project sparkle https://github.com/tweag/sparkle
* Julia from project Spark.jl https:/
