;>>> workers need to read/write to the checkpoint. The distributed file system
>>>> has to be immediately consistent: When one node writes to it, the other
>>>> nodes should be able to read it immediately
>>>>
>>>> The solutions/workarounds depend on wher
where you are hosting your Spark
>>> application.
>>>
>>>
>>>
>>> *From: *David Morin
>>> *Date: *Wednesday, December 23, 2020 at 11:08 AM
>>> *To: *"user@spark.apache.org"
>>> *Subject: *[EXTERNAL] Spark 3.0.
;> nodes should be able to read it immediately
>>
>> The solutions/workarounds depend on where you are hosting your Spark
>> application.
>>
>>
>>
>> *From: *David Morin
>> *Date: *Wednesday, December 23, 2020 at 11:08 AM
>> *To: *"user@s
> nodes should be able to read it immediately
>
> The solutions/workarounds depend on where you are hosting your Spark
> application.
>
>
>
> *From: *David Morin
> *Date: *Wednesday, December 23, 2020 at 11:08 AM
> *To: *"user@spark.apache.org"
> *Subject:
on where you are hosting your Spark
application.
From: David Morin
Date: Wednesday, December 23, 2020 at 11:08 AM
To: "user@spark.apache.org"
Subject: [EXTERNAL] Spark 3.0.1 Structured streaming - checkpoints fail
CAUTION: This email originated from outside of the organization. Do
Hello,
I have an issue with my Pyspark job related to checkpoint.
Caused by: org.apache.spark.SparkException: Job aborted due to stage
failure: Task 3 in stage 16997.0 failed 4 times, most recent failure: Lost
task 3.3 in stage 16997.0 (TID 206609, 10.XXX, executor 4):
