We are happy to announce the availability of Spark 2.3.2!
Apache Spark 2.3.2 is a maintenance release, based on the branch-2.3
maintenance branch of Spark. We strongly recommend all 2.3.x users to
upgrade to this stable release.
To download Spark 2.3.2, head over to the download page:
The spark-init ConfigMap is used for the init-container that is responsible
for downloading remote dependencies. The k8s submission client run by
spark-submit should create the ConfigMap and add a ConfigMap volume in the
driver pod. Can you provide the command you used to run the job?
On Wed, Sep
Hello ,
We're running spark 2.3.1 on kubernetes v1.11.0 and our driver pods from
k8s are getting stuck in initializing state like so:
NAME
READY STATUS RESTARTS AGE
my-pod-fd79926b819d3b34b05250e23347d0e7-driver 0/1 Init:0/1 0
18h
And
We're running spark 2.3.1 on kubernetes v1.11.0 and our driver pods from
k8s are getting stuck in initializing state like so:
NAME
READY STATUS RESTARTS AGE
my-pod-fd79926b819d3b34b05250e23347d0e7-driver 0/1 Init:0/1 0
18h
And from *kubectl
Our driver pods from k8s are getting stuck in initializing state like so:
NAME
READY STATUS RESTARTS AGE
my-pod-fd79926b819d3b34b05250e23347d0e7-driver 0/1 Init:0/1 0
18h
And from *kubectl describe pod*:
*Warning FailedMount 9m (x128
You can use Spark sql window function , something like
df.createOrReplaceTempView(“dfv”)
Select count(eventid) over ( partition by start_time, end_time orderly
start_time) from dfv
Sent from my iPhone
> On Sep 26, 2018, at 11:32 AM, Debajyoti Roy wrote:
>
> The problem statement and an
Cannot reproduce your situation.
Can you share Spark version?
Welcome to
__
/ __/__ ___ _/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.2.0
/_/
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_92)
Type
Our driver pods from k8s are getting stuck in initializing state like so:
NAME
READY STATUS RESTARTS AGE
my-pod-fd79926b819d3b34b05250e23347d0e7-driver 0/1 Init:0/1 0
18h
And from *kubectl describe pod*:
*Warning FailedMount 9m (x128
Hi Ilan/Yinan,
My observation is as follows:
The dependent files specified with “--py-files
http://10.75.145.25:80/Spark/getNN.py” are being downloaded and available in
the container at
“/var/data/spark-c163f15e-d59d-4975-b9be-91b6be062da9/spark-61094ca2-125b-48de-a154-214304dbe74/”.
I guess we
The problem statement and an approach to solve it using windows is
described here:
https://stackoverflow.com/questions/52509498/given-events-with-start-and-end-times-how-to-count-the-number-of-simultaneous-e
Looking for more elegant/performant solutions, if they exist. TIA !
Thanks, I'll check it out.
On Wed, Sep 26, 2018 at 6:25 PM Shahab Yunus wrote:
> Hi there. Have you seen this link?
> https://medium.com/@mrpowers/manually-creating-spark-dataframes-b14dae906393
>
>
> It shows you multiple ways to manually create a dataframe.
>
> Hope it helps.
>
> Regards,
>
It looks like the native R process is terminated from buffer overflow. Do you
know how much data is involved?
From: Junior Alvarez
Sent: Wednesday, September 26, 2018 7:33 AM
To: user@spark.apache.org
Subject: spark.lapply
Hi!
I’m using spark.lapply() in
Hi there. Have you seen this link?
https://medium.com/@mrpowers/manually-creating-spark-dataframes-b14dae906393
It shows you multiple ways to manually create a dataframe.
Hope it helps.
Regards,
Shahab
On Wed, Sep 26, 2018 at 8:02 AM Kuttaiah Robin wrote:
> Hello,
>
> Currently I have
Hi,
I'm looking to have spark jobs access S3 with temporary credentials. I've seen
some examples around AssumeRole, but I have a scenario where the temp
credentials are provided by GetFederationToken. Is there anything that can
help, or do I need to use boto to execute GetFederationToken, and
Hello,
Currently I have Oracle database table with description as shown below;
Table INSIGHT_ID_FED_IDENTIFIERS
-
CURRENT_INSTANCE_ID VARCHAR2(100)
PREVIOUS_INSTANCE_ID VARCHAR2(100)
Sample values in the table basically output of select * from
Hi!
I'm using spark.lapply() in sparkR on a mesos service I get the following crash
randomly (The spark.lapply() function is called around 150 times, some times it
crashes after 16 calls, other after 25 calls and so on...it is completely
random, even though the data used in the actual call is
Using FAIR mode.
If no other way. I think there is a limitation on number of parallel jobs
that spark can run. Is there a way that more number of jobs can run in
parallel. This is alright because, this sparkcontext would only be used
during web service calls.
I looked at spark configuration page
Spark has sc.wholeTextFiles() which returns RDD of tuple. First element of
tuple if the file name and second element is the file content.
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I am doing a pivot transformation on an input dataset
Following input schema
=
|-- c_salutation: string (nullable = true)
|-- c_preferred_cust_flag: string (nullable = true)
|-- integer_type_col: integer (nullable = false)
|-- long_type_col: long
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