There’s no one best for these questions. The question can be more refined with
a specific use case and for that which is the best data store.
> On Jun 25, 2015, at 12:02 AM, Sinha, Ujjawal (SFO-MAP)
> wrote:
>
> Hi Guys
>
>
> I am very new for spark , I have 2 question
>
>
> 1) which lan
I am fairly new to spark streaming and i have a basic question on how spark
streaming works on s3 bucket which is periodically getting new files once
in 10 mins.
When i use spark streaming to process these files in this s3 path, will it
process all the files in this path (old+new files) every batch
Hello all,
I have few questions regarding spark streaming :
* I am wondering anyone uses spark streaming with workflow orchestrators
such as data pipeline/SWF/any other framework. Is there any advantages
/drawbacks on using a workflow orchestrator for spark streaming?
*How do you guys manage the
gt; Cheers,
>
>
>
>
> Dr Mich Talebzadeh
>
> LinkedIn
> https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
>
> http://talebzadehmich.wordpress.com
>
>
>> On 22 June 2016 at 15:54, pandees waran wrote:
>> Hi
For my question (2), From my understanding checkpointing ensures the recovery
from failures.
Sent from my iPhone
> On Jun 22, 2016, at 10:27 AM, pandees waran wrote:
>
> In general, if you have multiple steps in a workflow :
> For every batch
> 1.stream data from s3
> 2.wri
All,
did anyone ever work on processing Ion formatted messages in Spark? Ion
format is superset of JSON. All JSONs are valid IONs, but the reverse is
not true.
For more details on Ion;
http://amznlabs.github.io/ion-docs/
Thanks.
It's based on "micro batching" model.
Sent from my iPhone
> On Aug 23, 2016, at 8:41 AM, Aseem Bansal wrote:
>
> I was reading this article https://www.inovex.de/blog/storm-in-a-teacup/ and
> it mentioned that spark streaming actually mini-batch not actual streaming.
>
> I have not used stre
All,
We have an use case in which 2 spark streaming jobs in same EMR cluster.
I am thinking of allowing multiple streaming contexts and run them as 2
separate spark-submit with wait for app completion set to false.
With this, the failure detection and monitoring seems obscure and doesn't
seem to
have you tried using "." access method?
e.g:
ds1.select("name","addresses[0].element.city")
On Sun, Nov 20, 2016 at 9:59 AM, shyla deshpande
wrote:
> The following my dataframe schema
>
> root
> |-- name: string (nullable = true)
> |-- addresses: array (nullable = true)
> |
I have encountered the similar error when the schema / datatypes are
conflicting in those 2 parquet files. Are you sure that the 2 individual files
are in the same structure with similar datatypes. If not you have to fix this
by enforcing the default values for the missing values to make the str
All, May I know what exactly changed in 2.1.1 which solved this problem?
Sent from my iPhone
> On Sep 17, 2017, at 11:08 PM, Anastasios Zouzias wrote:
>
> Hi,
>
> I had a similar issue using 2.1.0 but not with Kafka. Updating to 2.1.1
> solved my issue. Can you try with 2.1.1 as well and repo
Hi,
I am newbie to spark sql and i would like to know about how to read all the
columns from a file in spark sql. I have referred the programming guide
here:
http://people.apache.org/~tdas/spark-1.0-docs/sql-programming-guide.html
The example says:
val people =
sc.textFile("examples/src/main/re
Do we have any equivalent scala functions available for NVL() and CASE
expressions to use in spark sql?
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