Spark is processing engine not storage or cache ,you can dump your results
back to Cassandra, if you see latency then you can use cache to dump spark
results.
In short answer is NO,spark doesn't supporter give any api to give you
cache kind of storage.
Directly reading from dataset millions of
So you are now providing the data on-demand through spark?
I suggest you change your API to query from cassandra and store the results
from Spark back there, that way you will have to process the whole dataset just
once and cassandra is suitable for that kind of workloads.
-T
> On 10 Jun 2018,
I think your requirement is that of OLTP system. Spark & Cassandra are more
suitable for batch kind of jobs (They can be used for OLTP but there would
be a performance hit)
Deepak
"The greatness of a nation can be judged by the way its animals are
treated. Please consider stopping the cruelty by
Hi,
I'm using spark on top of cassandra as backend CRUD of a Restfull Application.
Most of Rest API's retrieve huge amount of data from cassandra and doing a lot
of aggregation on them in spark which take some seconds.
Problem: sometimes the output result would be a big list which make clien
