CODEWITHSUNDEEP
apache-sparkapache-kafkaarchitecture
Sankar
Sankar

Reputation: 413

Can Kafka-Spark Streaming pair be used for both batch+real time data?

H All,

I am currently working on developing an architecture which should be able to handle both real time and batch data(coming from disparate sources and point solutions - third party tools). The existing architecture is old school and uses mostly RDBMS(I am not going to to go detail in that).

What I have come up with is two different pipeline - one for batch data(sqoop/spark/hive) and the other for real time data(kafka-spark stream).

But I have been told to use kafka-spark streaming pair for handling all kinds of data.

If anyone has any experience working on kafka-spark streaming pair for handling all kinds of data, could you please give me a brief details if this could be a viable solution and better than having two different pipeline.

Thanks in advance!

Upvotes: 0

Views: 345

Answers (2)

Rishu S
Rishu S

Reputation: 3968

What I have come up with is two different pipeline - one for batch data(sqoop/spark/hive) and the other for real time data(kafka-spark stream).

Pipeline 1: Sqoop is a good choice for batch load, but it will slow in performance because underlying architecture is still on map-reduce. Though there are options to run sqoop on spark, but didn't try that. Once the data is in HDFS then you can use hive, which is great solution for batch processing. Having said that you can replace sqoop with Spark, if you are worrying about the RDMS fetch time. You can also do a batch transformations in spark also. I would say this is good solution.

Pipeline 2: Kafka and Spark streaming are the most obvious choice and is a good choice. But, If you are using Confluent dist. of Kafka then you could replace most of the spark transformations with K-SQL, K-Streams which will create a realtime transformations.

I would say, its good to have separate system for batching and one for real-time. This is what is lambda architecture. But if you are looking for a more unified framework, then you can try Apache Beam, which provides an unified framework for both batch and realtime processing. You can choose from multiple runners to execute your query.

Hope this helps :)

Upvotes: 1

dossani
dossani

Reputation: 1948

Lambda architecture would be the way to go! Hope this link gives you enough ideas: https://dzone.com/articles/lambda-architecture-how-to-build-a-big-data-pipeli

Thanks much.

Upvotes: 1

Related Questions