Hi Eliza,
As I mentioned to you in the Kafka mailing list when you asked this there,
there are pros and cons to all of the technologies you've mentioned, and
you really need to sit down and try each solution to see what suits your
needs best.
Kind regards,
Liam Clarke
On Wed, Aug 21, 2019 at 9:
Well, you are posting on the Spark mailing list. Though for streaming I'd
recommend Flink over Spark any day of the week. Flink was written as a
streaming platform from the beginning quickly aligning the API with the
theoretical framework of Google's Dataflow whitepaper. It's awesome for
streaming.
Hi,
What is the definition of real time here?
The engineering definition of real time is roughly fast enough to be
interactive. However, I put a stronger definition. In real time application
or data, there is no such thing as an answer which is supposed to be late
and correct. The timeliness is p
Also I found a excellent article for comparision.
https://www.linkedin.com/pulse/spark-streaming-vs-flink-storm-kafka-streams-samza-choose-prakash
regards.
on 2019/8/21 16:53, Eliza wrote:
Hi,
on 2019/8/21 16:44, Aziret Satybaldiev wrote:
In my experience, Kafka + Spark streaming + (perhaps HB
Hi,
on 2019/8/21 16:44, Aziret Satybaldiev wrote:
In my experience, Kafka + Spark streaming + (perhaps HBase if you want
to store the metrics) is so far the best combo.
Not only because the technology is mature, but also because there are a
lot of examples available on the web and books.
They t
Hi Eliza,
In my experience, Kafka + Spark streaming + (perhaps HBase if you want to
store the metrics) is so far the best combo.
Not only because the technology is mature, but also because there are a lot
of examples available on the web and books.
They typically should cover most of what you woul
Hello,
We have all of spark, flink, storm, kafka installed.
For realtime streaming calculation, which one is the best above?
Like other big players, the logs in our stack are huge.
Thanks.
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