Hi all
we are struggling a bit with a fairly simple stream that is supposed to map
columns from a topic populated by a Source Jdbc Connector into a format
destined for a Sink Jdbc Connector.
Our tables look something like this:
(These are not the actual column names we are using though)
SOURC
Why is quantity a STRING? Should it be a numeric?
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Robin Moffatt | Senior Developer Advocate | ro...@confluent.io | @rmoff
On Tue, 8 Sep 2020 at 08:52, Rainer Schamm wrote:
> Hi all
>
> we are struggling a bit with a fairly simple stream that is supposed to
> map columns from a topic popu
We are unfortunately not in control of the source and destination tables.
In the source table the 'quantity' column is numeric.
In the destination table 'quantityDest' column is a string.
So the question is how can we convert from numeric value to string value using
some KSQL syntax or functio
Nvm. This was an issue on my side.
On Mon, Sep 7, 2020 at 3:03 PM Samuel Cantero wrote:
> Hey all,
>
> I'd like to understand why I can't find the metrics for mm2 [1]. By using
> jconsole, I can find the mbeans for kafka.connect, kafka.consumer and
> kafka.producer but I can't find anything on k
Hi Cedric,
I'm not sure if this is directly applicable, but you might get a feel for
how Kafka relates to more traditional databases from this post (afaik this
is one of the seminal talks relating the two ideas):
https://www.confluent.io/blog/turning-the-database-inside-out-with-apache-samza/
You
Everything's down to requirements. I'm unclear on yours. I tried to
look at your website to see if I could pick up any clues but upsail.co
(and just in case, upsail.com) don't exist, so I dunno.
Some questions, rhetorical really:
Is there any reason a standard SQL database would not do - what doe
I’m no expert, but I think Kafka, Kafka Connect and Kafka Streams could be a
great fit for your use case.
Use Kafka Connect to pull data from the various data sources, into a topic or
topics and then use Kafka Streams to do the joins, enrichment, and / or
analysis needed to determine a record
