Gentle Reminder on the query.
On Wed, Mar 1, 2023 at 8:32 PM Kartikey Pant
wrote:
> Hi,
>
> We are using Table API with Flink (Java). Our use case requires us to use
> Multiple Aggregate Functions most of which the Table API already supports.
> However, when we went ahead with the Table APIs, we
Hello! Maybe you could help with debezium/vervica connectors in optimizing memory consumption for large changes in a single transaction using vervica flink-oracle-cdc-connector.Environment:flink - 1.15.1oracle-cdc - 2.3oracle - 19.3When updating large number of rows in a single transaction I get th
Hello,Try Infinispan - https://debezium.io/documentation/reference/stable/connectors/oracle.html#oracle-event-buffering15:12, 3 марта 2023 г., Alexandr Dmitrov :Hello! Maybe you could help with debezium/vervica connectors in optimizing memory consumption for large changes in a single transaction us
Hi-
Hoping someone can give me more understanding and a sense of timing flink
leveraging glue tables. Specifically I would like to leverage a glue table
data source via an AWS hosted Zeppelin notebook (instead of referencing a
kinesis data stream or s3 bucket directly). Additionally I will ne
Hi Flink User group,
I bumped into the following error when using FlinkSQL, version 1.15.3
* StreamPhysicalDeduplicate doesn't support consuming update and delete
changes which is produced by node ChangelogNormalize
Essentially I was trying to dedup over an upsert kafka topic.
I wonder if
Thanks Alexis,
I will be trying that out today. If it works I will share back and try adding
it to the docs.
From: Alexis Sarda-Espinosa
Sent: Thursday, March 2, 2023 3:33:03 PM
To: Ivan Webber
Cc: user
Subject: Re: [EXTERNAL] Re: Secure Azure Credential Conf
Hi Flink Users,
We are looking to use Flink Postgres CDC but then we noticed it only
supports single thread reading during the snapshot reading phase.
Is there any plan to support parallel snapshot reading for postgres in the
near future? Looks like this is not an issue for mysql.
Thanks
Leon
Hello,
My team has a Flink streaming job that does a stateful join across two high
throughput kafka topics. This results in a large amount of data ser/de and
shuffling (about 1gb/s for context). We're running into a bottleneck on
this shuffling step. We've attempted to optimize our flink configura
