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Hi all, do you use snowflake workspace or dedicated DWH from the writer with some other 3rd party tool that uses SQLAlchemy under the hood?
Would you benefit from us providing you direct SQLAlchemy connection string in this popup ui?
Please let me know!
Hi Community, I was not sure it has been mentioned here, but there's a new anonymization processor (MD5, SHA512 + salt):
Data Anonymization processor | Keboola Developer Portal
This processor enables you to anonymize specified columns of an input table. In the configuration you specify the method of anonymization and the tables and the respective columns you wish to anonymize. Specified tables and their specified columns are anonymized, the rest is passed through to out/tables.
example of the use mentioned in the documentation:
kds_consulting_team / kds-team.processor-data-anonymization / README.md
Hi community,
Since we are having increased requests on new functionality enabling, I think this simple diagram will be useful to determine the project eligibility:
The crucial piece is the move to Transformations V2 that enables the queue and hence a slew of new exciting features. Some of them heavily influence speed/costs ratio.
For more information and feedback please use the feedback button in the platform - our product team will be glad to hear any feedback that will help us improve!
Hi guys, some of you might notice spammy postings once in a while - we are on it with our platform provider. Please have a patience, you could help us by reporting those posts!
There is a stellar Keboola Academy course for Generic Extractor - I would encourage everyone to start there:
However, I think this guide might be pretty useful for kickstarting new configuration:
Official documentation:
(Important) If you bounce on some serious issues and you cannot get a solution from your peers, stop wasting your time further and switch to a custom component (Python, PHP, etc.)
To configure your first Generic Extractor, follow the tutorial for ‘Basic Configuration’. Also, review the following sections: Generic Extractor > Generic Extractor Tutorial >
Note: It is important to make use of Column Mapping feature in order to avoid occurrence of duplicates during extraction.
To understand the specific parts of an existing configuration, check the Configuration Map (aka Parameter Map) and review following sections: Generic Extractor > Configuration >
Iterate through each underlined item of the Configuration Map and review details. Alternatively, go to this page containing useful links for various sections of the Generic Extractor.
Review various Authentication types
Note: Don’t consume yourself with advanced authentication types e.g. OAuth, in the beginning. Start with ‘URL Query, ‘Basic HTTP’, ‘Login’ and know where to come back to in case another authentication type is required.
Adopted from an internal article by @Michal Hruska @Keboola
Here are many ways to share data:
https://help.keboola.com/catalog/
The data catalog represents an overview of data shared to and from the project. The data catalog allows you to share data in a very efficient, controlled and auditable way.
There are several options how you can share data:
This writer loads single or multiple tables from your current project into a different Keboola Connection project. The component can be used in situations where Data Catalog cannot, e.g., moving data between two different organizations or regions.
https://help.keboola.com/components/writers/storage/storage-api
Extractor uses source project storage API token to setup a data extraction tunnel between source project and destination (current project). API token can be limited to buckets, tables, or a single table if needed.
https://help.keboola.com/components/extractors/storage/storage-api/
TBD - as per platform capability feature request
Direct connection to Keboola storage through storage API, as described here:
https://keboola.docs.apiary.io/
Like [3] and [4], it requires the Keboola API token, which can be limited as mentioned before. Storage API supports quick sync and more robust async data load requests, as well as data preview requests, etc. More in the official documentation.
Since we are bringing a feature parity between different stacks (mostly existing stacks and pay-as-you-go one), I think it might be beneficial to discuss the new features and publish a bit of a guide how to do the same (for testing/developing SQL query in workspaces. Lets have a look on SQL workspaces now:
A workspace serves several purposes and can be used as
When a workspace is created, it enters the Active state and can be used.
Keboola Sandbox | Keboola Workspace |
|---|---|
| 1 click setup | 1 click setup |
| Single sandbox per user x project | Multiple private or shared Workspaces |
| No table unload | UI-based load/unload (user can also add new tables afterwards) |
| Scaling up via support ticket | UI-based scaling up (*some features may come later) |
| Has pre-set duration | Can be terminated, resumed & deleted |
How-to create workspace to develop and test SQL queries - you can create workspace by clicking on the button on the right:
then you can specify if the workspace should be shared:
once its up, you can click on the workspace detail:
you can see the input mapping has been correctly set (workspace created from transformation):
just click on credentials (link on the right) to get the same creds as you would be used to with "old" sandbox:
Let us know what is your experience working with Sandboxes and Workspaces, which features you miss and how can we improve it!
Hi all, as you may know, currently our GenEx does not support using user defined fields in child jobs:
(https://developers.keboola.com/extend/generic-extractor/configuration/config/#user-data).
Since this question appears once in a while in our support system, we would love your feedback on this missing functionality. Is here someone who would appreciate such feature? Would you be able to describe your case? Have you already submitted wishlist(idea) item? Thanks!
CC: @František Řehoř
It behaves in two different ways:
[1]
now() - cooldown period- so that it immediately starts recording the events.[2]
To to sum up - when created the cooldown is not in effect for the first run. When updated it's immediately recalculated, but it's still effective.
