FAQ
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Last updated
Was this helpful?
Can't find the correct answer please ask our community in Slack channel.
The flow is a streamlined process that transforms your data, beginning with the "Source" node and ending with the "Output" node. This is similar to a file in traditional applications.
You can create new flows, rename them, make duplicates, export them, and delete them. Each table displayed within the flow is simply a preview of the final result and is not saved.
A job is a process of executing the entire flow and saving the output in a file.
We cover all SQL features and some more such as auto-flattening JSON.
When you have completed designing the flow and wish to save the result, click on the "Run" button located in the top right corner.
The computation process will begin, utilizing either cloud resources or your local computer, depending on the destination specified in the "Output" node.
The choice of resources for flow execution depends on the configuration of the "Source" and "Output" nodes. If Snowflake or PostgreSQL is connected, tabula will execute the flow using their resources.
If "Local File" is selected, execution will take place on your computer. To ensure proper job execution, the Tabula app must be running, and the computer should not be in sleep mode.
No, the application only verifies your credentials during the initial launch.
Therefore, it is safe to use sensitive information in your flows as all data is stored on your local computer. We are actively working on implementing cloud features.
Yes, the app downloads a small sample of data to generate a table preview in design mode. This sample data is stored on your local computer where Tabula is running.
All the transformations execute utilizing warehouse or DB resources.
Yes, Tabula can open it no matter the size! The default sampling is 10,000 rows, but you can change it on the Explorer page
Yes, we currently support scalar user-defined functions. To create them, please follow these instructions.
It is important to note that any changes should only be made if you are fully aware of what you are doing. Remember to only include functions that are already working in the body.
You can find custom-created functions in the directory provided. They are provided as examples. Open the *.json file in your preferred text editor (such as Notepad++ or Sublime), modify the parameters, and save with a new name. Restart Retable and use them.
For Mac OS: “/Users/%username%/Library/Application Support/tabula/latest/udfs”
For Windows: “C:\Users\%username%\AppData\Roaming\tabula\latest\udfs”
Where "%username%" is the name of the user.
You can use AI Column and AI Table nodes or generate dummy data in the New Empty Table node.
You have a limited number of trial calls. But you can add your own token generated by Open AI, and we won't limit your calls.
Go to the settings file and add your key to the field token. Restart the app.
For Mac OS: “/Users/%username%/Library/Application Support/tabula/latest/config/app.yaml”
For Windows: “C:\Users\%username%\AppData\Roaming\tabula\latest\config\app.yaml”
Where "%username%" is your name of the user.
The application is currently in closed beta and undergoing heavy development. At this time, we have connectors for PostgreSQL and Snowflake. You can export the necessary tables from your database in *.csv format and import them into Tabula. MS Excel *.xslx format is also supported.
It's important to note that *.xslx files will only work if there are no Snowflake/PostgreSQL sources in the current flow.
Theoretically, unlimited sources can be added. To be more precise, you can add up to 1024 different Source nodes.
We provide full support for PostgreSQL and Snowflake connectors as sources, targets, and for executing flows. Additionally, we support CSV and *.xslx as a source and target.
For smooth functioning of our application on Windows OS, the Microsoft Visual C++ Redistributable library needs to be present in your system. Unfortunately, this library may be missing in some systems causing a disruption to the use of our product.
Here is a simple step-by-step guide on how you can rectify this:
Initiate the download process for the redistributable library that corresponds to your particular version of Windows OS.
Once downloaded, install the Microsoft Visual C++ Redistributable library by following the on-screen instructions.
After successfully installing the library, restart your system to complete the installation process.
Now, continue with the installation or running of the Tabula app.
Please note that this issue doesn't affect Mac OS users and thus these instructions are only applicable to Windows users.
If you're encountering an Unknown Authentication Error, it could be due to incomplete authentication steps.
After you've installed and opened the app, you should see a 'Sign In' button. Once clicked, a browser window will appear with a login page. Depending on your method of registration, use the Email and Password fields if you've set a password from the registration email link. Conversely, if registered via Google mail, use the Google account login button.
Upon successful signing in, a popup should appear - it is crucial to click on 'Open Tabula' to access the app's home page. Avoid switching the authorization window or delaying to press the 'Open Tabula' button because the authorization token has a limited lifespan. Delays may lead to the Unknown Authentication Error.
The mentioned video provides a comprehensive guide on how to execute the login process.
In case you're unable to move past the Unknown Authentication Error screen, simply refresh the page by selecting View -> Reload or restart the app. Then, repeat the authorization steps.
The log files a hosted below. If an error occurs during a job execution you can find logs on the job page Three dot button → Show logs.
Locating the folder where log files are stored can be a challenging task, particularly if the option to hide system files and folders is enabled in the operating system's settings.
For Mac OS:
Open any folder in Finder.
Press Command + Shift + Period.
See the hidden files appear in the folder.
Navigate to “/Users/%username%/Library/Application Support/tabula/latest/logs”
For Windows 10:
Open File Explorer from the taskbar.
Select View → Options → Change folder and search options.
Select the View tab and, in Advanced settings, select Show hidden files, folders, and drives and OK.
Navigate to “C:\Users\%username%\AppData\Roaming\tabula\latest\logs”
For Windows 11:
Open File Explorer from the taskbar.
Select View → Show → Hidden items.
Navigate to “C:\Users\%username%\AppData\Roaming\tabula\latest\logs”
Where "%username%" is your name of the user.
Yes, handling large databases is one of our main priorities. If you encounter unique problems when working with large databases, please report this issue in the channel.
In the field model to set the model that is available with your plan, use fields maxTokensInAnswer \ maxTokensSent to set max GPT tokens in request and answer. See Open AI for the settings for different models.
We plan to provide more connectors in future releases. To stay updated on product developments and share feedback on which integrations you need the most, join our for Data Analysts and Engineers.
Visit the Microsoft official website or click to directly navigate to the download page of Microsoft Visual C++ Redistributable.
Can't find the correct answer please ask our community in Slack channel.
