You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The type inference for function arguments and result type would increase the code reuse of user defined Bandicoot functions dramatically.
Here is an example of a function which takes one relation parameter and returns a relation as well. The function requires the input argument to have a string attribute called "quality". It could work on any relations which match this criteria and therefor the following code reuse would be possible:
This would make Bandicoot also very practical in scenarios where the data structure is not completely known, yet a calculation is needed or some information needs to be persisted and the rest of the data just flows through.
Here is an example of an HTTP service which captures the users and leaves the rest of the data untouched:
Any CSV tabular data could be piped through this function which contains the "user" column, for example capturing users for orders and processing them further:
cat orders.csv | \
curl --data-binary @- http://localhost:12345/CaptureUsers | \
... some other processing of the orders.csv file ...
The text was updated successfully, but these errors were encountered:
The type inference for function arguments and result type would increase the code reuse of user defined Bandicoot functions dramatically.
Here is an example of a function which takes one relation parameter and returns a relation as well. The function requires the input argument to have a string attribute called "quality". It could work on any relations which match this criteria and therefor the following code reuse would be possible:
This would make Bandicoot also very practical in scenarios where the data structure is not completely known, yet a calculation is needed or some information needs to be persisted and the rest of the data just flows through.
Here is an example of an HTTP service which captures the users and leaves the rest of the data untouched:
Any CSV tabular data could be piped through this function which contains the "user" column, for example capturing users for orders and processing them further:
The text was updated successfully, but these errors were encountered: