Examples
Examples
Try the starting example
- JSON Left table key frequencies [key,count]
- [["A",3],["B",1]]
- JSON Right table key frequencies [key,count]
- [["A",2],["C",4]]
- Join contribution [key,left count,right count,inner-join rows]
- [["A",3,2,6],["B",1,0,0],["C",0,4,0]]
- Predicted inner-join row count
- 6
- Many-to-many key IDs
- ["A"]
Try another scenario
- JSON Left table key frequencies [key,count]
- [["A",3],["B",1]]
- JSON Right table key frequencies [key,count]
- [["A",4],["B",1],["C",4]]
- Join contribution [key,left count,right count,inner-join rows]
- [["A",3,4,12],["B",1,1,1],["C",0,4,0]]
- Predicted inner-join row count
- 13
- Many-to-many key IDs
- ["A"]
Calculation method
Calculation method
Join contribution [key,left count,right count,inner-join rows]
For each exact key, multiply left and right frequency, absent count zero.
Predicted inner-join row count
Sum keywise frequency products.
Many-to-many key IDs
Keys whose left and right counts both exceed one.
Symbols and units
- a
- JSON Left table key frequencies [key,count]
- b
- JSON Right table key frequencies [key,count]
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Assumptions & limits
Assumptions & limits
- Exact equality inner join only; null matching semantics must be encoded as explicit included/excluded keys. No SQL execution. Supported limits: All numeric inputs must be finite. Only the explicitly described mathematical scenario is supported.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.