Task: equi-join-detect (source dataset: Auto-BI)

Your are given a database with related tables used for business intelligence analysis. Your task is to identify all key/foreign-key join relationships between the tables for this database. Recall that a join is a relationship between two tables, that allows rows from one table to be combined with rows from another, based on a set of common join columns.
 
 
No explanation needed. Please return all join relationships in the following JSON format:
{
  "joins": [
    {
      "from_table": "table-1",
      "from_column": "column-1",
      "to_table": "table-2",
      "to_column": "column-3"
    }, 
	...
  ]
}

Tables:

Table: Calendar
| Dates                   |   Year | Month Name   | FQ   | Year&Month   | Year&Quarter   |
|:------------------------|-------:|:-------------|:-----|:-------------|:---------------|
| 2020-01-01 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |
| 2020-01-02 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |
| 2020-01-03 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |
| 2020-01-04 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |
| 2020-01-05 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |
| 2020-01-06 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |
| 2020-01-07 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |
| 2020-01-08 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |
| 2020-01-09 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |
| 2020-01-10 00:00:00.000 |   2020 | January      | Q1   | January 2020 | Q1 2020        |


Table: City
| City   |   Index |
|:-------|--------:|
| City1  |       1 |
| City3  |       3 |
| City11 |      11 |
| City2  |       2 |
| City9  |       9 |
| City10 |      10 |
| City8  |       8 |
| City6  |       6 |
| City13 |      13 |
| City7  |       7 |


Table: Customer
| Customer Name   | Customer ID   |
|:----------------|:--------------|
| Dynazzy Company | ID115         |
| Quimm Company   | ID134         |
| Skippad Ltd     | ID142         |
| Kaymbo Company  | ID135         |
| Aldi Ltd        | ID137         |
| WOCKHARDT Group | ID109         |
| Epic Group      | ID116         |
| Epic Group      | ID117         |
| Muxo Group      | ID123         |
| Rhynoodle Ltd   | ID126         |


Table: Grouping
| Performanance   |   Min |   Max |
|:----------------|------:|------:|
| Top 10          |     0 |    10 |
| Rank 11-30      |    10 |    30 |
| Rank 31-50      |    30 |    50 |
| Rank 51-200     |    50 |   200 |


Table: Product
| Product    |
|:-----------|
| Product 2  |
| Product 7  |
| Product 19 |
| Product 21 |
| Product 6  |
| Product 1  |
| Product 14 |
| Product 22 |
| Product 11 |
| Product 5  |


Table: Sales
| Invoice Date            | Customer ID   | Customer Name   | City   | Product    |   Amount |
|:------------------------|:--------------|:----------------|:-------|:-----------|---------:|
| 2020-01-01 00:00:00.000 | ID115         | Dynazzy Company | City13 | Product 19 |   334.51 |
| 2020-01-01 00:00:00.000 | ID134         | Quimm Company   | City13 | Product 14 |   147.6  |
| 2020-01-01 00:00:00.000 | ID142         | Skippad Ltd     | City13 | Product 14 | -6250    |
| 2020-01-01 00:00:00.000 | ID142         | Skippad Ltd     | City13 | Product 19 | -9093.75 |
| 2020-01-01 00:00:00.000 | ID142         | Skippad Ltd     | City13 | Product 21 | -1460.09 |
| 2020-01-01 00:00:00.000 | ID142         | Skippad Ltd     | City13 | Product 6  | -2261.44 |
| 2020-01-01 00:00:00.000 | ID142         | Skippad Ltd     | City13 | Product 14 |  2083.34 |
| 2020-01-01 00:00:00.000 | ID142         | Skippad Ltd     | City13 | Product 19 |  3031.25 |
| 2020-01-01 00:00:00.000 | ID142         | Skippad Ltd     | City13 | Product 21 |   486.7  |
| 2020-01-01 00:00:00.000 | ID142         | Skippad Ltd     | City13 | Product 6  |   753.81 |

 


tables: name: Calendar
data: Calendar.csv
name: City
data: City.csv
name: Customer
data: Customer.csv
name: Grouping
data: Grouping.csv
name: Product
data: Product.csv
name: Sales
data: Sales.csv
label: Sales
Invoice Date
Calendar
Dates
output: {
    "joins": [
        {
            "from_table": "Sales",
            "from_column": "Invoice Date",
            "to_table": "Calendar",
            "to_column": "Dates"
        }
    ]
}