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: Actors
|   id | Actor             |
|-----:|:------------------|
|    0 | Jessica Chastain  |
|    1 | Andre Keuck       |
|    2 | Bill Pullman      |
|    3 | Stellan Skarsgård |
|    4 | Rod Taylor        |
|    5 | Deanna Durbin     |
|    6 | Anne Hathaway     |
|    7 | Bill Paxton       |
|    8 | Michelle Pfeiffer |
|    9 | Jack Nicholson    |


Table: Actors_film_id
|   unique_id |   film_id |   Actor_id |
|------------:|----------:|-----------:|
|         152 |        63 |         29 |
|         715 |       255 |         29 |
|        1093 |       389 |         29 |
|        1479 |      1126 |         29 |
|        1656 |      1274 |         29 |
|        2030 |      1565 |         29 |
|        2224 |      1691 |         29 |
|        3523 |      2841 |         29 |
|        3681 |      2944 |         29 |
|        3871 |      3108 |         29 |


Table: CalendarTable
| Date                    |   Year |
|:------------------------|-------:|
| 1912-01-01 00:00:00.000 |   1912 |
| 1912-01-02 00:00:00.000 |   1912 |
| 1912-01-03 00:00:00.000 |   1912 |
| 1912-01-04 00:00:00.000 |   1912 |
| 1912-01-05 00:00:00.000 |   1912 |
| 1912-01-06 00:00:00.000 |   1912 |
| 1912-01-07 00:00:00.000 |   1912 |
| 1912-01-08 00:00:00.000 |   1912 |
| 1912-01-09 00:00:00.000 |   1912 |
| 1912-01-10 00:00:00.000 |   1912 |


Table: Directors
|   id | Director           |
|-----:|:-------------------|
|    0 | Kathryn Bigelow    |
|    1 | Ben Coccio         |
|    2 | Jake Kasdan        |
|    3 | Hans Petter Moland |
|    4 | Clyde Geronimi     |
|    5 | Henry Koster       |
|    6 | Lone Scherfig      |
|    7 | Carl Franklin      |
|    8 | Michael Hoffman    |
|    9 | Miloš Forman       |


Table: Directors_film_id
|   unique_id |   film_id |   Director_id |
|------------:|----------:|--------------:|
|           0 |         4 |             0 |
|           1 |         5 |             1 |
|           2 |         6 |             2 |
|           3 |         9 |             3 |
|           4 |        14 |             4 |
|           5 |        14 |          4808 |
|           6 |        14 |           839 |
|           7 |        15 |             5 |
|           8 |        17 |             6 |
|           9 |        18 |             7 |


Table: film_table
| film                                      |   id | release_date   |   running_time_mins | country       | language   | budget   |   box_office | box_off_adj   | budget_adj   |
|:------------------------------------------|-----:|:---------------|--------------------:|:--------------|:-----------|:---------|-------------:|:--------------|:-------------|
| Operation Mad Ball                        | 1002 |                |                 105 | United States | English    |          |      1850000 |               |              |
| A Map of the World (film)                 | 1784 |                |                 125 | United States | English    |          |       544538 |               |              |
| How to Save a Marriage and Ruin Your Life | 1912 |                |                 102 | United States | English    |          |      2500000 |               |              |
| Hangar 18 (film)                          | 2647 |                |                  97 | United States | English    |          |     11000000 |               |              |
| Georgia (1995 film)                       | 2980 |                |                 115 | United States | English    |          |      1110104 |               |              |
| The Maddening                             | 3069 |                |                  95 | United States | English    |          |         5000 |               |              |
| Neil Simon's I Ought to Be in Pictures    | 3603 |                |                 108 | United States | English    |          |      6968359 |               |              |
| Cobb (film)                               | 4391 |                |                 128 | United States | English    |          |      1007600 |               |              |
| Ultimate X: The Movie                     | 4526 |                |                  47 | United States | English    |          |      4100000 |               |              |
| Seven Wonders of the World (film)         | 4579 |                |                 106 | United States | English    |          |     32100000 |               |              |


Table: Productioncompanies
|   id | Productioncompany         |
|-----:|:--------------------------|
|    0 | Columbia Pictures         |
|    1 | nan                       |
|    2 | Castle Rock Entertainment |
|    3 | Walt Disney Productions   |
|    4 | Universal Pictures        |
|    5 | Random House Films        |
|    6 | Lynda Obst Productions    |
|    7 | Fantasy Films             |
|    8 | Catch 23 Entertainment    |
|    9 | Hammer Film Productions   |


Table: Productioncompanies_film_id
|   unique_id |   film_id |   Productioncompany_id |
|------------:|----------:|-----------------------:|
|           3 |         5 |                      1 |
|           5 |         9 |                      1 |
|          11 |        18 |                      1 |
|          23 |        29 |                      1 |
|          24 |        31 |                      1 |
|          30 |        38 |                      1 |
|          42 |        53 |                      1 |
|          46 |        57 |                      1 |
|          49 |        65 |                      1 |
|          51 |        69 |                      1 |

 


tables: name: Actors
data: Actors.csv
name: Actors_film_id
data: Actors_film_id.csv
name: CalendarTable
data: CalendarTable.csv
name: Directors
data: Directors.csv
name: Directors_film_id
data: Directors_film_id.csv
name: film_table
data: film_table.csv
name: Productioncompanies
data: Productioncompanies.csv
name: Productioncompanies_film_id
data: Productioncompanies_film_id.csv
label: Actors_film_id
film_id
film_table
id
Actors_film_id
Actor_id
Actors
id
Productioncompanies_film_id
film_id
film_table
id
Productioncompanies_film_id
Productioncompany_id
Productioncompanies
id
Directors_film_id
Director_id
Directors
id
Directors_film_id
film_id
film_table
id
film_table
release_date
CalendarTable
Date
output: {
    "joins": [
        {
            "from_table": "Actors_film_id",
            "from_column": "film_id",
            "to_table": "film_table",
            "to_column": "id"
        },
        {
            "from_table": "Actors_film_id",
            "from_column": "Actor_id",
            "to_table": "Actors",
            "to_column": "id"
        },
        {
            "from_table": "Productioncompanies_film_id",
            "from_column": "film_id",
            "to_table": "film_table",
            "to_column": "id"
        },
        {
            "from_table": "Productioncompanies_film_id",
            "from_column": "Productioncompany_id",
            "to_table": "Productioncompanies",
            "to_column": "id"
        },
        {
            "from_table": "Directors_film_id",
            "from_column": "Director_id",
            "to_table": "Directors",
            "to_column": "id"
        },
        {
            "from_table": "Directors_film_id",
            "from_column": "film_id",
            "to_table": "film_table",
            "to_column": "id"
        },
        {
            "from_table": "film_table",
            "from_column": "release_date",
            "to_table": "CalendarTable",
            "to_column": "Date"
        }
    ]
}