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: Abfrage1
|     id | title                          | overview                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |   popularity |   revenue | posterPath                       | releaseDate   |   voteAvg |   voteCount |   runtime | tagline                                          |
|-------:|:-------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------:|----------:|:---------------------------------|:--------------|----------:|------------:|----------:|:-------------------------------------------------|
|  20982 | Naruto Shippuden the Movie     | Demons that once almost destroyed the world, are revived by someone. To prevent the world from being destroyed, the demon has to be sealed and the only one who can do it is the shrine maiden Shion from the country of demons, who has two powers; one is sealing demons and the other is predicting the deaths of humans. This time Naruto's mission is to guard Shion, but she predicts Naruto's death. The only way to escape it, is to get away from Shion, which would leave her unguarded, then the demon, whose only goal is to kill Shion will do so, thus meaning the end of the world. Naruto decides to challenge this "prediction of death." |      270.804 |         0 | /vDkct38sSFSWJIATlfJw0l3QOIR.jpg | 2007-08-04    |       7.1 |         314 |        94 |                                                  |
|  40170 | Mortal Kombat: Rebirth         | MORTAL KOMBAT: REBIRTH is a short film released by Kevin Tancharoen (Director) in 2010. It was originally made as a proof of concept for Tancharoen's pitch to Warner Brothers for a reboot movie franchise. This 8-minute short features an intricate fight scene choreographed by Larnell Stovall. It also reintroduces classic Mortal Kombat characters, including: Jax (Michael Jai White), Sonya Blade (Jeri Ryan), Johnny Cage (Matt Mullins), Scorpion (Ian Anthony Dale), Baraka (Lateef Crowder) and Shang Tsung (James Lew).                                                                                                                     |      280.737 |         0 | /78JIw8JICcPKDIURCJJq2F43iIZ.jpg | 2010-06-08    |       7   |          85 |         8 |                                                  |
| 317442 | The Last: Naruto the Movie     | Two years after the events of the Fourth Great Ninja War, the moon that Hagoromo Otsutsuki created long ago to seal away the Gedo Statue begins to descend towards the world, threatening to become a meteor that would destroy everything on impact. Amidst this crisis, a direct descendant of Kaguya Otsutsuki named Toneri Otsutsuki attempts to kidnap Hinata Hyuga but ends up abducting her younger sister Hanabi. Naruto and his allies now mount a rescue mission before finding themselves embroiled in a final battle to decide the fate of everything.                                                                                         |      178.825 |         0 | /bAQ8O5Uw6FedtlCbJTutenzPVKd.jpg | 2014-12-06    |       7.8 |         919 |       114 |                                                  |
| 385687 | Fast & Furious 10              | The tenth and penultimate installment of the Fast and Furious franchise.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |      469.311 |         0 | /2DyEk84XnbJEdPlGF43crxfdtHH.jpg |               |       0   |           0 |         0 |                                                  |
| 412656 | Chaos Walking                  | Two unlikely companions embark on a perilous adventure through the badlands of an unexplored planet as they try to escape a dangerous and disorienting reality, where all inner thoughts are seen and heard by everyone.                                                                                                                                                                                                                                                                                                                                                                                                                                   |      571.196 |         0 | /9kg73Mg8WJKlB9Y2SAJzeDKAnuB.jpg | 2021-02-24    |       7.1 |         647 |       109 | No one escapes the noise.                        |
| 471498 | Oxygen                         | A woman wakes in a cryogenic chamber with no recollection of how she got there, and must find a way out before running out of air.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         |      309.748 |         0 | /u74DFoZGTcZ8cuHO8nvQkCqXEVP.jpg | 2021-05-12    |       6.8 |         489 |       100 | No escape. No memory. 90 min to live.            |
| 484718 | Coming 2 America               | Prince Akeem Joffer is set to become King of Zamunda when he discovers he has a son he never knew about in America – a street savvy Queens native named Lavelle. Honoring his royal father's dying wish to groom this son as the crown prince, Akeem and Semmi set off to America once again.                                                                                                                                                                                                                                                                                                                                                              |      224.236 |         0 | /nWBPLkqNApY5pgrJFMiI9joSI30.jpg | 2021-03-05    |       6.8 |        1364 |       110 | A sequel is in the heir.                         |
| 501929 | The Mitchells vs. The Machines | A quirky, dysfunctional family's road trip is upended when they find themselves in the middle of the robot apocalypse and suddenly become humanity's unlikeliest last hope.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |      167.79  |         0 | /mI2Di7HmskQQ34kz0iau6J1vr70.jpg | 2021-04-22    |       8.1 |         553 |       114 | Saving the world can be a trip.                  |
| 509635 | Alone                          | A recently widowed traveler is kidnapped by a cold blooded killer, only to escape into the wilderness where she is forced to battle against the elements as her pursuer closes in on her.                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |      212.237 |         0 | /n9OzZmPMnVrV0cMQ7amX0DtBkQH.jpg | 2020-09-10    |       6.2 |         248 |        98 | What are you running from?                       |
| 509967 | 6 Underground                  | After faking his death, a tech billionaire recruits a team of international operatives for a bold and bloody mission to take down a brutal dictator.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |      199.385 |         0 | /lnWkyG3LLgbbrIEeyl5mK5VRFe4.jpg | 2019-12-10    |       6.3 |        3059 |       128 | They say no one can save the world. Meet no one. |


Table: Abfrage3
|   weekNr |   cases-recovered-deaths |
|---------:|-------------------------:|
|       15 |                   298889 |
|       16 |                   313802 |
|       17 |                   312229 |
|       18 |                   282379 |
|       19 |                   229475 |
|       20 |                   173999 |
|       21 |                   118808 |


Table: Covid
| cases-LAG(cases) OVER (ORDER BY weekNr ASC)   | deaths-LAG(deaths) OVER (ORDER BY weekNr ASC)   | recovered-LAG(recovered) OVER (ORDER BY weekNr ASC)   |   weekNr | concat("KW ", weekNr)   |
|:----------------------------------------------|:------------------------------------------------|:------------------------------------------------------|---------:|:------------------------|
|                                               |                                                 |                                                       |       15 | KW 15                   |
| 122298                                        | 1038                                            | 106347                                                |       16 | KW 16                   |
| 129847                                        | 1592                                            | 129828                                                |       17 | KW 17                   |
| 106656                                        | 1555                                            | 134951                                                |       18 | KW 18                   |
| 77072                                         | 1378                                            | 128598                                                |       19 | KW 19                   |
| 57825                                         | 1283                                            | 112018                                                |       20 | KW 20                   |
| 36892                                         | 1105                                            | 90978                                                 |       21 | KW 21                   |


Table: CovidAsStrings
|   weekNr | cases      | deaths   | recovered   |
|---------:|:-----------|:---------|:------------|
|       15 |            |          |             |
|       16 | 122.3 Tsd. | 1038     | 106.3 Tsd.  |
|       17 | 129.8 Tsd. | 1592     | 129.8 Tsd.  |
|       18 | 106.7 Tsd. | 1555     | 135.0 Tsd.  |
|       19 | 77.1 Tsd.  | 1378     | 128.6 Tsd.  |
|       20 | 57.8 Tsd.  | 1283     | 112.0 Tsd.  |
|       21 | 36.9 Tsd.  | 1105     | 91.0 Tsd.   |


Table: Location
| Titel                             | countryId   | cname                    |   weekNr |   Popularität |   movieId | AnzahlTrends   |
|:----------------------------------|:------------|:-------------------------|---------:|--------------:|----------:|:---------------|
| Our Friend                        | US          | United States of America |       16 |       201.468 |    583903 |                |
| Grand Isle                        | US          | United States of America |       16 |       201.706 |    560192 |                |
| Fast & Furious 10                 | US          | United States of America |       16 |       204.437 |    385687 |                |
| Venom                             | US          | United States of America |       16 |       204.586 |    335983 |                |
| Captain Marvel                    | US          | United States of America |       16 |       204.95  |    299537 |                |
| Underwater                        | US          | United States of America |       16 |       205.846 |    443791 |                |
| John Wick: Chapter 3 - Parabellum | US          | United States of America |       16 |       209.898 |    458156 |                |
| Mulan                             | US          | United States of America |       16 |       211.638 |    337401 |                |
| Alone                             | US          | United States of America |       16 |       212.237 |    509635 |                |
| 6 Underground                     | US          | United States of America |       16 |       214.284 |    509967 |                |


Table: MovieCountryTrendWeek
|   weekNr |   popularity | title                                  | Land                     | ISO_ID   |
|---------:|-------------:|:---------------------------------------|:-------------------------|:---------|
|       16 |      351.836 | Tenet                                  | United States of America | US       |
|       16 |      471.365 | Breach                                 | United States of America | US       |
|       16 |      201.706 | Grand Isle                             | United States of America | US       |
|       16 |      287.331 | The Tax Collector                      | United States of America | US       |
|       16 |      322.291 | The SpongeBob Movie: Sponge on the Run | United States of America | US       |
|       16 |      381.846 | Honest Thief                           | United States of America | US       |
|       16 |      261.94  | Roald Dahl's The Witches               | United States of America | US       |
|       16 |      313.88  | Extraction                             | United States of America | US       |
|       16 |      881.48  | Cherry                                 | United States of America | US       |
|       16 |      338.126 | Bloodshot                              | United States of America | US       |


Table: MovieGenres_Popularity
|   weekNr |   genreId |   AnzahlTrends | Genre           |   Popularität |
|---------:|----------:|---------------:|:----------------|--------------:|
|       16 |        28 |             56 | Action          |      40674.7  |
|       16 |        14 |             29 | Fantasy         |      22090.4  |
|       16 |        53 |             34 | Thriller        |      21952.6  |
|       16 |        12 |             30 | Adventure       |      21362.6  |
|       16 |       878 |             22 | Science Fiction |      18545.3  |
|       16 |        80 |             18 | Crime           |      12139.6  |
|       16 |        18 |             25 | Drama           |      11865.8  |
|       16 |        35 |             24 | Comedy          |      11091.3  |
|       16 |        16 |             19 | Animation       |      10781.1  |
|       16 |     10751 |             14 | Family          |       6778.99 |


Table: movieratings covid
|   weekNr |       cases |   deaths |   recovered |
|---------:|------------:|---------:|------------:|
|       15 | 3.15556e+06 |    81111 | 2.77556e+06 |
|       16 | 3.27785e+06 |    82149 | 2.8819e+06  |
|       17 | 3.4077e+06  |    83741 | 3.01173e+06 |
|       18 | 3.51436e+06 |    85296 | 3.14668e+06 |
|       19 | 3.59143e+06 |    86674 | 3.27528e+06 |
|       20 | 3.64925e+06 |    87957 | 3.3873e+06  |
|       21 | 3.68614e+06 |    89062 | 3.47828e+06 |


Table: MovieTrendAge
|   weekNr | agegroups   |   count(*) |
|---------:|:------------|-----------:|
|       16 | 0-19        |         22 |
|       16 | 20-29       |         76 |
|       16 | 30-39       |        143 |
|       16 | 40-49       |        176 |
|       16 | 50-59       |        188 |
|       16 | 60-69       |         84 |
|       16 | 70-79       |         26 |
|       16 | 80<         |         11 |
|       17 | 0-19        |          9 |
|       17 | 20-29       |         72 |


Table: MovieTrendsCountry
|   weekNr |   AnzahlTrends | Land      | ISO_ID   |
|---------:|---------------:|:----------|:---------|
|       16 |              2 | Argentina | AR       |
|       16 |              2 | Australia | AU       |
|       16 |              1 | Belgium   | BE       |
|       16 |              6 | Canada    | CA       |
|       16 |              1 | Chile     | CL       |
|       16 |              8 | China     | CN       |
|       16 |              1 | Cyprus    | CY       |
|       16 |              2 | Germany   | DE       |
|       16 |              3 | Spain     | ES       |
|       16 |              3 | France    | FR       |


Table: MovieTrendsGender
|   weekNr |   count(*) |   gender |
|---------:|-----------:|---------:|
|       16 |        170 |        0 |
|       16 |        278 |        1 |
|       16 |        694 |        2 |
|       16 |          2 |        3 |
|       17 |        182 |        0 |
|       17 |        267 |        1 |
|       17 |        678 |        2 |
|       17 |          2 |        3 |
|       18 |        190 |        0 |
|       18 |        259 |        1 |


Table: MWP
|   weekNr |   movieId | title                                     |   voteAvg |   popularity |   voteCount |
|---------:|----------:|:------------------------------------------|----------:|-------------:|------------:|
|       16 |    399566 | Godzilla vs. Kong                         |       8.2 |      4459.3  |        4848 |
|       16 |    460465 | Mortal Kombat                             |       8.2 |      3500.81 |         741 |
|       16 |    615678 | Thunder Force                             |       5.8 |      2556.11 |         404 |
|       16 |    791373 | Zack Snyder's Justice League              |       8.5 |      2375.45 |        5096 |
|       16 |    634528 | The Marksman                              |       7.1 |      2163.72 |         149 |
|       16 |    615457 | Nobody                                    |       8.5 |      1931.29 |         689 |
|       16 |    412656 | Chaos Walking                             |       7.4 |      1656.47 |         436 |
|       16 |    632357 | The Unholy                                |       5.5 |      1619.63 |          43 |
|       16 |    527774 | Raya and the Last Dragon                  |       8.3 |      1432.34 |        2399 |
|       16 |    664767 | Mortal Kombat Legends: Scorpion's Revenge |       8.4 |      1221.54 |         863 |


Table: SeriesGenres_Popularity
|   weekNr |   genreId |   Popularität |   AnzahlTrends | Genre              |
|---------:|----------:|--------------:|---------------:|:-------------------|
|       16 |        18 |     29931.3   |             72 | Drama              |
|       16 |     10765 |     16974.1   |             35 | Sci-Fi & Fantasy   |
|       16 |     10759 |     16184     |             35 | Action & Adventure |
|       16 |        80 |      7263.41  |             24 | Crime              |
|       16 |      9648 |      6010.43  |             19 | Mystery            |
|       16 |     10768 |      5315.73  |              2 | War & Politics     |
|       16 |        16 |      4520.35  |             14 | Animation          |
|       16 |        35 |      2995.68  |             15 | Comedy             |
|       16 |     10766 |      1336.36  |              6 | Soap               |
|       16 |     10762 |       947.965 |              3 | Kids               |


Table: SeriesTrendAge
|   weekNr |   InSeries | agegroups   |
|---------:|-----------:|:------------|
|       16 |         62 | 0-19        |
|       16 |        190 | 20-29       |
|       16 |        186 | 30-39       |
|       16 |        128 | 40-49       |
|       16 |         48 | 50-59       |
|       16 |         14 | 60-69       |
|       16 |          4 | 70-79       |
|       16 |          4 | 80<         |
|       17 |         59 | 0-19        |
|       17 |        184 | 20-29       |


Table: SeriesTrendsCountry
|   weekNr |   AnzahlTrends | Land           | ISO_ID   |
|---------:|---------------:|:---------------|:---------|
|       16 |              3 | Argentina      | AR       |
|       16 |              5 | Canada         | CA       |
|       16 |              3 | Colombia       | CO       |
|       16 |              2 | Germany        | DE       |
|       16 |              4 | Spain          | ES       |
|       16 |              1 | France         | FR       |
|       16 |              4 | United Kingdom | GB       |
|       16 |              1 | Ireland        | IE       |
|       16 |              1 | Italy          | IT       |
|       16 |              8 | Japan          | JP       |


Table: SeriesTrendsGender
|   weekNr |   count(*) |   gender |
|---------:|-----------:|---------:|
|       16 |        205 |        0 |
|       16 |        311 |        1 |
|       16 |        495 |        2 |
|       16 |          1 |        3 |
|       17 |        204 |        0 |
|       17 |        303 |        1 |
|       17 |        504 |        2 |
|       17 |          1 |        3 |
|       18 |        201 |        0 |
|       18 |        285 |        1 |


Table: SWP
|   weekNr |   seriesId | title                |   voteAvg |   popularity |   voteCount |
|---------:|-----------:|:---------------------|----------:|-------------:|------------:|
|       16 |       1416 | Grey's Anatomy       |       8.2 |     1016.61  |        5905 |
|       16 |      76669 | Elite                |       8.2 |      313.803 |        6304 |
|       16 |       1622 | Supernatural         |       8.2 |      272.073 |        5035 |
|       16 |       4604 | Smallville           |       8.2 |      263.146 |        2365 |
|       16 |     104877 | You Knock on My Door |       8.2 |      253.201 |         229 |
|       16 |      76773 | Station 19           |       8.2 |      223.366 |         781 |
|       16 |      60797 | Scorpion             |       8.2 |      223.169 |        2290 |
|       16 |      12971 | Dragon Ball Z        |       8.2 |      220.251 |        2232 |
|       16 |       4057 | Criminal Minds       |       8.2 |      189.969 |        2281 |
|       16 |      16286 | Yo soy Betty, la fea |       8.2 |      173.603 |        2003 |


Table: TopMovie
|   weekNr |   movieId | title                        |     max | GROUP_CONCAT(g.genre SEPARATOR ', ')                  | concat(mwp.voteAvg, "/10")   |
|---------:|----------:|:-----------------------------|--------:|:------------------------------------------------------|:-----------------------------|
|       16 |    399566 | Godzilla vs. Kong            | 4459.3  | Action, Science Fiction                               | 8.2/10                       |
|       17 |    460465 | Mortal Kombat                | 6983.02 | Adventure, Fantasy, Action, Thriller, Science Fiction | 7.9/10                       |
|       18 |    460465 | Mortal Kombat                | 4870.2  | Adventure, Fantasy, Action, Thriller, Science Fiction | 7.8/10                       |
|       19 |    567189 | Tom Clancy's Without Remorse | 4918.31 | Adventure, Action, Thriller, War                      | 7.3/10                       |
|       20 |    460465 | Mortal Kombat                | 2112.76 | Adventure, Fantasy, Action, Thriller, Science Fiction | 7.6/10                       |
|       21 |    632357 | The Unholy                   | 5972.41 | Horror                                                | 7.2/10                       |


Table: TopPersonWeekGender
|   weekNr |   gender | name                       |
|---------:|---------:|:---------------------------|
|       16 |        2 | Jason Statham              |
|       16 |        1 | Scarlett Johansson         |
|       17 |        2 | Keanu Reeves               |
|       17 |        1 | Scarlett Johansson         |
|       18 |        2 | Jason Statham              |
|       18 |        1 | Scarlett Johansson         |
|       19 |        2 | Philippe Leroy             |
|       19 |        1 | Scarlett Johansson         |
|       20 |        2 | Ángel 'Angelito' Rodríguez |
|       20 |        1 | Angelina Jolie             |


Table: TopSeries
|   weekNr |   seriesId | title                             |     max | GROUP_CONCAT(g.genre SEPARATOR ', ')                        | concat(swp.voteAvg,"/10")   |
|---------:|-----------:|:----------------------------------|--------:|:------------------------------------------------------------|:----------------------------|
|       16 |      88396 | The Falcon and the Winter Soldier | 5146.16 | Drama, Action & Adventure, Sci-Fi & Fantasy, War & Politics | 7.9/10                      |
|       17 |      88396 | The Falcon and the Winter Soldier | 2580.79 | Drama, Action & Adventure, Sci-Fi & Fantasy, War & Politics | 7.9/10                      |
|       18 |      95557 | Invincible                        | 1885.16 | Animation, Drama, Action & Adventure                        | 8.9/10                      |
|       19 |      88396 | The Falcon and the Winter Soldier | 1013.58 | Drama, Action & Adventure, Sci-Fi & Fantasy, War & Politics | 7.9/10                      |
|       20 |     120168 | Who Killed Sara?                  | 1527.66 | Drama, Crime, Mystery                                       | 7.8/10                      |
|       21 |      63174 | Lucifer                           | 1461.07 | Crime, Sci-Fi & Fantasy                                     | 8.5/10                      |


Table: TrendsAgeGroupsWeek
|   weekNr |   weekNr2 |   count |   InSeries | agegroups   |
|---------:|----------:|--------:|-----------:|:------------|
|       16 |        16 |      22 |         62 | 0-19        |
|       16 |        16 |      76 |        190 | 20-29       |
|       16 |        16 |     143 |        186 | 30-39       |
|       16 |        16 |     176 |        128 | 40-49       |
|       16 |        16 |     188 |         48 | 50-59       |
|       16 |        16 |      84 |         14 | 60-69       |
|       16 |        16 |      26 |          4 | 70-79       |
|       16 |        16 |      11 |          4 | 80<         |
|       17 |        17 |       9 |         59 | 0-19        |
|       17 |        17 |      72 |        184 | 20-29       |

 


tables: name: Abfrage1
data: Abfrage1.csv
name: Abfrage3
data: Abfrage3.csv
name: Covid
data: Covid.csv
name: CovidAsStrings
data: CovidAsStrings.csv
name: Location
data: Location.csv
name: MovieCountryTrendWeek
data: MovieCountryTrendWeek.csv
name: MovieGenres_Popularity
data: MovieGenres_Popularity.csv
name: movieratings covid
data: movieratings covid.csv
name: MovieTrendAge
data: MovieTrendAge.csv
name: MovieTrendsCountry
data: MovieTrendsCountry.csv
name: MovieTrendsGender
data: MovieTrendsGender.csv
name: MWP
data: MWP.csv
name: SeriesGenres_Popularity
data: SeriesGenres_Popularity.csv
name: SeriesTrendAge
data: SeriesTrendAge.csv
name: SeriesTrendsCountry
data: SeriesTrendsCountry.csv
name: SeriesTrendsGender
data: SeriesTrendsGender.csv
name: SWP
data: SWP.csv
name: TopMovie
data: TopMovie.csv
name: TopPersonWeekGender
data: TopPersonWeekGender.csv
name: TopSeries
data: TopSeries.csv
name: TrendsAgeGroupsWeek
data: TrendsAgeGroupsWeek.csv
label: Covid
weekNr
movieratings covid
weekNr
Abfrage3
weekNr
movieratings covid
weekNr
MWP
weekNr
Covid
weekNr
SWP
weekNr
Covid
weekNr
TopSeries
weekNr
Covid
weekNr
Covid
weekNr
TopMovie
weekNr
MovieGenres_Popularity
weekNr
Covid
weekNr
SeriesGenres_Popularity
weekNr
Covid
weekNr
MovieTrendsGender
weekNr
Covid
weekNr
SeriesTrendsGender
weekNr
Covid
weekNr
MovieTrendsCountry
weekNr
Covid
weekNr
SeriesTrendsCountry
weekNr
Covid
weekNr
Covid
weekNr
CovidAsStrings
weekNr
MovieCountryTrendWeek
weekNr
Covid
weekNr
Location
weekNr
Covid
weekNr
MovieTrendAge
weekNr
Covid
weekNr
TopPersonWeekGender
weekNr
Covid
weekNr
SeriesTrendAge
weekNr
Covid
weekNr
TrendsAgeGroupsWeek
weekNr
Covid
weekNr
output: {
    "joins": [
        {
            "from_table": "Covid",
            "from_column": "weekNr",
            "to_table": "movieratings covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Abfrage3",
            "from_column": "weekNr",
            "to_table": "movieratings covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "MWP",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SWP",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "TopSeries",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Covid",
            "from_column": "weekNr",
            "to_table": "TopMovie",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieGenres_Popularity",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SeriesGenres_Popularity",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieTrendsGender",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SeriesTrendsGender",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieTrendsCountry",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SeriesTrendsCountry",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Covid",
            "from_column": "weekNr",
            "to_table": "CovidAsStrings",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieCountryTrendWeek",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "Location",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "MovieTrendAge",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "TopPersonWeekGender",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "SeriesTrendAge",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        },
        {
            "from_table": "TrendsAgeGroupsWeek",
            "from_column": "weekNr",
            "to_table": "Covid",
            "to_column": "weekNr"
        }
    ]
}