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: Aggregation Table
|   Average | Value   |
|----------:|:--------|
|     174.1 | Measure |


Table: Append1
| Type   | Material   | Description   |
|:-------|:-----------|:--------------|
| A      | X          | plastic       |
| A      | X          | plastic       |
| B      | Y          | metal         |
| B      | Z          | rubber        |
| A      | 1          | cover         |
| A      | 2          | top           |
| B      | 3          | middle        |
| A      | a          | type1         |
| A      | b          | type2         |


Table: Calendar
| Date                    |   Week |
|:------------------------|-------:|
| 2020-01-01 00:00:00.000 |      1 |
| 2020-01-02 00:00:00.000 |      1 |
| 2020-01-03 00:00:00.000 |      1 |
| 2020-01-04 00:00:00.000 |      1 |
| 2020-01-05 00:00:00.000 |      2 |
| 2020-01-06 00:00:00.000 |      2 |
| 2020-01-07 00:00:00.000 |      2 |
| 2020-01-08 00:00:00.000 |      2 |
| 2020-01-09 00:00:00.000 |      2 |
| 2020-01-10 00:00:00.000 |      2 |


Table: csvs (2)
| Name      | Extension   | Date accessed           | Date modified           | Date created            | Folder Path           |
|:----------|:------------|:------------------------|:------------------------|:------------------------|:----------------------|
| four.csv  | .csv        | 2020-09-07 18:23:56.040 | 2020-08-22 10:20:34.360 | 2020-04-02 16:00:29.983 | C:\temp\powerbi\csvs\ |
| one.csv   | .csv        | 2020-09-06 23:58:17.526 | 2020-08-22 10:19:57.986 | 2020-04-02 16:00:29.993 | C:\temp\powerbi\csvs\ |
| three.csv | .csv        | 2020-09-06 23:58:17.526 | 2020-08-22 10:20:22.366 | 2020-04-02 16:00:30.000 | C:\temp\powerbi\csvs\ |
| two.csv   | .csv        | 2020-09-06 23:58:17.526 | 2020-08-22 10:20:10.813 | 2020-04-02 16:00:30.006 | C:\temp\powerbi\csvs\ |


Table: csvs
| Source.Name   |   column1 |   column2 |   column3 | date                    |
|:--------------|----------:|----------:|----------:|:------------------------|
| four.csv      |         1 |        10 |       100 | 2022-01-01 00:00:00.000 |
| four.csv      |         2 |        20 |       200 | 2022-01-01 00:00:00.000 |
| four.csv      |         3 |        30 |       300 | 2022-01-01 00:00:00.000 |
| one.csv       |         1 |        10 |       100 | 2019-01-01 00:00:00.000 |
| one.csv       |         2 |        20 |       200 | 2019-01-01 00:00:00.000 |
| one.csv       |         3 |        30 |       300 | 2019-01-01 00:00:00.000 |
| three.csv     |         1 |        10 |       100 | 2021-01-01 00:00:00.000 |
| three.csv     |         2 |        20 |       200 | 2021-01-01 00:00:00.000 |
| three.csv     |         3 |        30 |       300 | 2021-01-01 00:00:00.000 |
| two.csv       |         1 |        10 |       100 | 2020-01-01 00:00:00.000 |


Table: Production data
|   prod_order_number |   P21_hour_qty |
|--------------------:|---------------:|
|                1001 |              1 |
|                1001 |              1 |
|                1002 |              2 |
|                1003 |              3 |


Table: Query1
| Type   | Material   | Description   |
|:-------|:-----------|:--------------|
| A      | X          | plastic       |
| A      | X          | plastic       |
| B      | Y          | metal         |
| B      | Z          | rubber        |
| A      | 1          | cover         |
| A      | 2          | top           |
| B      | 3          | middle        |
| A      | a          | type1         |
| A      | b          | type2         |


Table: Sheet1
|   Column1 |   Column2 |   Column3 |
|----------:|----------:|----------:|
|         1 |         1 |         1 |
|         2 |         2 |         2 |
|         3 |         3 |         3 |


Table: Table (10)
| Column1   |   Column2 |
|:----------|----------:|
| A         |    0.9957 |
| B         |    0.9955 |
| C         |    0.991  |
| D         |    0.9865 |
| E         |    0.9865 |
| F         |    0.9784 |


Table: Table (11)
| Column1                 | Custom   |
|:------------------------|:---------|
| 2020-01-01 00:00:00.000 | 1/2/2020 |


Table: Table (12)
|   Auto ID |   Roll No | Name   |   Marks | Gender   |   Top N |
|----------:|----------:|:-------|--------:|:---------|--------:|
|         1 |     12324 | ABC    |     515 | M        |       3 |
|         2 |      2323 | LMN    |     525 | M        |       2 |
|         3 |     23234 | XYN    |     535 | F        |       1 |
|         4 |     65655 | DEF    |     525 | M        |       2 |
|         5 |    345345 | PRS    |     510 | F        |       4 |


Table: Table (13)
| Time                    |   device |     m1 |    m2 |    m3 |   State |   Cycles Desired |   Cycle Change |   Cycles |   Cycles Count |
|:------------------------|---------:|-------:|------:|------:|--------:|-----------------:|---------------:|---------:|---------------:|
| 2020-09-01 00:01:00.000 |        4 | -0.103 |   0   | 100   |       1 |                1 |              1 |        1 |              1 |
| 2020-09-01 12:56:00.000 |        4 | -0.103 |   0   | 100   |       1 |                1 |              0 |        1 |              1 |
| 2020-09-01 13:26:00.000 |        4 | -0.103 |   0   | 100   |       1 |                1 |              0 |        1 |              1 |
| 2020-09-01 13:26:00.000 |        4 | -0.594 |   0   | 100   |       4 |                1 |              0 |        1 |              1 |
| 2020-09-01 13:31:00.000 |        4 | -0.594 |  -0.1 | 100   |       4 |                1 |              0 |        1 |              1 |
| 2020-09-01 13:36:00.000 |        4 | -0.654 | -15   |  99.9 |       4 |                1 |              0 |        1 |              1 |
| 2020-09-01 20:31:00.000 |        4 |  0.02  | -24.7 |  77.3 |       4 |                1 |              0 |        1 |              1 |
| 2020-09-01 20:33:00.000 |        4 | 16.927 |   0   |  77.8 |       3 |                1 |              0 |        1 |              1 |
| 2020-09-01 20:38:00.000 |        4 | 17.407 |   1.5 |  79.1 |       3 |                1 |              0 |        1 |              1 |
| 2020-09-01 20:58:00.000 |        4 | 17.331 |   7.3 |  84.4 |       3 |                1 |              0 |        1 |              1 |


Table: Table (14)
| Selection   | First Name   | Last Name   | Department   | Salary   | Source   |
|:------------|:-------------|:------------|:-------------|:---------|:---------|
| Office      | ABC          | Corp        | NA           |          |          |
| A           | Josephine    | Darakjy     | Payroll      | 42000    | Internal |
| B           | Lenna        | Paprocki    | Research     | 58000    | Internal |
| C           | Simona       | Morasca     | Real Estate  | 75000    | External |
| D           | Leota        | Dilliard    | Marketing    | 60000    | External |


Table: Table (15)
| Weekending Date         | Test Date               | Student Name   |   Test Score |
|:------------------------|:------------------------|:---------------|-------------:|
| 2020-08-07 00:00:00.000 | 2020-08-03 00:00:00.000 | Ron            |         0.95 |
| 2020-08-07 00:00:00.000 | 2020-08-03 00:00:00.000 | Rudy           |         0.89 |
| 2020-08-07 00:00:00.000 | 2020-08-06 00:00:00.000 | James          |         0.87 |
| 2020-08-07 00:00:00.000 | 2020-08-05 00:00:00.000 | Ron            |         0.91 |
| 2020-08-14 00:00:00.000 | 2020-08-11 00:00:00.000 | Rudy           |         0.87 |
| 2020-08-21 00:00:00.000 | 2020-08-18 00:00:00.000 | James          |         0.93 |
| 2020-08-14 00:00:00.000 | 2020-08-12 00:00:00.000 | Ron            |         0.8  |
| 2020-08-14 00:00:00.000 | 2020-08-12 00:00:00.000 | Rudy           |         0.92 |
| 2020-08-21 00:00:00.000 | 2020-08-17 00:00:00.000 | Ron            |         0.85 |


Table: Table (16)
|   ID | Submitted Date          | Date Resolved           |
|-----:|:------------------------|:------------------------|
|    1 | 2020-02-17 00:00:00.000 | 2020-08-26 00:00:00.000 |
|    2 | 2020-02-27 00:00:00.000 | 2020-08-27 00:00:00.000 |
|    3 | 2020-04-29 00:00:00.000 | 2020-08-24 00:00:00.000 |
|    4 | 2020-04-30 00:00:00.000 | 2020-08-24 00:00:00.000 |
|    5 | 2020-05-04 00:00:00.000 | 2020-08-24 00:00:00.000 |
|    6 | 2020-05-07 00:00:00.000 | 2020-08-26 00:00:00.000 |
|    7 | 2020-05-22 00:00:00.000 | 2020-08-24 00:00:00.000 |
|    8 | 2020-06-04 00:00:00.000 | 2020-08-28 00:00:00.000 |
|    9 | 2020-06-10 00:00:00.000 | 2020-08-24 00:00:00.000 |
|   10 | 2020-06-11 00:00:00.000 | 2020-08-28 00:00:00.000 |


Table: Table (17)
|   Member Count |   Age - Category | District - Category   |
|---------------:|-----------------:|:----------------------|
|              2 |               23 | z                     |
|              6 |               23 | z                     |
|              5 |               23 | x                     |
|              4 |               29 | s                     |
|              1 |               29 | s                     |
|              2 |               29 | z                     |
|              9 |               36 | z                     |
|             10 |               36 | x                     |
|             24 |               36 | x                     |
|              9 |               36 | z                     |


Table: Table (18)
|   ID |   Time_1 |   Time_2 Desired |   Time_2 |
|-----:|---------:|-----------------:|---------:|
|    1 |       30 |               10 |       10 |
|    1 |       30 |               10 |       10 |
|    1 |       30 |               10 |       10 |
|    2 |       50 |               50 |       50 |
|    3 |       40 |               20 |       20 |
|    3 |       40 |               20 |       20 |
|    4 |       80 |               20 |       20 |
|    4 |       80 |               20 |       20 |
|    4 |       80 |               20 |       20 |
|    4 |       80 |               20 |       20 |


Table: Table (19)
| Date                    | SalesPerson   | Item   |   Value |
|:------------------------|:--------------|:-------|--------:|
| 2020-05-01 00:00:00.000 | ABC           | MM     |     100 |
| 2020-08-01 00:00:00.000 | ABC           | MM     |      30 |
| 2020-08-01 00:00:00.000 | XYZ           | NN     |      50 |
| 2020-09-05 00:00:00.000 | ABC           | QQ     |      60 |
| 2020-09-05 00:00:00.000 | XYZ           | NN     |      70 |


Table: Table (2)
|   SampleID | Date                    |   Outcome | Custom               |   Custom.1 |
|-----------:|:------------------------|----------:|:---------------------|-----------:|
|          1 | 2020-01-01 00:00:00.000 |         1 | 9/6/2020 10:57:54 PM |    5998.96 |
|          2 | 2020-01-01 00:00:00.000 |         0 | 9/6/2020 10:57:54 PM |    5998.96 |
|          3 | 2020-01-01 00:00:00.000 |         1 | 9/6/2020 10:57:54 PM |    5998.96 |


Table: Table (20)
|   Time |   Rain mm |   Event Group |
|-------:|----------:|--------------:|
|      1 |         1 |             1 |
|      2 |         2 |             1 |
|      3 |         1 |             1 |
|      4 |         0 |             0 |
|      5 |         0 |             0 |
|      6 |         1 |             2 |
|      7 |         4 |             2 |
|      8 |         2 |             2 |
|      9 |         1 |             2 |
|     10 |         0 |             0 |


Table: Table (21)
| Customer   | Product   |   Serial | StartDate               | EndDate    |   Period (M) | Free / Subscription   |   Given Free | StartDate (FreeWare)    | EndDate (FreeWare)   | Serial (FreeWare)   | Serial (Sub)   | StartDate (Sub)         | EndDate (Sub)   | Converted?   |
|:-----------|:----------|---------:|:------------------------|:-----------|-------------:|:----------------------|-------------:|:------------------------|:---------------------|:--------------------|:---------------|:------------------------|:----------------|:-------------|
| A          | WA        |    15685 | 2019-01-01 00:00:00.000 | 31/12/2019 |           12 | Free                  |            1 | 2020-01-01 00:00:00.000 | 31/5/2020            | 67732               | 60719          | 2020-01-07 00:00:00.000 | 30/6/2021       | Y            |
| A          | WA        |    67732 | 2020-01-01 00:00:00.000 | 31/5/2020  |            5 | Free                  |            1 | 2020-01-01 00:00:00.000 | 31/5/2020            | 67732               | 60719          | 2020-01-07 00:00:00.000 | 30/6/2021       | Y            |
| A          | WA        |    12114 | 2020-01-06 00:00:00.000 | 30/6/2020  |            1 | Sub                   |            1 | 2020-01-01 00:00:00.000 | 31/5/2020            | 67732               | 60719          | 2020-01-07 00:00:00.000 | 30/6/2021       | Y            |
| A          | WA        |    60719 | 2020-01-07 00:00:00.000 | 30/6/2021  |           12 | Sub                   |            1 | 2020-01-01 00:00:00.000 | 31/5/2020            | 67732               | 60719          | 2020-01-07 00:00:00.000 | 30/6/2021       | Y            |
| A          | QWS       |    32789 | 2019-01-01 00:00:00.000 | 31/12/2019 |           12 | Free                  |            1 | 2019-01-01 00:00:00.000 | 31/12/2019           | 32789               |                |                         |                 | N            |
| A          | KS        |    48065 | 2020-01-07 00:00:00.000 | 30/6/2021  |           12 | Sub                   |            0 |                         |                      |                     | 48065          | 2020-01-07 00:00:00.000 | 30/6/2021       | N            |
| B          | WA        |    18944 | 2020-01-01 00:00:00.000 | 31/5/2020  |            5 | Free                  |            1 | 2020-01-01 00:00:00.000 | 31/5/2020            | 18944               | 56311          | 2020-01-06 00:00:00.000 | 30/6/2020       | Y            |
| B          | WA        |    56311 | 2020-01-06 00:00:00.000 | 30/6/2020  |            1 | Sub                   |            1 | 2020-01-01 00:00:00.000 | 31/5/2020            | 18944               | 56311          | 2020-01-06 00:00:00.000 | 30/6/2020       | Y            |
| B          | KS        |    77724 | 2020-01-07 00:00:00.000 | 30/6/2021  |           12 | Sub                   |            0 |                         |                      |                     | 77724          | 2020-01-07 00:00:00.000 | 30/6/2021       | N            |
| C          | QWS       |    19615 | 2020-01-07 00:00:00.000 | 30/6/2021  |           12 | Sub                   |            0 |                         |                      |                     | 19615          | 2020-01-07 00:00:00.000 | 30/6/2021       | N            |


Table: Table (22)
|   id |   results | threshold   | number   |
|-----:|----------:|:------------|:---------|
|    1 |       101 |             |          |
|    1 |       104 |             |          |
|    1 |       600 | 0.9         | 40       |
|    1 |       101 |             |          |
|    1 |       500 | 0.4         | 0        |
|    2 |       101 |             |          |
|    2 |       101 |             |          |
|    2 |       101 |             |          |
|    2 |       101 |             |          |
|    3 |       500 | 0.2         | 0        |


Table: Table (22)B
|   id |   max | threshold   | number   |
|-----:|------:|:------------|:---------|
|    1 |   600 | 0.9         | 40       |
|    2 |   101 |             |          |
|    3 |   500 | 0.2         | 0        |


Table: Table (23)
|   Date Rev |   Revenue | CustomerUID   |
|-----------:|----------:|:--------------|
|  202000601 |       100 | ABC           |
|  202000701 |       200 | ABC           |
|  202000801 |       300 | ABC           |
|  202000901 |       400 | ABC           |


Table: Table (23a)
|   Tender Start Date |   Tender End Date |   Tender Value | CustomerUID   |   Actual Revenue |
|--------------------:|------------------:|---------------:|:--------------|-----------------:|
|           202000701 |         202000801 |            600 | ABC           |              500 |


Table: Table (23b)
| CustomerUID   |
|:--------------|
| ABC           |


Table: Table (24)
| Client Name               | Column          | Column 2        | Column 3        | Column 4        |
|:--------------------------|:----------------|:----------------|:----------------|:----------------|
| Microsoft Corporation Ltd | Microsoft       | Microsoft       | Microsoft       | Microsoft       |
| BARCLAYS (LLP)            | Barclays        |                 | Barclays (aBc)  | Barclays (      |
| CaSey General             | Casey           |                 | ernst and young | Casey           |
| LLP Ernst and Young       | Ernst and Young | Ernst and Young | ernst and young | Ernst and Young |
| ASTRAZENCALimimited AMT   | Astrazenca      | Astrazenca      | astrazenca      | Astrazenca      |


Table: Table (24a)
| Ongoing Projects   |
|:-------------------|
| Microsoft          |
| Barclays           |
| Casey              |
| Ernst and Young    |
| Astrazenca         |


Table: Table (24b)
| Ongoing Projects   |   Index |
|:-------------------|--------:|
| Microsoft          |       1 |
| Barclays (ABC)     |       2 |
| Casey's            |       3 |
| Ernst and Young    |       4 |
| Astrazenca         |       5 |


Table: Table (24c)
|   Index |   Value | Ongoing Projects   | Search    | Match   |
|--------:|--------:|:-------------------|:----------|:--------|
|       1 |       1 | Microsoft          | M         |         |
|       1 |       2 | Microsoft          | Mi        |         |
|       1 |       3 | Microsoft          | Mic       |         |
|       1 |       4 | Microsoft          | Micr      |         |
|       1 |       5 | Microsoft          | Micro     |         |
|       1 |       6 | Microsoft          | Micros    |         |
|       1 |       7 | Microsoft          | Microso   |         |
|       1 |       8 | Microsoft          | Microsof  |         |
|       1 |       9 | Microsoft          | Microsoft |         |
|       2 |       1 | Barclays (ABC)     | B         | 1       |


Table: Table (25)
| LinkName   | Date                    |   Column |
|:-----------|:------------------------|---------:|
| A          | 2020-08-15 00:00:00.000 |        0 |
| A          | 2020-08-16 00:00:00.000 |        0 |
| A          | 2020-08-17 00:00:00.000 |        0 |
| A          | 2020-08-18 00:00:00.000 |        0 |
| A          | 2020-08-19 00:00:00.000 |        0 |
| A          | 2020-08-20 00:00:00.000 |        0 |
| A          | 2020-08-21 00:00:00.000 |        1 |
| B          | 2020-08-15 00:00:00.000 |        0 |
| B          | 2020-08-16 00:00:00.000 |        0 |
| B          | 2020-08-17 00:00:00.000 |        0 |


Table: Table (26)
|   Column1 |
|----------:|
|      2016 |
|      2017 |
|      2018 |


Table: Table (27)
| Name   |   Employee Number | Position         | Date of Birth           | Age   |
|:-------|------------------:|:-----------------|:------------------------|:------|
| A      |                 1 | Customer Service | 1990-01-01 00:00:00.000 | 30-50 |
| B      |                 2 | Mechanic         | 1981-01-01 00:00:00.000 | 30-50 |
| C      |                 3 | Painter          | 1975-01-02 00:00:00.000 | 30-50 |
| D      |                 4 | Mechanic         | 1978-06-15 00:00:00.000 | 30-50 |


Table: Table (28)
| Product   | Month    |   Net Revenue |
|:----------|:---------|--------------:|
| Aluminum  | January  |           100 |
| Steel     | January  |            50 |
| Aluminum  | January  |           120 |
| Wood      | January  |            30 |
| Steel     | February |            60 |
| Steel     | February |            75 |
| Aluminum  | February |           115 |
| Wood      | March    |            20 |
| Wood      | March    |            25 |
| Aluminum  | March    |           150 |


Table: Table (29)
| VM Name   |
|:----------|
| VM 1      |
| VM 2      |
| VM 3      |
| VM 4      |


Table: Table (29a)
| Software Names   |
|:-----------------|
| Software 1       |
| Software 2       |
| Software 3       |
| Software 4       |


Table: Table (29b)
| VM Name.1   | Software Installed   | Ower   | Email     | Subscription ID   |
|:------------|:---------------------|:-------|:----------|:------------------|
| VM 1        | Software 2           | a      | a@xyz.com | x                 |
| VM 2        | Software 1           | b      | b@xyz.com | y                 |
| VM 3        | Software 1           | c      | c@xyz.com | z                 |
| VM 3        | Software 2           | c      | c@xyz.com | z                 |
| VM 3        | Software 3           | c      | c@xyz.com | z                 |


Table: Table (29c)
| VM Name   | Software Names   | Owner   | Email     | Subscription ID   | Status    |
|:----------|:-----------------|:--------|:----------|:------------------|:----------|
| VM 1      | Software 1       | a       | a@xyz.com | x                 | Missing   |
| VM 2      | Software 1       | b       | b@xyz.com | y                 | Installed |
| VM 3      | Software 1       | c       | c@xyz.com | z                 | Installed |
| VM 4      | Software 1       | NA      | NA        | NA                | Missing   |
| VM 1      | Software 2       | a       | a@xyz.com | x                 | Installed |
| VM 2      | Software 2       | b       | b@xyz.com | y                 | Missing   |
| VM 3      | Software 2       | c       | c@xyz.com | z                 | Installed |
| VM 4      | Software 2       | NA      | NA        | NA                | Missing   |
| VM 1      | Software 3       | a       | a@xyz.com | x                 | Missing   |
| VM 2      | Software 3       | b       | b@xyz.com | y                 | Missing   |


Table: Table (3)
| Person   | Activite   | Start                   | End                     | Location   |   Consequective |   Group |
|:---------|:-----------|:------------------------|:------------------------|:-----------|----------------:|--------:|
| Person 1 | Surgery    | 2019-06-05 17:29:00.000 | 2019-06-05 18:02:00.000 | Surgery 1  |               1 |       1 |
| Person 1 | Ward       | 2019-06-05 18:03:00.000 | 2019-06-06 22:44:00.000 | Ward 135   |               1 |       1 |
| Person 1 | Ward       | 2019-06-06 22:45:00.000 | 2019-06-14 10:00:00.000 | Ward 354   |               1 |       1 |
| Person 1 | Ward       | 2020-03-26 10:54:00.000 | 2020-03-26 16:48:00.000 | Ward 237   |               0 |       2 |
| Person 1 | Ward       | 2020-03-26 16:49:00.000 | 2020-03-27 15:45:00.000 | Ward 236   |               1 |       2 |
| Person 1 | Ward       | 2020-03-27 15:46:00.000 | 2020-04-03 12:29:00.000 | Ward 303   |               1 |       2 |
| Person 2 | Ward       | 2019-06-24 14:57:00.000 | 2019-06-27 20:50:00.000 | Ward 137   |               1 |       1 |
| Person 2 | Ward       | 2019-06-27 20:51:00.000 | 2019-06-28 20:32:00.000 | Ward 137   |               1 |       1 |
| Person 2 | Ward       | 2019-06-28 20:33:00.000 | 2019-07-06 09:05:00.000 | Ward 67    |               1 |       1 |
| Person 2 | Ward       | 2019-07-06 09:06:00.000 | 2019-07-09 14:19:00.000 | Ward 136   |               1 |       1 |


Table: Table (30)
| Date (A)                | Day of week (B)   |   Sales (C) |   5 day moving average |   Column |   5 Day Average |
|:------------------------|:------------------|------------:|-----------------------:|---------:|----------------:|
| 2020-08-31 00:00:00.000 | Mon               |        1501 |                   1448 |       12 |          1448.2 |
| 2020-08-28 00:00:00.000 | Fri               |        2350 |                   2906 |       11 |          2906.2 |
| 2020-08-27 00:00:00.000 | Thu               |        2587 |                   2869 |       10 |          2869   |
| 2020-08-26 00:00:00.000 | Wed               |         589 |                   2549 |        9 |          2548.8 |
| 2020-08-25 00:00:00.000 | Tue               |         214 |                   3982 |        8 |          3981.8 |
| 2020-08-24 00:00:00.000 | Mon               |        8791 |                  12933 |        7 |         12932.6 |
| 2020-08-21 00:00:00.000 | Fri               |        2164 |                  12144 |        6 |         12143.6 |
| 2020-08-20 00:00:00.000 | Thu               |         986 |                  14442 |        5 |         14442.2 |
| 2020-08-19 00:00:00.000 | Wed               |        7754 |                  15288 |        4 |         17806.2 |
| 2020-08-18 00:00:00.000 | Tue               |       44968 |                  14931 |        3 |         21157   |


Table: Table (31)
|   RECORD_ID | TAG   |
|------------:|:------|
|           1 | TAG1  |
|           1 | TAG2  |
|           2 | TAG1  |
|           2 | TAG3  |


Table: Table (31a)
| TAG   |
|:------|
| TAG1  |
| TAG2  |
| TAG3  |


Table: Table (32)
|   Total Spend |   Quantity |   Price |
|--------------:|-----------:|--------:|
|            25 |          5 |       5 |
|            20 |          2 |      10 |
|            40 |         10 |       4 |


Table: Table (32a)
|   Total Spend |   Quantity |   Price |   Value |
|--------------:|-----------:|--------:|--------:|
|            25 |          5 |       5 |       1 |
|            25 |          5 |       5 |       2 |
|            25 |          5 |       5 |       3 |
|            25 |          5 |       5 |       4 |
|            25 |          5 |       5 |       5 |
|            20 |          2 |      10 |       1 |
|            20 |          2 |      10 |       2 |
|            40 |         10 |       4 |       1 |
|            40 |         10 |       4 |       2 |
|            40 |         10 |       4 |       3 |


Table: Table (33)
| Company Name   |   User Amount |   Pricing |   Column |
|:---------------|--------------:|----------:|---------:|
| Test Company   |           100 |       198 |      404 |


Table: Table (34)
| Column1   |   Column2 |   Index |
|:----------|----------:|--------:|
| July      |         0 |       0 |
| August    |         0 |       1 |
| September |         0 |       2 |
| November  |         0 |       3 |
| December  |         0 |       4 |
| January   |         0 |       5 |
| February  |         0 |       6 |
| March     |        30 |       7 |
| April     |        60 |       8 |
| May       |        80 |       9 |


Table: Table (35)
|   Column |
|---------:|
|        1 |
|        2 |
|        3 |
|        4 |
|        5 |
|        3 |
|        3 |


Table: Table (35a)
|   Column |   Column1 |
|---------:|----------:|
|        2 |       100 |
|        3 |        85 |
|        5 |        55 |
|        9 |        75 |


Table: Table (36)
| Gen. Date               |   Loc. No. |   GF |   FM |   S |    U |   S+U=24 |   Column |
|:------------------------|-----------:|-----:|-----:|----:|-----:|---------:|---------:|
| 2020-04-01 00:00:00.000 |        123 |  0   |  5.8 |   0 |  0.5 |        0 |        0 |
| 2020-04-02 00:00:00.000 |        123 |  0   | 12.8 |   0 |  1   |        0 |        0 |
| 2020-04-29 00:00:00.000 |        123 |  3.7 |  0   |  12 | 12   |        1 |        1 |
| 2020-04-30 00:00:00.000 |        123 |  4.7 |  0   |  12 | 12   |        1 |        1 |
| 2020-05-01 00:00:00.000 |        123 |  0   |  0   |  12 | 12   |        1 |        1 |
| 2020-05-02 00:00:00.000 |        123 |  0   |  0   |   0 |  0   |        0 |        0 |
| 2020-05-07 00:00:00.000 |        123 |  0   |  0   |   0 |  0   |        0 |        0 |
| 2020-05-08 00:00:00.000 |        123 |  0   |  0   |  11 | 13   |        1 |        1 |
| 2020-05-30 00:00:00.000 |        123 |  0   |  0   |   0 |  0   |        0 |        0 |
| 2020-05-31 00:00:00.000 |        123 |  0.8 |  0   |   0 |  0   |        0 |        0 |


Table: Table (37)
| u_asset_type_display_value   | Complete?   |   Datekey |   Month # |
|:-----------------------------|:------------|----------:|----------:|
| Preventative Maintenance     | True        |  20200121 |         1 |
| Preventative Maintenance     | False       |  20200120 |         1 |
| Preventative Maintenance     | False       |  20200117 |         1 |
| Preventative Maintenance     | False       |  20200116 |         1 |


Table: Table (38)
| Person   | Location   | Date                    |
|:---------|:-----------|:------------------------|
| A        | a          | 2020-01-01 00:00:00.000 |
| A        | b          | 2020-02-01 00:00:00.000 |
| A        | c          | 2020-02-02 00:00:00.000 |
| A        | d          | 2020-03-02 00:00:00.000 |
| D        | a          | 2020-01-01 00:00:00.000 |
| B        | a          | 2020-02-01 00:00:00.000 |
| B        | b          | 2020-02-02 00:00:00.000 |
| C        | c          | 2020-03-02 00:00:00.000 |
| C        | d          | 2020-04-02 00:00:00.000 |


Table: Table (38a)
| person   |   number of locations |
|:---------|----------------------:|
| A        |                     4 |
| B        |                     2 |
| C        |                     2 |
| D        |                     1 |


Table: Table (39)
| TYPE   |   Value |
|:-------|--------:|
| A      |      10 |
| B      |      15 |
| C      |       5 |
| D      |      20 |
| E      |      15 |
| Y      |      20 |
| Z      |      30 |


Table: Table (39a)
| TYPE   |
|:-------|
| A      |
| E      |
| Z      |


Table: Table (4)
|   INVOICE AMOUNT |   Column 2 |   Column 3 |   Column 4 |   Column 5 |
|-----------------:|-----------:|-----------:|-----------:|-----------:|
|            18500 |    5388.89 |    5388.89 |       6000 |    5388.89 |
|            18500 |    5388.89 |    5388.89 |       6000 |    5388.89 |
|            18500 |    5388.89 |    5388.89 |       6000 |    5388.89 |
|            18500 |    5388.89 |    5388.89 |       6000 |    5388.89 |
|            19000 |    5388.89 |    5388.89 |       6500 |    5388.89 |
|             5000 |    5388.89 |    5388.89 |      -7500 |    5388.89 |
|            19000 |    5388.89 |    5388.89 |       6500 |    5388.89 |
|            19000 |    5388.89 |    5388.89 |       6500 |    5388.89 |
|            25000 |    5388.89 |    5388.89 |      12500 |    5388.89 |


Table: Table (40)
|   Column 1 | Category   |   Value | Column 2   |   Column |
|-----------:|:-----------|--------:|:-----------|---------:|
|          1 | A          |       3 | True       |        1 |
|          2 | A          |       2 | True       |        1 |
|          3 | A          |       0 | False      |        0 |
|          4 | A          |       0 | False      |        0 |
|          5 | B          |       3 | True       |        1 |
|          6 | B          |       2 | False      |        0 |
|          7 | B          |       0 | True       |        1 |
|          8 | C          |       1 | True       |        1 |


Table: Table (5)
| Type   | Material1   | Description1   | Materia2   | Description2   | Material3   | Description3   |
|:-------|:------------|:---------------|:-----------|:---------------|:------------|:---------------|
| A      | X           | plastic        | 1          | cover          | a           | type1          |
| A      | X           | plastic        | 2          | top            | b           | type2          |
| B      | Y           | metal          | 3          | middle         |             |                |
| B      | Z           | rubber         |            |                |             |                |


Table: Table (6)
| Type   | Material   | Description   |
|:-------|:-----------|:--------------|
| A      | X          | plastic       |
| A      | X          | plastic       |
| B      | Y          | metal         |
| B      | Z          | rubber        |


Table: Table (7)
| Type   | Material   | Description   |
|:-------|:-----------|:--------------|
| A      | 1          | cover         |
| A      | 2          | top           |
| B      | 3          | middle        |
| B      |            |               |


Table: Table (8)
| Type   | Material   | Description   |
|:-------|:-----------|:--------------|
| A      | a          | type1         |
| A      | b          | type2         |
| B      |            |               |
| B      |            |               |


Table: Table (9)
| Member ID   |   Age - Category | District - Category   |
|:------------|-----------------:|:----------------------|
| A           |               23 | z                     |
| b           |               23 | z                     |
| c           |               23 | x                     |
| d           |               29 | s                     |
| e           |               29 | s                     |
| f           |               29 | z                     |
| g           |               36 | z                     |
| h           |               36 | x                     |
| i           |               36 | x                     |
| j           |               36 | z                     |


Table: Table 2
|   Value |   Column |
|--------:|---------:|
|       1 |  3.20762 |
|       2 |  3.39991 |
|       3 |  3.59944 |
|       4 |  3.80616 |
|       5 |  4.01997 |
|       6 |  4.24074 |
|       7 |  4.46833 |
|       8 |  4.70255 |
|       9 |  4.94317 |
|      10 |  5.18992 |


Table: Table 3
| key      | date                    |   value2 |
|:---------|:------------------------|---------:|
| asfasf44 | 2020-07-31 00:00:00.000 |       56 |
| asfasf45 | 2020-07-31 00:00:00.000 |       45 |
| asfasf44 | 2020-08-15 00:00:00.000 |       44 |
| asfasf45 | 2020-08-15 00:00:00.000 |       33 |


Table: Table 4
| key      |   value1 |
|:---------|---------:|
| asfasf44 |       34 |
| asfasf45 |      463 |
| asfasf46 |       23 |
| asfasf47 |      534 |
| asfasf48 |        6 |
| asfasf49 |      657 |


Table: Table 5
| Selection                          | First Name   | Last Name   | Department   | Salary   |
|:-----------------------------------|:-------------|:------------|:-------------|:---------|
| A                                  | Josephine    | Darakjy     | Payroll      | 42000    |
| B                                  | Lenna        | Paprocki    | Research     | 58000    |
| C                                  | Simona       | Morasca     | Real Estate  | 75000    |
| D                                  | Leota        | Dilliard    | Marketing    | 60000    |
|                                    |              |             | Minimum      | 42000    |
|                                    |              |             | Maximum      | 75000    |
|                                    |              |             | Average      | 58750    |
| Office                             | ABC          | Corp        |              |          |
| Source:  and Internal and External |              |             |              |          |


Table: Table
| Date                    |   Value |
|:------------------------|--------:|
| 2019-01-01 00:00:00.000 |     261 |
| 2019-01-02 00:00:00.000 |      53 |
| 2019-01-03 00:00:00.000 |     158 |
| 2019-01-04 00:00:00.000 |     281 |
| 2019-01-05 00:00:00.000 |     240 |
| 2019-01-06 00:00:00.000 |     170 |
| 2019-01-07 00:00:00.000 |     115 |
| 2019-01-08 00:00:00.000 |     235 |
| 2019-01-09 00:00:00.000 |      94 |
| 2019-01-10 00:00:00.000 |      70 |


Table: wagons
| Consignment   | Docket     | Date Loaded             | Depot   | Wagon     |   Product |   Gross |   Tare |   Net |   Overcarry |
|:--------------|:-----------|:------------------------|:--------|:----------|----------:|--------:|-------:|------:|------------:|
| RA17221       | RA00318461 | 2016-12-04 05:04:00.000 | 010Y    | THFY015-N |     13068 |    66.8 |  20.65 | 46.15 |        1.65 |
| RA17221       | RA00318462 | 2016-12-04 05:03:00.000 | 010Y    | THFY012-J |     13068 |    66.9 |  20.5  | 46.4  |        1.35 |
| RA17221       | RA00318463 | 2016-12-04 05:09:00.000 | 010Y    | THFY002   |     13068 |    67   |  19.65 | 47.35 |        0    |

 


tables: name: Aggregation Table
data: Aggregation Table.csv
name: Append1
data: Append1.csv
name: Calendar
data: Calendar.csv
name: csvs (2)
data: csvs (2).csv
name: csvs
data: csvs.csv
name: Production data
data: Production data.csv
name: Query1
data: Query1.csv
name: Sheet1
data: Sheet1.csv
name: Table (10)
data: Table (10).csv
name: Table (11)
data: Table (11).csv
name: Table (12)
data: Table (12).csv
name: Table (13)
data: Table (13).csv
name: Table (14)
data: Table (14).csv
name: Table (15)
data: Table (15).csv
name: Table (16)
data: Table (16).csv
name: Table (17)
data: Table (17).csv
name: Table (18)
data: Table (18).csv
name: Table (19)
data: Table (19).csv
name: Table (2)
data: Table (2).csv
name: Table (20)
data: Table (20).csv
name: Table (21)
data: Table (21).csv
name: Table (22)
data: Table (22).csv
name: Table (22)B
data: Table (22)B.csv
name: Table (23)
data: Table (23).csv
name: Table (23a)
data: Table (23a).csv
name: Table (23b)
data: Table (23b).csv
name: Table (24)
data: Table (24).csv
name: Table (24a)
data: Table (24a).csv
name: Table (24b)
data: Table (24b).csv
name: Table (24c)
data: Table (24c).csv
name: Table (25)
data: Table (25).csv
name: Table (26)
data: Table (26).csv
name: Table (27)
data: Table (27).csv
name: Table (28)
data: Table (28).csv
name: Table (29)
data: Table (29).csv
name: Table (29a)
data: Table (29a).csv
name: Table (29b)
data: Table (29b).csv
name: Table (29c)
data: Table (29c).csv
name: Table (3)
data: Table (3).csv
name: Table (30)
data: Table (30).csv
name: Table (31)
data: Table (31).csv
name: Table (31a)
data: Table (31a).csv
name: Table (32)
data: Table (32).csv
name: Table (32a)
data: Table (32a).csv
name: Table (33)
data: Table (33).csv
name: Table (34)
data: Table (34).csv
name: Table (35)
data: Table (35).csv
name: Table (35a)
data: Table (35a).csv
name: Table (36)
data: Table (36).csv
name: Table (37)
data: Table (37).csv
name: Table (38)
data: Table (38).csv
name: Table (38a)
data: Table (38a).csv
name: Table (39)
data: Table (39).csv
name: Table (39a)
data: Table (39a).csv
name: Table (4)
data: Table (4).csv
name: Table (40)
data: Table (40).csv
name: Table (5)
data: Table (5).csv
name: Table (6)
data: Table (6).csv
name: Table (7)
data: Table (7).csv
name: Table (8)
data: Table (8).csv
name: Table (9)
data: Table (9).csv
name: Table 2
data: Table 2.csv
name: Table 3
data: Table 3.csv
name: Table 4
data: Table 4.csv
name: Table 5
data: Table 5.csv
name: Table
data: Table.csv
name: wagons
data: wagons.csv
label: Append1
Description
Table (7)
Description
Table (8)
Description
Table (7)
Description
Append1
Description
Table (5)
Description2
Table (8)
Description
Table (5)
Description2
Query1
Description
Table (7)
Description
Query1
Description
Table (5)
Description2
Table 3
key
Table 4
key
Table (18)
ID
Table (16)
ID
Table (22)
id
Table (16)
ID
Table (23b)
CustomerUID
Table (23a)
CustomerUID
Table (23)
CustomerUID
Table (23b)
CustomerUID
Table (24b)
Index
Table (34)
Index
Table (35)
Column
Table (35a)
Column
Table (38)
Person
Table (38a)
person
Table (5)
Type
Table (39)
TYPE
Table (6)
Type
Table (39)
TYPE
Table (39a)
TYPE
Table (39)
TYPE
csvs
column1
Table (40)
Column 1
Sheet1
Column1
Table (40)
Column 1
Table (35)
Column
Table (40)
Column 1
output: {
    "joins": [
        {
            "from_table": "Append1",
            "from_column": "Description",
            "to_table": "Table (7)",
            "to_column": "Description"
        },
        {
            "from_table": "Table (8)",
            "from_column": "Description",
            "to_table": "Table (7)",
            "to_column": "Description"
        },
        {
            "from_table": "Append1",
            "from_column": "Description",
            "to_table": "Table (5)",
            "to_column": "Description2"
        },
        {
            "from_table": "Table (8)",
            "from_column": "Description",
            "to_table": "Table (5)",
            "to_column": "Description2"
        },
        {
            "from_table": "Query1",
            "from_column": "Description",
            "to_table": "Table (7)",
            "to_column": "Description"
        },
        {
            "from_table": "Query1",
            "from_column": "Description",
            "to_table": "Table (5)",
            "to_column": "Description2"
        },
        {
            "from_table": "Table 3",
            "from_column": "key",
            "to_table": "Table 4",
            "to_column": "key"
        },
        {
            "from_table": "Table (18)",
            "from_column": "ID",
            "to_table": "Table (16)",
            "to_column": "ID"
        },
        {
            "from_table": "Table (22)",
            "from_column": "id",
            "to_table": "Table (16)",
            "to_column": "ID"
        },
        {
            "from_table": "Table (23b)",
            "from_column": "CustomerUID",
            "to_table": "Table (23a)",
            "to_column": "CustomerUID"
        },
        {
            "from_table": "Table (23)",
            "from_column": "CustomerUID",
            "to_table": "Table (23b)",
            "to_column": "CustomerUID"
        },
        {
            "from_table": "Table (24b)",
            "from_column": "Index",
            "to_table": "Table (34)",
            "to_column": "Index"
        },
        {
            "from_table": "Table (35)",
            "from_column": "Column",
            "to_table": "Table (35a)",
            "to_column": "Column"
        },
        {
            "from_table": "Table (38)",
            "from_column": "Person",
            "to_table": "Table (38a)",
            "to_column": "person"
        },
        {
            "from_table": "Table (5)",
            "from_column": "Type",
            "to_table": "Table (39)",
            "to_column": "TYPE"
        },
        {
            "from_table": "Table (6)",
            "from_column": "Type",
            "to_table": "Table (39)",
            "to_column": "TYPE"
        },
        {
            "from_table": "Table (39a)",
            "from_column": "TYPE",
            "to_table": "Table (39)",
            "to_column": "TYPE"
        },
        {
            "from_table": "csvs",
            "from_column": "column1",
            "to_table": "Table (40)",
            "to_column": "Column 1"
        },
        {
            "from_table": "Sheet1",
            "from_column": "Column1",
            "to_table": "Table (40)",
            "to_column": "Column 1"
        },
        {
            "from_table": "Table (35)",
            "from_column": "Column",
            "to_table": "Table (40)",
            "to_column": "Column 1"
        }
    ]
}