Primary Keys

When configuring a external Dataset into Whaly, whether it is a Table Import from your Warehouse or when saving a Model (SQL or No-code), you'll have to configure a the set of columns that compose the Primary Key.

Simply put, the Primary Key should be a way to uniquely identify a row in the table. So 2 rows in the table shouldn't have the same values in the columns that are composing the primary key.

Example 1:

| fruit_id | name     |
|----------|----------|
| 1        | Banana   |
| 2        | Apple    |
| 3        | Orange   |
| 4        | Eggplant |
| 5        | Avocado  |

In this table, every row has a different value in the fruit_id column. Hence, the fruit_id column can be used to uniquely identify all the rows of the table.

Primary Key = fruit_id ✅

Example 2:

| event_date | event_name      | channel    | source       | campaign_id | spend  | 
|------------|-----------------|------------|--------------|-------------|--------|
| 2022-01-01 | Marketing Spend | Search Ads | Google Ads   | 123         | 18.67  |
| 2022-01-01 | Marketing Spend | Search Ads | Google Ads   | 456         | 54.21  |
| 2022-01-02 | Marketing Spend | Search Ads | Google Ads   | 456         | 48.21  |
| 2022-01-01 | Marketing Spend | Social Ads | Facebook Ads | 102212210   | 54.21  |
| 2022-01-01 | Marketing Spend | Social Ads | Facebook Ads | 441215442   | 126.46 |
| 2022-01-02 | Marketing Spend | Social Ads | Facebook Ads | 102212210   | 214.21 |

On this example, many columns contains the same value for different rows. Ex. event_date column contains multiple times the value "2022-01-01" for different rows.

Same thing for:

• event_name

• channel

• source

• campaign_id

Hence, those columns can't be used individually as the Primary Key.

However, taken all together, event_date + event_name + channel + source + campaign_id columns are producing a combinaison of values that are unique for each row in the table. If we only keep those columns in the above tables, we have:

| event_date | event_name      | channel    | source       | campaign_id |
|------------|-----------------|------------|--------------|-------------|
| 2022-01-01 | Marketing Spend | Search Ads | Google Ads   | 123         |
| 2022-01-01 | Marketing Spend | Search Ads | Google Ads   | 456         |
| 2022-01-02 | Marketing Spend | Search Ads | Google Ads   | 456         |
| 2022-01-01 | Marketing Spend | Social Ads | Facebook Ads | 102212210   |
| 2022-01-01 | Marketing Spend | Social Ads | Facebook Ads | 441215442   |
| 2022-01-02 | Marketing Spend | Social Ads | Facebook Ads | 102212210   |

Each row has a unique combinaison of those columns, together they are forming the Primary Key 👍

Primary Key = event_date + event_name + channel + source + campaign_id ✅

Why is the Primary Key important?

In order for a join to work in an Exploration when having Related Tables, it is necessary to define a Primary Key as specified below. It is a requirement when a join is defined so that Whaly can handle row multiplication issues.

Let's imagine you want to calculateOrder Amount by Order Item Product Name.

In this case, Order rows will be multiplied by the Order Item join due to the hasMany relationship between Order and Order Item as it will be a LEFT JOIN.

It is known as the JOIN Fan Out issue.

In order to produce correct results, Whaly will select distinct Primary Keys from Order first and then will join these primary keys with Order to get the correct Order Amount sum result.