# Join datasets

The Join step allows you to combine two datasets listed in the dataHub to bring columns from the former into the latter, matching rows based `on` columns correspondance

### Step parameters

* `Select a dataset to join (as a right dataset)` **column(string)\***: Select a dataset to join as the right dataset.
* `Select a join Type` **dropdown(string)\***`:` Choose from "left", "inner", or "left outer" join.
  * `left`: will keep every row of the current dataset and fill unmatched rows with `null` values,
  * `left outer` :
  * `inner`: will only keep rows that match rows of the joined dataset.
* `Join based on columns:`specify 1 or more column couple(s) that will be compared to determine rows correspondance between the 2 datasets. The first element of a couple is for the current dataset column, and the second for the corresponding column in the right dataset to be joined. If you specify more than 1 couple, the matching rows will be those that find a correspondance between the 2 datasets for every column couple specified (logical ‘AND’).

### Example

**Input**

<figure><img src="/files/PQlhpFtl0N1ebFfvLs3i" alt=""><figcaption><p>Combine - join - dataset_to_join</p></figcaption></figure>

<figure><img src="/files/86zWnalCqKAagafZXUa2" alt=""><figcaption><p>Combine - join - dataset_to_join</p></figcaption></figure>

**Configuration**

```json
{
    "right_pipeline": "dataset_to_join",
    "type": "left",
    "on": [
        {
            "id": "emp_id"
        }
    ]
}
```

**Output**

<figure><img src="/files/0hf9RjmdrHH8B2qL6sib" alt=""><figcaption><p>Combine - join output</p></figcaption></figure>


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