# Join Using a Source

In this document, you’ll learn how to use the *Join* function in Astera Dataprep to combine a dataset from a project source with an existing dataset in your Dataprep Recipe.

### Use Case

In this use case, we have a Dataprep Recipe where a company’s *Customers* dataset has been cleansed. Now, they want to join it with their *Orders* dataset, which is available in a shared project source.

<figure><img src="/files/MKrp4dkOALkQsthXUro4" alt=""><figcaption></figcaption></figure>

1. To begin, click on the *Join* option in the toolbar and select *Source* from the drop-down.

<figure><img src="/files/yNaiMLXOQoJLJIV8qKQk" alt=""><figcaption></figcaption></figure>

2. Alternatively, you can drag and drop the project source from the *Data Source Browser* panel onto the *Join* object in the Recipe canvas.

<figure><img src="/files/2cK1N6qfoMB7BfYaijhU" alt=""><figcaption></figcaption></figure>

3. This will open the *Recipe Configuration – Join* panel.

<figure><img src="/files/lZh1qM5ddcDLBfD37Osb" alt="" width="387"><figcaption></figcaption></figure>

4. In this panel, you’ll configure the following options:

* **Filter Source:** Choose the type of source you want to use. You can filter by type or simply select *All*.

<figure><img src="/files/oBi3nPD0PStRcGEHceA6" alt="" width="347"><figcaption></figcaption></figure>

* **Shared Source:** From the drop-down, select the project source dataset you want to join.

<figure><img src="/files/rRj7uBfoJJ4SMFndpZ2W" alt="" width="362"><figcaption></figcaption></figure>

* **Join Dataset:** You can provide a custom name for the joined dataset or keep the default name. In this example, we’ll keep the default name.

<figure><img src="/files/tkbQHiVvEr7RA9eMNbCu" alt="" width="350"><figcaption></figcaption></figure>

* **Join Type:** Choose the type of join you want to perform:

  * **Inner:** Keeps only the records that have matching values in both datasets.
  * **Left Outer:** Keeps all records from the current dataset and adds matching data from the project source. Unmatched records from the project source are filled with nulls.
  * **Right Outer:** Keeps all records from the project source and adds matching data from the current dataset. Unmatched records from the current dataset are filled with nulls.
  * **Full Outer:** Keeps all records from both datasets. Unmatched values are filled with nulls.

  In our example, we’ll use an *Inner join* to include only matching records.

<figure><img src="/files/T6h3AGetMnNUMZFu6JDq" alt="" width="376"><figcaption></figcaption></figure>

* **Keys:** Specify the key fields that the join will be based on. Astera will auto-detect matching fields, but you can modify them as needed.
  * **Left Field:** Field from the current dataset.
  * **Right Field:** Field from the project source dataset.

In this case, we’ll keep the default key fields selected.

<figure><img src="/files/ILU0ZmGk6eWL13Lbrgw6" alt="" width="369"><figcaption></figcaption></figure>

5. Once you’re done, click <img src="/files/MoI3HgBFnNJT7Jgo3HNm" alt="" data-size="line"> *Apply.* The project source dataset will now be joined, and the result will appear in the grid.

<figure><img src="/files/nKsoR5vxeppByqGERrRR" alt=""><figcaption></figcaption></figure>


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