# Error Handling

{% hint style="warning" %}

#### Workshop - Error Handling

Bad data happens. Don’t fail the whole transformation because of a few rows. Route error rows to a separate stream for review and cleanup.

**What you’ll do**

* Read a CSV with a date field
* Trigger a controlled date parsing error
* Configure an error hop to capture failing rows
* Review the error metadata fields (description, field name, error code)
* Fix the date format and verify success

**Prerequisites:** Complete the **Hello World** and **Logging** workshops

**Estimated time:** 10 minutes
{% endhint %}

***

<figure><img src="/files/eqdOBPvxSiAQqWlgomiO" alt=""><figcaption><p>Error handling</p></figcaption></figure>

{% hint style="info" %}
**Workshop files**

Download the following files.

Keep the filenames unchanged.

Save them in your workshop folder.
{% endhint %}

{% file src="/files/qbHHtBgSQAPhXGGQnDtE" %}

{% hint style="info" %}
**Create a new transformation**

Use any of these options to open a new transformation tab:

* Select **File** > **New** > **Transformation**
* Use `Ctrl+N` (Windows/Linux) or `Cmd+N` (macOS)
  {% endhint %}

{% tabs %}
{% tab title="1. CSV file input" %}
{% hint style="info" %}

#### **CSV file input**

The CSV File Input step reads data from delimited text files into a PDI transformation. While this step is called CSV File Input, you can also use CSV File Input with many other separator types, such as pipes, tabs, and semicolons.

**Note:** The semicolon (;) is set as the default separator type for this step.
{% endhint %}

1. Double-click to edit the CSV file input step.

<figure><img src="/files/YiJRcLaPaZIbXKQO01YV" alt=""><figcaption><p>CSV file input</p></figcaption></figure>

2. Set the following metadata properties for: birthdate

| Fieldname | Type | Format     |
| --------- | ---- | ---------- |
| birthdate | date | yyyy/MM/dd |

{% hint style="warning" %}
If your CSV uses a different date pattern, keep `yyyy/MM/dd` for now. This mismatch is what triggers the error rows in the next step.
{% endhint %}
{% endtab %}

{% tab title="2. Error hop" %}
{% hint style="info" %}

#### Error hop

An error hop routes rows that fail in a step to a separate target step. This lets you keep processing valid rows. You also get extra error fields in the error stream.
{% endhint %}

1. Double-click the white diagonal cross on the red error hop.

<figure><img src="/files/4J94cekxgltyfD170Gym" alt=""><figcaption><p>Hop - Error handling</p></figcaption></figure>

2. Set the error field names (you can pick your own).

* **Nr of errors fieldname**: Number of errors for the row.
* **Error descriptions fieldname**: Human-readable error message.
* **Error field fieldname**: The field that caused the error.
* **Error codes fieldname**: A code you can filter or group by.
  {% endtab %}

{% tab title="3. Run" %}
{% hint style="info" %}

#### Run the transformation

Preview both streams. One contains valid rows. One contains error rows plus error metadata.
{% endhint %}

1. Select **Run** in the canvas toolbar.
2. Preview the **Dummy** step:

<figure><img src="/files/HgMqUQhlZ62FeL5KBMCH" alt=""><figcaption><p>Correct birthdate format</p></figcaption></figure>

3. Preview the **Dummy - Errors** step:

<figure><img src="/files/21KRmIJRrGKS7K5Ds1EH" alt=""><figcaption><p>Errors for incorrectly formatted birthdates</p></figcaption></figure>

4. Scroll to the end of the **Execution results** pane.

{% hint style="info" %}
Use `errorCodes` to route errors into targeted cleanup logic.
{% endhint %}

***

**Fix the format and verify**

1. Open **CSV file input** again.
2. Update the **Format** value for `birthdate` to match your CSV.

{% hint style="info" %}
Example: if your data looks like `2026-02-17`, use `yyyy-MM-dd`.
{% endhint %}

3. Run the transformation again.
4. Preview **Dummy - Errors**. You should see fewer rows, or none.
   {% endtab %}
   {% endtabs %}

***


---

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