> ## Documentation Index
> Fetch the complete documentation index at: https://docs.nrev.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Merge Data

> Combine exactly two datasets — stack rows or join columns with full control and zero drama.

## What It Does

* Merges **two datasets** either by stacking rows (append) or joining columns (join)
* Join on **row position**, **matching fields**, or **all combinations**
* Supports join types: **inner**, **left**, **right**, **outer**, and **cross**
* Automatically resolves field conflicts and validates input compatibility
* Outputs are available in both CSV and Parquet formats

***

## 🏁 Getting Started

<Frame>
  <img src="https://mintcdn.com/nurturev/mHCimB8YAP--VMGj/images/Merge%20Data%20node%20configuration%20screenshot.png?fit=max&auto=format&n=mHCimB8YAP--VMGj&q=85&s=27befdf9e55e3d72d76d3ed77226fa6c" alt="Merge Data node configuration screenshot" style={{ borderRadius: '0.5rem', width: '100%', margin: '1.5rem 0' }} width="1180" height="1664" data-path="images/Merge Data node configuration screenshot.png" />
</Frame>

<Steps>
  <Step title="Add the Node">
    Drag the **Merge Data** node into your canvas.
  </Step>

  <Step title="Connect Inputs">
    Connect exactly **two datasets**: one to **First Input**, the other to **Second Input**.
  </Step>

  <Step title="Choose Merge Type">
    Pick between:

    * **Append**: stack rows
    * **Join**: merge columns based on row order or fields
  </Step>

  <Step title="Configure Join (if selected)">
    Select how to join:

    * **Row Position**: merge by row order
    * **Matching Fields**: match shared column values
    * **All Combinations**: cross join all rows
  </Step>

  <Step title="Run the Node">
    Output will contain the full merged dataset, ready for download or downstream use.
  </Step>
</Steps>

***

## Inputs

### 🛠️ Required Fields

* **First Input (✅)**\
  The primary dataset — acts as the left table in joins.

* **Second Input (✅)**\
  The secondary dataset — used as the right table in joins.

* **Merge Type (✅)**\
  Choose `Append` or `Join`. If `Join`, you must also specify how to merge.

***

## Output

You get a single merged dataset with:

* All merged rows and columns, depending on type and logic
* File download links:
  * `s3_output_url`: Parquet format
  * `s3_output_url_csv`: CSV format
* A `merge_info` summary describing how many rows were merged and how

***

## Merge Types & Options

### 🔁 Append (Row Stack)

* Adds all rows from the second dataset below the first
* Columns from both inputs are preserved
* Missing columns will be filled with `null`

### 🔗 Join (Row Merge)

* Combines rows across datasets side-by-side
* Choose how to join:
  * **Row Position**: Merge row 1 with row 1, row 2 with row 2, etc.
  * **Matching Fields**: Match rows using one or more shared columns
  * **All Combinations**: Every row from dataset A is joined with every row from dataset B

#### Join Types (for Matching Fields only)

| Join Type  | Description                                                |
| ---------- | ---------------------------------------------------------- |
| Inner Join | Keep only rows where both sides match on all fields        |
| Left Join  | Keep all rows from first dataset + matches from second     |
| Right Join | Keep all rows from second dataset + matches from first     |
| Outer Join | Keep all rows from both datasets (full outer)              |
| Cross Join | All combinations (used with “All Combinations” merge mode) |

***

## 🚀 Example Use Cases

| Scenario                           | Setup Example                                                               |
| ---------------------------------- | --------------------------------------------------------------------------- |
| Stack monthly exports              | Merge Type: `Append`                                                        |
| Enrich Nrev AI accounts            | Merge Type: `Join`, On: `Matching Fields`, Join Type: `Left`, Key: `domain` |
| Align scraped leads with CRM       | Merge Type: `Join`, On: `Row Position`                                      |
| Pair Sayanta’s leads with rep list | Merge Type: `Join`, On: `All Combinations`                                  |

***

## ✨ Pro Tips

<Tip>
  Label your inputs clearly as **First Input** and **Second Input**. It keeps things clean when reviewing joins later.
</Tip>

<Tip>
  If joining on fields like `email` or `domain`, make sure those exist in **both** datasets — and have the same name.
</Tip>

<Tip>
  Appending is great when schemas align. If not? Use Join and take the wheel.
</Tip>

***

## ⚠️ Important Considerations

<Warning>
  If both datasets have a column named `email`, they’ll be renamed (e.g. `email_1`, `email_2`) to avoid confusion.
</Warning>

<Warning>
  Cross joins can balloon fast. Use with caution unless you really want every combo.
</Warning>

<Warning>
  Joining on `Matching Fields`? Make sure the columns have the same name **and** compatible data types.
</Warning>

***

## 🛠 Troubleshooting & Gotchas

| Symptom                              | Likely Cause                | Quick Fix                               |
| ------------------------------------ | --------------------------- | --------------------------------------- |
| Output is empty                      | No matching rows in join    | Adjust join fields or change join type  |
| Unexpected nulls in output           | Fields missing in one input | Reconcile columns or switch to Join     |
| Merge fails                          | Only one input connected    | Ensure both First and Second are linked |
| Duplicate fields with \_1/\_2 suffix | Field name conflict         | Rename upstream columns if needed       |

***

## 📝 FAQ

<AccordionGroup>
  <Accordion title="Can I append datasets with different columns?">
    Yep — all fields are preserved. Missing values get filled with `null`.
  </Accordion>

  <Accordion title="Do column names need to match for join?">
    Only if you’re using `Matching Fields`. For other join types, names can differ.
  </Accordion>

  <Accordion title="How are output columns ordered?">
    Fields from the First Input come first, then fields from the Second.
  </Accordion>
</AccordionGroup>

***

## 💰 Pricing

> The Merge Data node is **free** — no credits required.

***

<p style={{ fontSize: '1rem', fontWeight: 'bold', marginTop: '1.5rem' }}>
  Whether you're stacking exports or enriching accounts, Merge Data makes it seamless. Join, append, and move on. 🔗
</p>