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

# Join

> Join multiple topics. Supports schema evolution and pass-through fields.

## Setup

* Navigate to [Create Transform](https://app.streamkap.com/transforms/create).
* Choose **Join**.

### 1. Settings

* **Name:** Enter a name for the transform e.g. filter out empty records
* **Language:** Select the preferred (if supported) language to define the transform.
* **Input Pattern:** Enter a regular expression pattern to list the topics this transform is applied to e.g. `source_abcd1234.public.orders`,`source_abcd1234\.public\.order.*`.
* **Output Pattern:** Enter the desired output topic name including schema e.g. `enriched.orders`.
* **Transform Parallelism:** The degree of parallelism for this transform. Determines number of tasks this transform should use when executing the transform logic. The default should be more than sufficient in most cases.

### 2. Advanced Parameters

* **Input Serialization:** The format (e.g. `JSON`, `AVRO`, `STRING`, `BYTES`) of the input data. The default (`Any`) will try determine the format automatically.
* **Output Serialization:** The format (e.g. `JSON`, `AVRO`, `STRING`, `BYTES`) of the output data. The default (`Any`) will try determine the format automatically.

Click **Save**.

## Implementation

Now you need to define the logic for your transform and deploy it.

* Go to the **Implementation** tab.

### 1. Objective / Goal

* Describe in a short sentence the purpose of the transform and its expected output.

### 2. Input / Output Topics

These take the **Input Pattern** and **Output Pattern** entered earlier. You can also amend the input tables, and see a preview of the input topics captured by the input pattern as well as the corresponding output topic.

<Info>
  ### No topics in preview

  If no topics are shown, review and amend your input topic patterns. The [topics page](https://app.streamkap.com/topics) shows the full names of topics, usually in three parts. Starting your pattern with `.*` ignores the first part (usually the Connector's ID), so you can focus your pattern on matching the schema (middle) and table (last) parts.
</Info>

* **Output Topic Replacement:** Amend the desired output topic name using a regular expression pattern.

#### 2.1 Input Tables

Here the input topic pattern is translated into individual table expressions for easier control over which topics are or are not included in the join.

* **Add** or **Remove** topics as needed.

Click **Save Topics Pattern / Replacement**.

### 3. Transform Logic

Here is where you define the logic for the transform.

#### SQL Join

Depending on the number of input tables, a number of editable SQL scripts are generated. There are 2 types of SQL script involved: the first type defines-per input table-the fields needed to join them together, and the other is the `JOIN` query itself.

* Click on each `.sql` script to edit it.

Once you're happy with them, continue to the next section.

### 4. Deploy & Check

Here you deploy your transform, but you can also perform diagnostic and validation checks at a click of a button.

#### 4.0 Clear Output Topic

This purges the output topic of data (if any) as well as any cached job state. A "reset" of the transform's previous outputs so you can start fresh.

* **Output Topic pattern to clear:** Enter a regular expression pattern that captures the output topics to be cleared.

Click **Clear Output Topics and Job State**.

#### 4.1 Deploy

When deploying a transform, you can decide from what point the transform starts processing the input topics data-assuming the data's still available.

* **Replay Window:**

  * **Time-based**: Enter the **last** number of days, hours or minutes to process.
  * **Recency-based**: Enter `0` to process from the **latest** data, or, leave it blank/empty to process from the **earliest** data.

Click **Deploy Transform**.

#### 4.2 Job Status

Check on the current status of the transform job.

Click **Check Job Status**.

#### 4.3 Output Topics

Check what output topics were created (if any) and populated by the transform.

Click **Check Output Topics**.

#### 4.4 Errors

Check if the transform jobs are failing and if so, what the problem is.

Click **Check for Errors**.

## See Also

* [Transform Ordering](/transform-ordering) - Understand how transforms are ordered and executed within a pipeline
* [Transform Examples](/transform-examples) - Practical examples and recipes for common transform use cases