---
title: "MySQL as a Source"
slug: "mysql"
description: "Get your data to MySQL easily with Dataddo. Follow steps to create a MySQL data source. Set up advanced optional settings & configure snapshotting preferences."
tags: ["Custom-schema connector", "How-to guide", "Data source"]
updated: 2024-04-01T14:44:29Z
published: 2024-04-01T14:44:29Z
---

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

# MySQL as a Source

**MySQL** is an open-source relational database management system. It is widely used for storing, managing, and retrieving structured data, making it a popular choice for web applications, content management systems, and various other software solutions.

## Authorize the Connection to MySQL

In order to connect MySQL as a ***data source***, you will need to first [authorize the connection to your MySQL](/docs/mysql-destination#authorize-the-connection-to-mysql).

## Create a MySQL Data Source

1. On the **Sources** page, click on the [**Create Source**](https://app.dataddo.com/sources/new) button and select the connector from the list.
2. From the drop-down menu, choose your **account**.
          **Didn't find your account?**

          

Click on **Add new Account** at the bottom of the drop-down and follow the on-screen prompts. You can also go to the **Authorizers** tab and click on [**Add New Service**](https://app.dataddo.com/service/new).
3. **Name** your data source, choose your **MySQL server** and fill in your [SQL statement](/docs/mysql#sql-statement-examples).
4. Configure your **snapshotting preferences**. Choose your [**sync frequency**](https://docs.dataddo.com/docs/extraction#extraction-frequency) or the exact synchronization time under **Show advanced settings**.
          **DATADDO TIP**

          

If you need to **load historical data**, please refer to the [**Data Backfilling**](https://docs.dataddo.com/docs/data-backfilling) article.
5. Preview your data by clicking on the **Test Data** button in the top right corner. You can **adjust the date range** for a more specific time frame.
6. Click on **Save** and **congratulations, your new data source is ready!**

          **WARNING**

          

Dataddo relies on your query statements to accurately retrieve the right data. By choosing specific statements, you guide Dataddo's actions on your data.

Every command in your query statement directly affects your database. **Special attention is required when using commands like`DELETE` or `UPDATE`**, which are more impactful than a simple `SELECT`.

### SQL Statement Examples

1. Extract **all data** from the `clients` table:

```
SELECT * FROM clients
```
2. Extract the **name, email, company** columns from the `clients` table:

```
SELECT name,email,company FROM clients
```
3. Extract **data from specific rows (rows 240,000 to 800,000)** from **all columns** from the `clients` table:

```
SELECT * FROM clients  
LIMIT 2400000,  
800000
```
4. Extract **all data from columns for a specific country** from the `clients` table:

```
SELECT * FROM clients WHERE countryCode = 'USA'
```
5. Extract **all data** from **all columns** if a **job title contains a specific position** from the `clients` table:

```
SELECT * FROM clients WHERE jobTitle = '%Manager%' OR company= 'Dataddo'
```

---

## Limitations

### Only Append is Possible

As neither delete or update operations are perfomed during data delivery, data is inserted in append-only mode.

In certain cases, the append-only solution might have drawbacks due to the growing size of the database. The best solution is to define an `AFTER INSERT` trigger that will delete historical data as **the retention period can be customized**. In the example below, the trigger deletes all the rows meeting the `insert_date < DATE_SUB(NOW(), INTERVAL 1 DAY)` conditions.

```
DELIMITER $$  
   
CREATE TRIGGER trigger_name  
    AFTER INSERT  
    ON table_name  
BEGIN  
    DELETE FROM table_name WHERE insert_date < DATE_SUB(NOW(), INTERVAL 1 DAY)  
END$$      
   
DELIMITER ;
```

## Troubleshooting

### Context Deadline Exceeded Error

**ERROR CODE**

```
rpc error: code = DeadlineExceeded desc = context deadline exceeded
```

This issue may be caused by extracting data over an **extended timeframe**. Use `WHERE` or `LIMIT` clauses in your SQL query to manage the size and scope of the data extraction.

1. Use `WHERE` to specify the date range.

```
SELECT * FROM your_table
WHERE date_column BETWEEN '202X-01-01' AND '202X-01-31';
```
2. Use `LIMIT` to specify the specify the maximum number of records to return.

```
SELECT * FROM your_table
LIMIT 1000;
```
3. Combine `WHERE` and `LIMIT` for more precise control. The query in this example will return the first 1000 records where the date is after January 1, 202X.

```
SELECT * FROM your_table
WHERE date_column > '202X-01-01'
LIMIT 1000;
```

## Related Articles

Now that you have successfully created a ***data source***, see how you can connect your data to a dashboarding app or a data storage.

**Sending Data to Dashboarding Apps**

- [Simple Data Integration to Dashboards](https://docs.dataddo.com/docs/simple-data-integration-to-dashboards)
- [Data Backfilling to Dashboarding Apps](https://docs.dataddo.com/docs/data-backfilling-to-dashboarding-apps)

**Sending Data to Data Storages**

- [Batch Ingestion to Data Warehouses](https://docs.dataddo.com/docs/ingestion-to-data-warehouses)
- [Data Backfilling to Storages](https://docs.dataddo.com/docs/data-backfilling-to-storages)

**Other Resources**

- [Troubleshooting](https://docs.dataddo.com/docs/troubleshooting)
- [Extraction Logs](https://docs.dataddo.com/docs/extraction-logs)
- [Data Duplication](https://docs.dataddo.com/docs/data-duplication)