> For the complete documentation index, see [llms.txt](https://upsolver.gitbook.io/content/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://upsolver.gitbook.io/content/quickstarts-1/jobs/transformation/data-targets/output-to-snowflake.md).

# Output to Snowflake

## Prerequisites

Ensure that you have a [Snowflake](/content/reference-1/sql-commands/connections/create-connection/snowflake.md) connection with the correct permissions to write to your target table. Additionally, this target table should already exist within Snowflake before writing to it using Upsolver. Furthermore, you will need a storage connection that has access to the bucket you would like the job to use to store the intermediate files used while running the job. Finally, you should also have a staging table created previously that contains your ingested data.

## Create a job writing to Snowflake

After you have fulfilled the prerequisites, you can create an `INSERT` job as follows:

```sql
CREATE SYNC JOB load_data_to_snowflake
   RUN_INTERVAL = 1 MINUTE
   START_FROM = BEGINNING
   COMMENT = 'insert data into snowflake target table'
AS INSERT INTO SNOWFLAKE your_snowflake_connection.your_schema.target_table 
   MAP_COLUMNS_BY_NAME
      SELECT customer_id,
             COUNT(DISTINCT order_id) AS num_orders,
             SUM(net_total) AS total_spent,
             MIN(order_date) AS first_purchase,
             MAX(order_date) AS last_purchase
      FROM default_glue_catalog.your_database.staging_table
      WHERE time_filter()
      GROUP BY customer_id;
```

This example only uses a subset of all job options available when writing to Snowflake. 

Depending on your use case, you may want to configure a different set of options. For instance, this example contains an aggregation, which means you may want to configure the `AGGREGATION_PARALLELISM` option.

## Alter a job writing to Snowflake

Certain job options are considered mutable, meaning that in some cases, you can run a SQL command to alter an existing transformation job rather than having to create a new one.

For example, take the job we created as an example earlier:

```sql
CREATE SYNC JOB load_data_to_snowflake
   RUN_INTERVAL = 1 MINUTE
   START_FROM = BEGINNING
   COMMENT = 'insert data into snowflake target table'
AS INSERT INTO SNOWFLAKE your_snowflake_connection.your_schema.target_table 
   MAP_COLUMNS_BY_NAME
      SELECT customer_id,
             COUNT(DISTINCT order_id) AS num_orders,
             SUM(net_total) AS total_spent,
             MIN(order_date) AS first_purchase,
             MAX(order_date) AS last_purchase
      FROM default_glue_catalog.your_database.staging_table
      WHERE time_filter()
      GROUP BY customer_id;
```

If you wanted to keep the job as is but just change the cluster that is running the job, you can run the following command:

```sql
ALTER JOB load_data_to_snowflake
    SET COMPUTE_CLUSTER = high_memory_cluster;
```

Note that some options such as `RUN_INTERVAL` cannot be altered once the connection has been created.

## Drop a job writing to Snowflake

If you no longer need a certain job, you can easily drop it with the following SQL command:

```sql
DROP JOB load_data_to_snowflake;
```

***

{% hint style="success" %}
**Learn More** 

For the full list of job options with syntax and detailed descriptions, see the transformation job options for [Snowflake](/content/reference-1/sql-commands/jobs/create-job/transformation/job-options/snowflake.md).

See the [INSERT](/content/reference-1/sql-commands/jobs/create-job/transformation/insert.md) SQL command reference for more details and examples.
{% endhint %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://upsolver.gitbook.io/content/quickstarts-1/jobs/transformation/data-targets/output-to-snowflake.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.