Here are some best practices for using Snowpipe:
- Use file sizes above 10 MB and preferably in the range of 100 MB to 250 MB. This will help to optimize performance and reduce costs.
- Consider using auto-ingest Snowpipe for continuous loading. This will automatically load new files into Snowflake as they are created, which can be helpful for data that needs to be available as soon as possible.
- Use a staging area in cloud storage. This will allow you to store your data files before they are loaded into Snowflake, which can help to improve performance and scalability.
- Use a consistent schema for your data files. This will make it easier to load the data into Snowflake and to query it later.
- Use error handling to prevent data loss. Snowpipe supports a variety of error handling options, such as retrying failed loads and skipping bad rows.
- Monitor your Snowpipe pipelines. This will help you to identify and troubleshoot any problems.
Here are some additional tips:
- If you are loading a large amount of data, you may want to consider using Snowpipe Streaming. This can help to improve performance by loading data in real time.
- If you are loading data from a variety of sources, you may want to consider using a Snowpipe connector. This will make it easier to load the data into Snowflake.
- If you are using Snowpipe for a production workload, you may want to consider using a dedicated account. This will help to isolate your Snowpipe pipelines from other workloads and to improve performance.