Understanding Snowflake File Formats: Optimizing Your Data Operations

Snowflake’s cloud data platform offers exceptional flexibility in loading and unloading data. A vital element of this is the concept of file formats. File formats are essential for streamlining how Snowflake interacts with your data residing in internal or external stages. Let’s dive into what they are and how to get the most out of them.

What are Snowflake File Formats?

In essence, a Snowflake file format is a named database object. It acts as a set of instructions telling Snowflake how to parse and handle files you intend to load into Snowflake tables (or unload data from Snowflake). With a defined file format, Snowflake knows:

• File Type: Whether the data is structured (CSV, Parquet, ORC), semi-structured (JSON, Avro, XML), etc.
• Delimiters: How fields are separated in a file (commas, pipes, etc.).
• Compression: If and how the file is compressed (GZIP, BZIP2, etc.).
• Data Encoding: Character encoding the file uses (UTF-8, etc.).
• Additional Options: Specific to the file type (e.g., options for handling arrays in JSON).

Why Use File Formats?

1. Simplification: File formats eliminate the need to repeatedly specify formatting details each time you work with a particular file type.
2. Reusability: A file format can be used across multiple load and unload operations.
3. Governance: File formats help enforce data consistency and standardization.

Supported File Formats

Snowflake works with an extensive range of file formats:

• Structured
  • CSV (Comma-Separated Values)
  • Parquet
  • ORC (Optimized Row Columnar)
• Semi-Structured
  • JSON (JavaScript Object Notation)
  • Avro
  • XML (Extensible Markup Language)

Choosing the Right Format

The best Snowflake file format for you depends on several factors:

• Data Structure: Parquet and ORC are excellent choices for large, columnar datasets, while JSON or Avro are better suited for semi-structured data with nested elements.
• Performance Goals: Columnar formats like Parquet and ORC often provide faster query speeds thanks to columnar storage and compression.
• Flexibility: JSON and Avro can easily accommodate schema changes rather than highly structured formats.

Creating a File Format

Here’s an example of creating a CSV file format:

SQL

CREATE FILE FORMAT my_csv_format

  TYPE = CSV

  FIELD_DELIMITER = ‘,’

  SKIP_HEADER = 1; 

Use code with caution.

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Using a File Format

You reference a file format when using a COPY INTO statement for loading:

SQL

COPY INTO my_table

FROM @my_stage/data_files

FILE_FORMAT = my_csv_format;

Use code with caution.

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Key Takeaways

• File formats are essential for effectively managing data loading and unloading in Snowflake.
• Understanding the different file formats and their strengths helps you make informed choices.
• Use the CREATE FILE FORMAT and SHOW FILE FORMATS commands to manage your file formats within Snowflake.