What is the primary purpose of partitioning staged data files for regular data loads?
What is the primary purpose of partitioning staged data files for regular data loads?
The primary purpose of partitioning staged data files for regular data loads is to improve the performance of data loads. By partitioning data, you can narrow the data load process to the most relevant files, effectively optimizing the loading speed and efficiency.
It's A & D : https://docs.snowflake.com/en/user-guide/data-load-considerations-stage#organizing-data-by-path A-> When loading your staged data, narrow the path to the most granular level that includes your data for improved data load performance D-> Organizing your data files by path lets you copy any fraction of the partitioned data into Snowflake with a single command
See, the question is primary purpose Hence, it is performance
A is correct
https://docs.snowflake.com/en/user-guide/data-load-considerations-manage Note "S3 transmits a directory list with each COPY statement used by Snowflake, so reducing the number of files in each directory improves the performance of your COPY statements. You may even consider creating subfolders of 10-15 minute increments within the folders for each hour." --reducing the number of files in each directory improves the performance of your COPY statements. meaning more partition, better the performance.
When staging regular data sets, we recommend partitioning the data into logical paths that include identifying details such as geographical location or other source identifiers, along with the date when the data was written. Organizing your data files by path lets you copy any fraction of the partitioned data into Snowflake with a single command. This allows you to execute concurrent COPY statements that match a subset of files, taking advantage of parallel operations. https://docs.snowflake.com/en/user-guide/data-load-considerations-stage#organizing-data-by-path
Parallel operations, thus performance.