Snowflake Certification Practice Test

What element is important for improving performance in data ingestion?

1. Using smaller input files

2. Maintaining a consistent database schema

3. Increasing the number of stages

4. Utilizing a larger virtual warehouse only

The correct answer is: Using smaller input files

Using smaller input files is important for improving performance in data ingestion because it allows for more efficient processing of data within Snowflake. When smaller files are ingested, it can lead to better parallelism during the data loading process. Each file can be handled separately in different ingestion streams, enabling the system to process them concurrently. This parallelism significantly reduces the overall time taken to ingest large volumes of data. In contrast, having larger input files can lead to bottlenecks, where only a limited number of files are processed at once, increasing the time needed for data loading. Smaller files also minimize the chances of hitting memory limits or resource constraints, which can occur when dealing with very large files containing vast amounts of data. While maintaining a consistent database schema, increasing the number of stages, and utilizing a larger virtual warehouse can all contribute to performance improvements in certain contexts, they do not directly optimize the ingestion process in the same way that using smaller input files does. Each of these other factors may enhance overall database efficiency or resource allocation but does not specifically target the ingestion mechanism as effectively as smaller input files do.