What distribution option is ideal for a sales fact table containing billions of records?

The most suitable distribution option for a sales fact table containing billions of records is the HASH distribution method. Utilizing HASH distribution effectively balances data across different partitions based on the values of a specified column, which is typically a key column such as a sales transaction ID or customer ID. This method ensures that the workload is evenly distributed, leading to improved query performance as it reduces data movement during joins and aggregations.

With billions of records in a sales fact table, leveraging HASH distribution facilitates better performance during data retrieval and analysis. It minimizes the chances of "hot spots," where one partition becomes a performance bottleneck due to having significantly more data than others. Instead, data is spread out, which enhances parallel processing and enhances overall transactional throughput.

Choosing HASH distribution is particularly critical in a scenario with large datasets, like a sales fact table, because it maintains balanced partitions, which is essential for efficient query execution and data management. This approach is advantageous compared to alternatives that may not provide adequate distribution or may replicate data unnecessarily, causing inefficiencies and increased storage costs.