Exploring Sharded Tables in BigQuery: Advantages and Use Cases

Pseudo-partitioning in BigQuery refers to a method where data is stored split between different tables, each having a different suffix in the name, formatted as dataset.table_name_{your_suffix}. This allows the tables to be queried as one by using a wildcard *, which retrieves data from all the tables matching the wildcard, essentially performing an invisible UNION ALL behind the scenes.

BigQuery discourages the use of sharded tables with date suffixes because there is an overhead in terms of storing a separate schema and metadata for each table, as well as additional permission checks. This overhead is compared to the more efficient method of using a date-partitioned table, which is designed to handle time-based data more effectively and with less complexity.

BigQuery offers a quick way to convert a group of date-sharded tables to a regular date-partitioned table, although the specific method is not detailed in the text. Users interested in this conversion process should refer to the official BigQuery documentation or follow-up resources for the exact steps and commands.