Improving performance with Iceberg sorted tables

Sorted Iceberg tables significantly enhance query performance and reduce cloud storage costs by organizing data according to one or more columns, thus minimizing the number of files read during data retrieval. This sorting approach drastically cuts down on query times, especially in large datasets, by only accessing necessary files rather than scanning all data, as demonstrated with the TPC-DS benchmark. For example, a sorted version of the catalog_sales table on the cs_sold_date_sk column showed a substantial decrease in data read compared to its unsorted counterpart. Implementing these sorted tables in Apache Iceberg, particularly in conjunction with the Starburst Galaxy platform, provides an efficient solution for optimizing data storage and retrieval processes. Additionally, materialized views can also benefit from sorted columns, further enhancing performance. Iceberg's optimize command consolidates smaller files into larger, sorted ones, maintaining performance advantages even as data is streamed or batch processed. This methodology not only improves performance but also yields cost savings in cloud object storage, making it a valuable strategy in data management.