Enhancements to ScyllaDB’s Filtering Implementation

ScyllaDB's Open Source 3.0 release introduces enhanced filtering support, addressing the reliance on the ALLOW FILTERING keyword by the Spark-Cassandra connector when generating CQL queries. Although filtering can be useful, it may negatively impact performance, prompting a need for alternative solutions such as schema changes, secondary indexing, or materialized views. These alternatives can help avoid the inefficiencies of filtering, which executes only after fetching all potential rows, leading to unnecessary data processing. The discussion highlights the importance of thoughtful data model design to mitigate performance issues related to filtering, and it provides insights into the conditions when ALLOW FILTERING might be beneficial, particularly in low selectivity queries. Additionally, the blog post underscores the impact of filtering on performance through a local test, suggesting that sequential scans can sometimes outperform random index lookups, especially in specific scenarios.