PLEASE NOTE: This webinar is hosted on Microsoft Teams. Once you register, please use the link to sign up on Teams.
Slowness of query execution can stem from countless potential causes.
Thankfully, Snowflake offers virtually unlimited computing power, which can be easily scaled up or out as needed. This advanced architecture results in significantly fewer performance issues.
However, as support engineers, solution architects, sales engineers, or system engineers, we still encounter performance challenges in our daily work.
This scalability can potentially hide underlying issues:
- Have we thoroughly analysed the SQL itself to identify potential areas for improvement?
- Can clustering or other solutions be applied?
- Can the query be refactored to minimise table scans or eliminate unnecessary joins?
This becomes particularly crucial when customers migrate from other platforms to Snowflake with strict performance SLAs for their critical workloads. In such cases, the environment is typically not the root cause. These scenarios often escalate quickly, as there is a strong emphasis on ensuring a smooth and timely migration to our platform.
Will Riley will talk about how to quickly diagnose performance issue, mainly focusing on performance tuning and SQL optimisation. For example, by minimizing unnecessary data scans through effective clustering, pruning, or the use of it's Search Optimization Service (SOS), Snowflake can greatly enhance query speed and cost-efficiency, leading to improved overall performance for data analytics and reporting tasks.
