Query Optimization in Azure Synapse: Tips for Speed and Scale

Once you’ve designed your tables and chosen the right distribution strategy, the next big lever for performance is query optimization. In Azure Synapse Dedicated SQL Pools, this means writing efficient SQL, minimizing data movement, and ensuring the engine has the information it needs to generate the best query plan.

Let’s explore key optimization techniques that will help your workloads scale efficiently.

Update and Maintain Statistics

Synapse uses statistics to estimate row counts and choose the best query plan. Outdated or missing stats can lead to poor performance.

• Run UPDATE STATISTICS after large data loads.
• Monitor query plans for warnings about stale or missing stats.
• Use DBCC commands to inspect distribution skew and table metadata.

Use Explicit Column Projection

Avoid SELECT *. Instead, project only the columns you actually need.

• Reduces memory usage and I/O
• Makes result sets smaller
• Speeds up intermediate operations like joins and aggregations

Optimize Joins

Data movement during joins is one of the biggest performance killers in Synapse.

• Join on distribution keys when possible to avoid shuffles
• If joining on replicated tables, ensure they are truly small (< 2GB)
• Use appropriate join types (INNER, LEFT, etc.) for the workload

Leverage Materialized Views

Materialized views can pre-aggregate and cache results from expensive queries.

• Useful for repeated reporting workloads
• Must be manually refreshed in Synapse
• Can significantly reduce query complexity and runtime

Filter Early and Often

Push filters as close to the data as possible.

• Use WHERE clauses to reduce rows early in the query plan
• Filter staging or fact tables before joins to minimize row processing
• Partition elimination (on partitioned tables) helps prune unnecessary data

Avoid Common Pitfalls

• Don’t rely on default distribution—analyze and choose based on usage
• Avoid using low-cardinality columns as distribution keys
• Monitor for data skew and adjust design as needed

In Part 5, we’ll dive into resource management and cost optimization strategies—including how to scale your compute resources, manage concurrency, and pause workloads when idle.