Azure Data Engineer Course | Microsoft Azure Data Engineer

1
Optimizing Query Performance in Azure Synapse

• Title

Subtitle Best Practices Techniques
2
Introduction to Azure Synapse Performance
Optimization

• What is Azure Synapse? A cloud-based analytics
  service for big data and data warehousing.
• Why optimize queries? Improves speed, reduces
  costs, and enhances user experience.
• Common challenges Large datasets, inefficient
  queries, poor indexing, and resource constraints.

3
Understanding Synapse SQL Architecture

• Two SQL Pools
• Dedicated SQL Pool (for structured data
  processing).
• Serverless SQL Pool (for on-demand data
  exploration).
• Distributed Processing Model Uses Massively
  Parallel Processing (MPP) for query execution.
• Importance of Partitioning Distribution
  Affects query performance.

4
Best Practices for Query Optimization

• Choose the Right Data Distribution Strategy
• Hash Distribution for even data spread.
• Round-Robin Distribution for general use.
• Replicated Tables for small reference data.
• Use Columnstore Indexes for efficient storage and
  faster scans.
• Optimize Joins Aggregations using proper
  indexing and data modeling.
• Minimize Data Movement by aligning distributions
  in joins.

5
Performance Tuning with Indexing Statistics

• Columnstore vs. Rowstore Indexes
• Columnstore for analytics.
• Rowstore for transactional queries.
• Update Statistics Regularly to improve query
  execution plans.
• Use Materialized Views for faster access to
  precomputed results.

6
Query Performance Optimization Techniques

• Avoid SELECT Fetch only required columns.
• Filter Early with WHERE Clauses Reduce
  unnecessary data scans.
• Optimize CTEs Temp Tables Minimize temporary
  data processing overhead.
• Use Result Set Caching Store frequently used
  query results for reuse.

7
Managing Workload Resource Allocation

• Use Workload Management for Query Prioritization
• Assign Resource Classes to optimize memory usage.
• Set Query Timeouts to prevent long-running
  queries.
• Monitor Query Performance Using Synapse
  Monitoring Tools
• Synapse Studio View query execution plans.
• DMVs (Dynamic Management Views) Analyze query
  stats and resource usage.

8
Advanced Optimization Strategies

• Partition Large Tables to speed up query
  execution.
• Leverage Azure Data Lake for Staging Data before
  transformation.
• Use Materialized Views Caching for repeated
  queries.
• Enable Result Set Caching for frequently accessed
  data.

9
Conclusion Next Steps

• Optimizing Azure Synapse queries improves speed,
  efficiency, and cost-effectiveness.
• Key Takeaways
• Choose the right distribution strategy.
• Use indexing statistics wisely.
• Optimize queries, joins, and aggregations.
• Monitor query performance and workload
  management.
• Next Steps
• Implement best practices in your Synapse
  environment.
• Explore Synapse Studio for performance
  monitoring.
• QA

10
Thank You
www.visualpath.in