As my application scales, I'm starting to see performance issues related to our current database schema. I believe the way our tables are structured might not be optimal for handling increased data vo
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推荐解决方案
最相关的解决方案
10 个解决方案Scale Up Hardware
Consider increasing RAM, CPU cores, or using faster storage (e.g., SSDs) if hardware is the limiting factor.
Monitor Resource Utilization
Track CPU, memory, and disk I/O during the workload execution to identify resource bottlenecks.
Create Composite Indexes
Consider creating indexes that cover multiple columns used together in query predicates.
Identify Missing Indexes
Use database performance monitoring tools or query execution plans to find columns that would benefit from indexing.
Analyze Query Execution Plans
Use `EXPLAIN` or `EXPLAIN ANALYZE` to identify bottlenecks in the query execution and optimize accordingly.
Rewrite Suboptimal Queries
Refactor queries to use more efficient join strategies, avoid `SELECT *`, and utilize window functions where appropriate.
Add Appropriate Indexes
Create indexes on columns frequently used in WHERE clauses, JOIN conditions, and ORDER BY clauses.
Optimize Connection Pooling
Ensure efficient connection management to reduce overhead for frequent query executions.
Tune Query Planner Settings
Adjust parameters like `work_mem` (PostgreSQL) or `sort_buffer_size` (MySQL) to allow for larger sorts and hash joins in memory.
Review and Adjust Memory Buffers
Increase shared_buffers (PostgreSQL) or innodb_buffer_pool_size (MySQL) to cache more data in memory.
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常见问题
与此问题及其解决方案相关的常见问题。
What type of database system are you using?
How frequently do these connection failures occur?
What type of sensitive customer information are you handling?
What specific database operations are exhibiting the most significant performance issues?
What types of data are most critical to your company's operations?
Which specific financial reports are showing discrepancies?
When did the performance degradation begin?
What is the typical duration of these unexpected downtimes?
Which database system are you using?
What is the approximate latency you are experiencing between data generation and its availability for decision-making?
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已识别原因
Lack of Proper Indexing
90%Missing or inefficient indexes on frequently queried columns force the database to perform full table scans, significantly slowing down read operations as data grows.
Denormalization Issues
70%Over-normalization can lead to excessive JOINs, increasing query complexity and execution time. Conversely, excessive denormalization can lead to data redundancy and update anomalies.
Inefficient Data Types or Storage
60%Using inappropriate data types (e.g., storing large text blobs in primary tables) or inefficient storage mechanisms can bloat tables and slow down operations.
Poorly Designed Relationships
50%Circular references, overly complex relationships, or incorrect foreign key constraints can lead to performance bottlenecks and data integrity issues.
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