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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

問題の説明

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 volume and user traffic. I need to refactor the schema to ensure future scalability and maintainability.
1
公開セッション
10
利用可能な解決策
4
特定された原因

推奨される解決策

最も関連性の高いソリューション

10 ソリューション

Scale Up Hardware

75%

Consider increasing RAM, CPU cores, or using faster storage (e.g., SSDs) if hardware is the limiting factor.

Monitor Resource Utilization

75%

Track CPU, memory, and disk I/O during the workload execution to identify resource bottlenecks.

Create Composite Indexes

75%

Consider creating indexes that cover multiple columns used together in query predicates.

Identify Missing Indexes

75%

Use database performance monitoring tools or query execution plans to find columns that would benefit from indexing.

Analyze Query Execution Plans

75%

Use `EXPLAIN` or `EXPLAIN ANALYZE` to identify bottlenecks in the query execution and optimize accordingly.

Rewrite Suboptimal Queries

75%

Refactor queries to use more efficient join strategies, avoid `SELECT *`, and utilize window functions where appropriate.

Add Appropriate Indexes

75%

Create indexes on columns frequently used in WHERE clauses, JOIN conditions, and ORDER BY clauses.

Optimize Connection Pooling

75%

Ensure efficient connection management to reduce overhead for frequent query executions.

Tune Query Planner Settings

75%

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

75%

Increase shared_buffers (PostgreSQL) or innodb_buffer_pool_size (MySQL) to cache more data in memory.

より多くの質問に答えると、関連性スコアが更新されます

よくある質問

この問題とその解決策に関連する一般的な質問。

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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特定された原因

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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