kb.pub

My database schema seems to be poorly designed, leading to inefficient data retrieval and storage. I believe a redesign could significantly improve performance and maintainability.

问题描述

My database schema seems to be poorly designed, leading to inefficient data retrieval and storage. I believe a redesign could significantly improve performance and maintainability.
1
公开会话
10
可用解决方案
4
已识别原因

推荐解决方案

最相关的解决方案

10 个解决方案

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.

相关性分数会随着您回答更多问题而更新

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?

演示诊断会话

探索此问题的真实诊断会话,包含不同场景和解决方案。

已识别原因

Missing or Inefficient Indexes

80%

Crucial columns used in WHERE clauses, JOIN conditions, or ORDER BY clauses may lack appropriate indexes, forcing full table scans.

Lack of Normalization / Denormalization Issues

75%

The schema might be overly denormalized, leading to data redundancy and update anomalies, or it might be too normalized, causing excessive joins for simple queries.

Inappropriate Data Types

60%

Using overly large or inappropriate data types (e.g., VARCHAR for fixed-length strings, large numeric types for small values) can waste storage and slow down operations.

Poorly Structured Relationships (e.g., Orphaned Records, Excessive Foreign Keys)

50%

Complex or incorrectly defined relationships between tables can lead to performance bottlenecks and data integrity issues.

开始您的诊断会话

获得针对您问题的个性化帮助。我们基于AI的诊断系统将通过一系列问题引导您找到最佳解决方案。

开始诊断