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domaintaishanghu.com
summaryOkay, I've reviewed the logs you provided. Here's a breakdown of what I see and some observations:

Overall Observations:

* Heavy SQL Querying: The system is performing a large number of SQL queries. This is a common pattern for web applications, but excessive queries can significantly impact performance.
* Slow Queries: Some queries, particularly those involving `SELECT ... FROM website_friendlink` and `SELECT ... FROM download_article`, are taking a considerable amount of time (ranging from 0.017s to 0.028s). This is a key area for optimization. The "RunTime" values indicate the time taken for each of these queries.
* Index Usage (Potential): Based on the query patterns, there might be opportunities to improve performance by adding or optimizing indexes. The queries selecting from `website_friendlink`, `download_article` and `article` frequently filter by `website_id` and `id`, suggesting that indexes on those columns could be very beneficial.
* `SELECT ... FROM ... WHERE ... LIKE CONCAT, keyword`: The repeated use of `LIKE CONCAT, keyword` is likely a performance bottleneck. `LIKE` with a wildcard (`%`) is generally slow, especially when the wildcard is at the beginning of the pattern. If possible, try to avoid wildcards or optimize the matching conditions.

Specific Queries and Potential Improvements:

1. `SELECT ... FROM website_friendlink WHERE website_id = 9385` (and similar)
* Issue: This query is likely slow because it's scanning the entire `website_friendlink` table.
* Solution: Create an index on the `website_id` column in the `website_friendlink` table:
```sql
CREATE INDEX idx_website_id ON website_friendlink (website_id);
```

2. `SELECT ... FROM download_article WHERE website_id = 9385` (and similar)
* Issue: Same as above. This is a table scan.
* Solution: Create an index on the `website_id` column in the `download_article` table:
```sql
CREATE INDEX idx_website_id_download_article ON download_article (website_id);
```

3. `SELECT ... FROM article WHERE id IN (1516976,1895490,1791854,1774767,1986754)`
* Issue: This query uses an `IN` clause with multiple values. While not as bad as a full table scan, it still isn't ideal.
* Solution: If these `id` values are relatively static, consider creating an index on the `id` column of the `article` table:
```sql
CREATE INDEX idx_article_id ON article (id);
```
or, if the IDs are used very frequently, and you can change the query to use a prepared statement (to avoid repeatedly parsing the query), that would be even more efficient.

4. `SELECT ... FROM ... WHERE ... LIKE` (General)
* Issue: Using `LIKE` with wildcards (`%`) is slow.
* Solution:
* Avoid Wildcards (if possible): If you can modify your application logic to avoid using wildcards, it's the best solution.
* Full-Text Search (Advanced): If you need to perform complex pattern matching, consider using a full-text search engine (like MySQL's built-in fulltext index or a dedicated search engine) for faster and more efficient searching. This is a more complex solution, but can provide significant performance benefits.

Recommendations:

1. Analyze Query Performance: Use your database's query analyzer tools (e.g., `EXPLAIN` in MySQL) to get a detailed breakdown of how each query is executed. This will show you which parts of the query are the slowest and whether indexes are being used effectively.
2. Index Optimization: Based on the query analysis, carefully create indexes on the columns that are frequently used in `WHERE` clauses, `JOIN` conditions, and `ORDER BY` clauses.
3. Query Optimization: Review your application code to see if you can rewrite queries to be more efficient.
4. Caching: Implement caching mechanisms to store frequently accessed data and reduce the load on the database.
5. Database Server Tuning: Ensure your database server is properly configured for optimal performance.

To help me give you even more specific advice, could you tell me:

* What database system are you using? (e.g., MySQL, PostgreSQL, SQL Server, etc.)
* Can you provide a more complete query example that is slow? (The ones you showed are just snippets). Knowing the entire query is important.
* What is the size of your tables? (e.g., number of rows).
titleBeluga Accelerator - Beluga Accelerator Official Genuine - Beluga Accelerator Organ Network
descriptionBeluga Accelerator makes accessing overseas websites stress-free! Unlock global content and enjoy the international Internet. The official Beluga accelerator only requires one accelerator software.
keywordslimit, like, show, full, columns, twitter, order, type, article, website, description, hammer, http, queries, reads
upstreams
downstreams
nslookupA 104.21.60.140, A 172.67.197.129
created2025-12-06
updated2025-12-06
summarized2025-12-11

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