The full request feature captures every SQL statement executed on your MySQL instance — not just slow queries — giving you a complete picture of database workload. Use it to troubleshoot performance incidents, generate SQL templates for stress testing, and identify the queries that consume the most resources.
Slow query logs only capture queries that exceed a time threshold. This leaves gaps in common scenarios:
CPU spike with no slow queries: An alert fires for 100% CPU utilization at 03:00 (UTC+8), but no slow queries are logged at that time. Full request data lets you reconstruct what was running during the spike.
Stress testing without SQL templates: Collecting SQL templates and execution frequencies from individual data providers is slow and error-prone. Full request generates SQL templates directly from production traffic.
Prioritizing optimization work: Not every slow query is worth optimizing immediately. Full request shows which queries consume the most cumulative resources, so you can focus on the highest-impact ones first.
Prerequisites
Before you begin, ensure that you have:
The full request feature enabled for the database instance
A MySQL database instance in the China (Shanghai) region
DAS Enterprise Edition enabled for the instance. For more information, see Enable and manage DAS Economy Edition and DAS Enterprise Edition
View full request data
Log on to the DAS console.
In the left-side navigation pane, choose Intelligent O&M Center > SQL Explorer.
Specify a time range to filter the Full Request Trend chart and the Full Request Statistics table.
To export the Full Request Statistics table, click Export. You can export up to 10 million rows at a time.
Understand the data
The SQL Explorer page surfaces full request data across three views:
| View | What it shows | When to use it |
|---|---|---|
| Execution Duration Distribution tab | Distribution of query execution durations across time, collected every minute | Spot when latency spikes occurred and gauge overall instance health |
| Full Request Statistics table | Per-SQL breakdown: SQL text, execution duration percentage, average execution duration, and execution trend | Identify which queries consume the most resources and prioritize optimization |
| SQL Sample tab | Client IP address and username for each SQL request | Trace traffic sources and access patterns |
Execution Duration Distribution
The chart divides query execution times into these ranges:
| Range | Description |
|---|---|
[0,1] ms | 0 ms to 1 ms |
(1,2] ms | Greater than 1 ms, up to 2 ms |
(2,3] ms | Greater than 2 ms, up to 3 ms |
(3,10] ms | Greater than 3 ms, up to 10 ms |
(10,100] ms | Greater than 10 ms, up to 100 ms |
(0.1,1] s | Greater than 0.1 s, up to 1 s |
> 1s | Greater than 1 s |
A larger blue area means most queries complete quickly — a healthy sign. Growing orange and red areas indicate that a significant portion of queries are slow, pointing to a performance problem that needs attention.
Example: For the period from 10:40:00 on October 19, 2020 to 10:40:00 on November 19, 2020:
34.30% of queries completed within
[0,1] ms23.13% of queries fell in the
(10,100] msrange25.98% of queries fell in the
(0.1,1] srange
Full Request Statistics
The Execution duration percentage column shows how much cumulative MySQL resource time each query pattern consumes:
Execution duration percentage =
(Execution duration of the SQL statement × Number of executions)
÷ (Total execution duration of all SQL statements × Total number of executions)
× 100%A high execution duration percentage means the query is a strong optimization candidate — reducing its execution time or execution count will have the largest impact on overall instance performance. Focus on these queries first when planning optimization work.
Click an SQL ID to drill into the performance trend and sample data for that specific query.
SQL templates
Full request groups structurally identical queries into SQL templates by replacing literal values with placeholders. Use SQL templates to:
Analyze business traffic patterns without processing millions of individual queries
Generate realistic workloads for stress testing before promotional events
Plan database capacity based on query distribution
SQL Sample
The SQL Sample tab shows the client IP address and username for each SQL request, giving you visibility into which applications or users are generating specific query patterns.
Execution duration over time
The Execution Duration tab (also referred to as SQL response time) plots query execution durations across the specified time range, making it easier to correlate latency changes with external events.
