Restructure query guides with improved organization and navigation (#2706)

* improve guides/query

* fix: remove broken links from DDL docs to query guides

Remove external links from DDL documentation to query guides to maintain independence between SQL reference and user guides sections. This fixes build failures caused by broken links after query guides restructuring.

Changes:
- Remove references to query-profile from EXPLAIN and monitoring docs
- Replace external links with inline examples in CREATE FUNCTION docs
- Update stored procedure references to use DDL documentation
- Remove guide links from aggregating index and dictionary functions
- Update UDF link paths to match new hierarchical structure

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <[email protected]>

* trigger fresh build

---------

Co-authored-by: Claude <[email protected]>

Author: BohuTANG

docs/cn/release-notes/databend.md

@@ -1,14 +1,16 @@
 ---
-sidebar_label: Databend 版本发布
-title: Databend 版本发布
+sidebar_label: Databend Releases
+title: Databend Releases
 sidebar_position: 1
 slug: /
 ---
 
 import StepsWrap from '@site/src/components/StepsWrap';
 import StepContent from '@site/src/components/Steps/step-content';
 
-本页面提供 <a href="https://github.com/databendlabs/databend">Databend</a> 最新功能、增强与错误修复的相关信息。
+This page provides information about recent features, enhancements, and bug fixes for <a href="https://github.com/databendlabs/databend">Databend</a>.
+
+
 
 import MD1 from '@site/docs/release-stable/2025-04-21_v1.2.725.md';
 import MD2 from '@site/docs/release-stable/2025-02-14_v1.2.697.md';
@@ -35,138 +37,138 @@ import MD17 from '@site/docs/release-stable/2023-12-13_v1.2.233.md';
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.725" number="-1">
 
-## 2025 年 4 月 21 日（v1.2.725）
+## Apr 21, 2025 (v1.2.725)
 
 <MD1 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.697" number="">
 
-## 2025 年 2 月 14 日（v1.2.697）
+## Feb 14, 2025 (v1.2.697)
 
 <MD2 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.680" number="">
 
-## 2025 年 1 月 2 日（v1.2.680）
+## Jan 2, 2025 (v1.2.680)
 
 <MD3 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.615" number="">
 
-## 2024 年 8 月 19 日（v1.2.615）
+## Aug 19, 2024 (v1.2.615)
 
 <MD4 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.609" number="">
 
-## 2024 年 8 月 13 日（v1.2.609）
+## Aug 13, 2024 (v1.2.609)
 
 <MD5 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.530" number="">
 
-## 2024 年 6 月 16 日（v1.2.530）
+## Jun 16, 2024 (v1.2.530)
 
 <MD6 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.452" number="">
 
-## 2024 年 5 月 6 日（v1.2.452）
+## May 6, 2024 (v1.2.452)
 
 <MD7 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.410" number="">
 
-## 2024 年 4 月 8 日（v1.2.410）
+## Apr 8, 2024 (v1.2.410)
 
 <MD8 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.371" number="">
 
-## 2024 年 3 月 11 日（v1.2.371）
+## Mar 11, 2024 (v1.2.371)
 
 <MD9 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.344" number="">
 
-## 2024 年 2 月 22 日（v1.2.344）
+## Feb 22, 2024 (v1.2.344)
 
 <MD10 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.307" number="">
 
-## 2024 年 1 月 25 日（v1.2.307）
+## Jan 25, 2024 (v1.2.307)
 
 <MD11 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.292" number="">
 
-## 2024 年 1 月 11 日（v1.2.292）
+## Jan 11, 2024 (v1.2.292)
 
 <MD12 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.290" number="">
 
-## 2024 年 1 月 10 日（v1.2.290）
+## Jan 10, 2024 (v1.2.290)
 
 <MD13 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.279" number="">
 
-## 2024 年 1 月 2 日（v1.2.279）
+## Jan 2, 2024 (v1.2.279)
 
 <MD14 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.275" number="">
 
-## 2023 年 12 月 30 日（v1.2.275）
+## Dec 30, 2023 (v1.2.275)
 
 <MD15 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.262" number="">
 
-## 2023 年 12 月 20 日（v1.2.262）
+## Dec 20, 2023 (v1.2.262)
 
 <MD16 />
 
 </StepContent>
 
 <StepContent outLink="https://github.com/databendlabs/databend/releases/tag/v1.2.233" number="">
 
-## 2023 年 12 月 13 日（v1.2.233）
+## Dec 13, 2023 (v1.2.233)
 
 <MD17 />
 
 </StepContent>
 
-</StepsWrap>
+</StepsWrap> 

docs/en/guides/00-products/01-dee/10-enterprise-features.md

@@ -20,7 +20,7 @@ This page provides an updated list of available enterprise features. To access t
 | [Ngram Index](/guides/performance/ngram-index)                                  | Query Performance  | Accelerate LIKE pattern matching queries with wildcard searches.                                                                                                                                                                                                                                                                                                                                                                                                        |
 | [Virtual Column](/sql/sql-commands/ddl/virtual-column)                          | Query Performance  | Automatically accelerate JSON queries with zero-configuration performance optimization for VARIANT data.                                                                                                                                                                                                                                                                                                                                                                |
 | [Dynamic Column](/sql/sql-commands/ddl/table/ddl-create-table#computed-columns)  | Query Performance  | Generate columns automatically from scalar expressions with stored or virtual calculation modes.                                                                                                                                                                                                                                                                                                                                                                         |
-| [Python UDF](/guides/query/udf#python-requires-databend-enterprise)              | Advanced Analytics | Execute Python code within SQL queries using built-in handler.                                                                                                                                                                                                                                                                                                                                                                                                          |
+| [Python UDF](/guides/query/advanced/udf#python-requires-databend-enterprise)              | Advanced Analytics | Execute Python code within SQL queries using built-in handler.                                                                                                                                                                                                                                                                                                                                                                                                          |
 | [ATTACH TABLE](/sql/sql-commands/ddl/table/attach-table)                         | Data Sharing       | Create read-only links to existing table data with zero-copy access across environments.                                                                                                                                                                                                                                                                                                                                                                                |
 | [Stream](/sql/sql-commands/ddl/stream)                                           | Change Data Capture | Track and capture table changes for incremental data processing.                                                                                                                                                                                                                                                                                                                                                                                                        |
 | [Vacuum Temp Files](/sql/sql-commands/administration-cmds/vacuum-temp-files)     | Storage Management | Clean up temporary files (join, aggregate, sort spills) to free storage space.                                                                                                                                                                                                                                                                                                                                                                                          |

docs/en/guides/20-cloud/20-manage/01-monitor.md

@@ -27,7 +27,7 @@ The **SQL History** tab displays a list of SQL statements that have been execute
 Clicking a record on the **SQL History** page reveals detailed information on how Databend Cloud executed the SQL statement, providing access to the following tabs:
 
 - **Query Details**: Includes Query State (success or failure), Rows Scanned, Warehouse, Bytes Scanned, Start Time, End Time, and Handler Type.
-- **Query Profile**: Illustrates how the SQL statement was executed. For more information, see [Query Profile](/guides/query/query-profile).
+- **Query Profile**: Illustrates how the SQL statement was executed.
 
 ## Task History
 

docs/en/guides/51-ai-functions/01-external-functions.md

@@ -78,5 +78,5 @@ LIMIT 5;
 
 ## Learn More
 
-- **[External Functions Guide](/guides/query/external-function)** - Complete setup and deployment instructions
+- **[External Functions Guide](/guides/query/advanced/external-function)** - Complete setup and deployment instructions
 - **[Databend Cloud](https://databend.com)** - Try external functions with a free account

docs/en/guides/54-query/00-basics/_category_.json

@@ -0,0 +1,4 @@
+{
+  "label": "Basic Queries",
+  "position": 1
+}

docs/en/guides/54-query/00-basics/aggregating-data.md

@@ -0,0 +1,90 @@
+---
+title: Aggregating Data
+---
+
+Learn to summarize and analyze data using GROUP BY, aggregate functions, and advanced grouping techniques.
+
+## Basic Aggregation
+
+### Common Aggregate Functions
+```sql
+-- Count rows
+SELECT COUNT(*) FROM employees;
+
+-- Statistical functions
+SELECT 
+    AVG(salary) as avg_salary,
+    MIN(salary) as min_salary,
+    MAX(salary) as max_salary,
+    SUM(salary) as total_salary
+FROM employees;
+```
+
+## GROUP BY Fundamentals
+
+### Single Column Grouping
+```sql
+-- Count employees by department
+SELECT department, COUNT(*) as emp_count
+FROM employees 
+GROUP BY department;
+
+-- Average salary by department
+SELECT department, AVG(salary) as avg_salary
+FROM employees 
+GROUP BY department
+ORDER BY avg_salary DESC;
+```
+
+### Multiple Column Grouping
+```sql
+-- Group by department and hire year
+SELECT 
+    department,
+    EXTRACT(YEAR FROM hire_date) as hire_year,
+    COUNT(*) as count,
+    AVG(salary) as avg_salary
+FROM employees 
+GROUP BY department, EXTRACT(YEAR FROM hire_date)
+ORDER BY department, hire_year;
+```
+
+### GROUP BY with HAVING
+```sql
+-- Find departments with more than 5 employees
+SELECT department, COUNT(*) as emp_count
+FROM employees 
+GROUP BY department
+HAVING COUNT(*) > 5;
+
+-- Departments with average salary > 70000
+SELECT department, AVG(salary) as avg_salary
+FROM employees 
+GROUP BY department
+HAVING AVG(salary) > 70000;
+```
+
+## Advanced Grouping
+
+### GROUP BY ALL
+```sql
+-- Automatically group by all non-aggregate columns
+SELECT department, job_title, COUNT(*) as count
+FROM employees 
+GROUP BY ALL;
+```
+
+## Advanced Grouping Extensions
+
+Databend supports SQL:2003 standard grouping extensions:
+
+- **[ROLLUP](./groupby/group-by-rollup.md)** - Hierarchical subtotals
+- **[CUBE](./groupby/group-by-cube.md)** - All possible combinations  
+- **[GROUPING SETS](./groupby/group-by-grouping-sets.md)** - Custom combinations
+
+## Best Practices
+
+1. **Use appropriate aggregates** - COUNT(*) vs COUNT(column)
+2. **Filter before grouping** - Use WHERE before GROUP BY
+3. **Use HAVING for aggregate conditions** - Filter groups after aggregation
+4. **Consider indexes** - GROUP BY columns should be indexed