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Aug 24, 2025
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Restructure query guides with improved organization and navigation #2706

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2c24646
improve guides/query
BohuTANG Aug 24, 2025
a66fad7
fix: remove broken links from DDL docs to query guides
BohuTANG Aug 24, 2025
e8a06a8
trigger fresh build
BohuTANG Aug 24, 2025
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44 changes: 23 additions & 21 deletions docs/cn/release-notes/databend.md
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---
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';
Expand All @@ -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>
2 changes: 1 addition & 1 deletion docs/en/guides/00-products/01-dee/10-enterprise-features.md
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Expand Up @@ -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. |
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2 changes: 1 addition & 1 deletion docs/en/guides/20-cloud/20-manage/01-monitor.md
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Expand Up @@ -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

Expand Down
2 changes: 1 addition & 1 deletion docs/en/guides/51-ai-functions/01-external-functions.md
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Expand Up @@ -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
4 changes: 4 additions & 0 deletions docs/en/guides/54-query/00-basics/_category_.json
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{
"label": "Basic Queries",
"position": 1
}
90 changes: 90 additions & 0 deletions docs/en/guides/54-query/00-basics/aggregating-data.md
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---
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
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