databendlabs · BohuTANG · Aug 7, 2025 · Aug 7, 2025
diff --git a/docs/cn/guides/40-load-data/04-transform/04-querying-metadata.md b/docs/cn/guides/40-load-data/04-transform/04-querying-metadata.md
@@ -17,11 +17,11 @@ sidebar_label: 元数据
 
 ## 查询元数据详细指南
 
-| 文件格式 | 指南                                                                                |
-| ----------- | ------------------------------------------------------------------------------------ |
-| Parquet     | [使用元数据查询 Parquet 文件](./00-querying-parquet.md#query-with-metadata)         |
-| CSV         | [使用元数据查询 CSV 文件](./01-querying-csv.md#query-with-metadata)                 |
-| TSV         | [使用元数据查询 TSV 文件](./02-querying-tsv.md#query-with-metadata)                 |
-| NDJSON      | [使用元数据查询 NDJSON 文件](./03-querying-ndjson.md#query-with-metadata)           |
-| ORC         | [使用元数据查询 ORC 文件](./03-querying-orc.md#query-with-metadata)                 |
-| Avro        | [使用元数据查询 Avro 文件](./04-querying-avro.md#query-with-metadata)               |
+| 文件格式 | 指南                                                                 |
+| ----------- |--------------------------------------------------------------------|
+| Parquet     | [使用元数据查询 Parquet 文件](./00-querying-parquet.md#query-with-metadata) |
+| CSV         | [使用元数据查询 CSV 文件](./01-querying-csv.md#query-with-metadata)         |
+| TSV         | [使用元数据查询 TSV 文件](./02-querying-tsv.md#query-with-metadata)         |
+| NDJSON      | [使用元数据查询 NDJSON 文件](./03-querying-ndjson.md#query-with-metadata)   |
+| ORC         | [使用元数据查询 ORC 文件](./05-querying-orc.md#query-with-metadata)         |
+| Avro        | [使用元数据查询 Avro 文件](./04-querying-avro.md#query-with-metadata)       |
diff --git a/docs/cn/guides/40-load-data/04-transform/index.md b/docs/cn/guides/40-load-data/04-transform/index.md
@@ -36,11 +36,11 @@ FROM {@<stage_name>[/<path>] [<table_alias>] | '<uri>' [<table_alias>]}
 
 ## 支持的文件格式
 
-| 文件格式 | 返回格式 | 访问方法 | 示例 | 指南 |
-| ----------- | ------------ | ------------- | ------- | ----- |
+| 文件格式 | 返回格式 | 访问方法 | 示例 | 指南                                        |
+| ----------- | ------------ | ------------- | ------- |-------------------------------------------|
 | Parquet | 原生数据类型 | 直接列名 | `SELECT id, name FROM` | [查询 Parquet 文件](./00-querying-parquet.md) |
-| ORC | 原生数据类型 | 直接列名 | `SELECT id, name FROM` | [查询 ORC 文件](./03-querying-orc.md) |
-| CSV | 字符串值 | 位置引用 `$<position>` | `SELECT $1, $2 FROM` | [查询 CSV 文件](./01-querying-csv.md) |
-| TSV | 字符串值 | 位置引用 `$<position>` | `SELECT $1, $2 FROM` | [查询 TSV 文件](./02-querying-tsv.md) |
-| NDJSON | Variant 对象 | 路径表达式 `$1:<field>` | `SELECT $1:id, $1:name FROM` | [查询 NDJSON 文件](./03-querying-ndjson.md) |
-| Avro | Variant 对象 | 路径表达式 `$1:<field>` | `SELECT $1:id, $1:name FROM` | [查询 Avro 文件](./04-querying-avro.md) |
+| ORC | 原生数据类型 | 直接列名 | `SELECT id, name FROM` | [查询 ORC 文件](./05-querying-orc.md)         |
+| CSV | 字符串值 | 位置引用 `$<position>` | `SELECT $1, $2 FROM` | [查询 CSV 文件](./01-querying-csv.md)         |
+| TSV | 字符串值 | 位置引用 `$<position>` | `SELECT $1, $2 FROM` | [查询 TSV 文件](./02-querying-tsv.md)         |
+| NDJSON | Variant 对象 | 路径表达式 `$1:<field>` | `SELECT $1:id, $1:name FROM` | [查询 NDJSON 文件](./03-querying-ndjson.md)   |
+| Avro | Variant 对象 | 路径表达式 `$1:<field>` | `SELECT $1:id, $1:name FROM` | [查询 Avro 文件](./04-querying-avro.md)       |
diff --git a/docs/cn/guides/40-load-data/index.md b/docs/cn/guides/40-load-data/index.md
@@ -52,7 +52,7 @@ Databend 强大的 ETL 能力支持从多种数据源和格式高效加载数据
 <summary> ORC </summary>
 
 - [将 ORC 数据导入表](./03-load-semistructured/04-load-orc.md)
-- [直接查询 ORC 文件](./04-transform/03-querying-orc.md)
+- [直接查询 ORC 文件](./04-transform/05-querying-orc.md)
 
 </details>
 

diff --git a/docs/en/guides/40-load-data/04-transform/00-querying-parquet.md b/docs/en/guides/40-load-data/04-transform/00-querying-parquet.md
@@ -3,32 +3,12 @@ title: Querying Parquet Files in Stage
 sidebar_label: Parquet
 ---
 
-## Query Parquet Files in Stage
 
-Syntax:
-```sql
-SELECT [<alias>.]<column> [, <column> ...] 
-FROM {@<stage_name>[/<path>] [<table_alias>] | '<uri>' [<table_alias>]} 
-[( 
-  [<connection_parameters>],
-  [ PATTERN => '<regex_pattern>'],
-  [ FILE_FORMAT => 'PARQUET | <custom_format_name>'],
-  [ FILES => ( '<file_name>' [ , '<file_name>' ] [ , ... ] ) ],
-  [ CASE_SENSITIVE => true | false ]
-)]
-```
-
-:::info Tips
-**Query Return Content Explanation:**
+## Syntax:
 
-* **Return Format**: Column values in their native data types (not variants)
-* **Access Method**: Directly use column names `column_name`
-* **Example**: `SELECT id, name, age FROM @stage_name`
-* **Key Features**:
-  * No need for path expressions (like `$1:name`)
-  * No type casting required
-  * Parquet files contain embedded schema information
-:::
+- [Query rows as Variants](./index.md#query-rows-as-variants)
+- [Query columns by name](./index.md#query-columns-by-name)
+- [Query Metadata](./index.md#query-metadata)
 
 ## Tutorial
 
@@ -47,14 +27,14 @@ CONNECTION = (
 ### Step 2. Create Custom Parquet File Format
 
 ```sql
-CREATE FILE FORMAT parquet_query_format 
-    TYPE = PARQUET
-    ;
+CREATE FILE FORMAT parquet_query_format TYPE = PARQUET;
 ```
 - More Parquet file format options refer to [Parquet File Format Options](/sql/sql-reference/file-format-options#parquet-options)
 
 ### Step 3. Query Parquet Files
 
+query with colum names:
+
 ```sql
 SELECT *
 FROM @parquet_query_stage
@@ -63,6 +43,20 @@ FROM @parquet_query_stage
     PATTERN => '.*[.]parquet'
 );
 ```
+
+query with path expressions:
+
+
+```sql
+SELECT $1
+FROM @parquet_query_stage
+(
+    FILE_FORMAT => 'parquet_query_format',
+    PATTERN => '.*[.]parquet'
+);
+```
+
+
 ### Query with Metadata
 
 Query Parquet files directly from a stage, including metadata columns like `METADATA$FILENAME` and `METADATA$FILE_ROW_NUMBER`:
@@ -77,4 +71,4 @@ FROM @parquet_query_stage
     FILE_FORMAT => 'parquet_query_format',
     PATTERN => '.*[.]parquet'
 );
-```
+```
diff --git a/docs/en/guides/40-load-data/04-transform/01-querying-csv.md b/docs/en/guides/40-load-data/04-transform/01-querying-csv.md
@@ -3,33 +3,10 @@ title: Querying CSV Files in Stage
 sidebar_label: CSV
 ---
 
-## Query CSV Files in Stage
+## Syntax:
 
-Syntax:
-```sql
-SELECT [<alias>.]$<col_position> [, $<col_position> ...] 
-FROM {@<stage_name>[/<path>] [<table_alias>] | '<uri>' [<table_alias>]} 
-[( 
-  [<connection_parameters>],
-  [ PATTERN => '<regex_pattern>'],
-  [ FILE_FORMAT => 'CSV| <custom_format_name>'],
-  [ FILES => ( '<file_name>' [ , '<file_name>' ] [ , ... ] ) ]
-)]
-```
-
-
-:::info Tips
-**Query Return Content Explanation:**
-
-* **Return Format**: Individual column values as strings by default
-* **Access Method**: Use positional references `$<col_position>` (e.g., `$1`, `$2`, `$3`)
-* **Example**: `SELECT $1, $2, $3 FROM @stage_name`
-* **Key Features**:
-  * Columns accessed by position, not by name
-  * Each `$<col_position>` refers to a single column, not the whole row
-  * Type casting required for non-string operations (e.g., `CAST($1 AS INT)`)
-  * No embedded schema information in CSV files
-:::
+- [Query columns by position](./index.md#query-columns-by-position)
+- [Query Metadata](./index.md#query-metadata)
 
 ## Tutorial
 

diff --git a/docs/en/guides/40-load-data/04-transform/02-querying-tsv.md b/docs/en/guides/40-load-data/04-transform/02-querying-tsv.md
@@ -3,33 +3,11 @@ title: Querying TSV Files in Stage
 sidebar_label: TSV
 ---
 
-## Query TSV Files in Stage
+## Syntax:
 
-Syntax:
-```sql
-SELECT [<alias>.]$<col_position> [, $<col_position> ...] 
-FROM {@<stage_name>[/<path>] [<table_alias>] | '<uri>' [<table_alias>]} 
-[( 
-  [<connection_parameters>],
-  [ PATTERN => '<regex_pattern>'],
-  [ FILE_FORMAT => 'TSV| <custom_format_name>'],
-  [ FILES => ( '<file_name>' [ , '<file_name>' ] [ , ... ] ) ]
-)]
-```
-
-
-:::info Tips
-**Query Return Content Explanation:**
+- [Query columns by position](./index.md#query-columns-by-position)
+- [Query Metadata](./index.md#query-metadata)
 
-* **Return Format**: Individual column values as strings by default
-* **Access Method**: Use positional references `$<col_position>` (e.g., `$1`, `$2`, `$3`)
-* **Example**: `SELECT $1, $2, $3 FROM @stage_name`
-* **Key Features**:
-  * Columns accessed by position, not by name
-  * Each `$<col_position>` refers to a single column, not the whole row
-  * Type casting required for non-string operations (e.g., `CAST($1 AS INT)`)
-  * No embedded schema information in TSV files
-:::
 
 ## Tutorial
 

diff --git a/docs/en/guides/40-load-data/04-transform/03-querying-ndjson.md b/docs/en/guides/40-load-data/04-transform/03-querying-ndjson.md
@@ -21,33 +21,10 @@ NDJSON (Newline Delimited JSON) is a JSON-based file format where each line cont
 - **Big data compatible**: Widely used in log files, data exports, and ETL pipelines
 - **Easy to process**: Each line is an independent JSON object, enabling parallel processing
 
-## Query NDJSON Files in Stage
+## Syntax
 
-Syntax:
-```sql
-SELECT [<alias>.]$1:<column> [, $1:<column> ...] 
-FROM {@<stage_name>[/<path>] [<table_alias>] | '<uri>' [<table_alias>]} 
-[( 
-  [<connection_parameters>],
-  [ PATTERN => '<regex_pattern>'],
-  [ FILE_FORMAT => 'NDJSON| <custom_format_name>'],
-  [ FILES => ( '<file_name>' [ , '<file_name>' ] [ , ... ] ) ]
-)]
-```
-
-
-:::info Tips
-**Query Return Content Explanation:**
-
-* **Return Format**: Each row as a single variant object (referenced as `$1`)
-* **Access Method**: Use path expressions `$1:column_name`
-* **Example**: `SELECT $1:title, $1:author FROM @stage_name`
-* **Key Features**:
-  * Must use path notation to access specific fields
-  * Type casting required for type-specific operations (e.g., `CAST($1:id AS INT)`)
-  * Each NDJSON line is parsed as a complete JSON object
-  * Whole row is represented as a single variant object
-:::
+- [Query rows as Variants](./index.md#query-rows-as-variants)
+- [Query Metadata](./index.md#query-metadata)
 
 ## Tutorial
 
@@ -106,34 +83,9 @@ FROM @ndjson_query_stage
 ```
 
 **Key difference:** The pattern `.*[.]ndjson[.]gz` matches files ending with `.ndjson.gz`. Databend automatically decompresses gzip files during query execution thanks to the `COMPRESSION = AUTO` setting in the file format.
-### Query with Metadata
-
-You can also include file metadata in your queries, which is useful for tracking data lineage and debugging:
-
-```sql
-SELECT
-    METADATA$FILENAME,
-    METADATA$FILE_ROW_NUMBER,
-    $1:title, $1:author
-FROM @ndjson_query_stage
-(
-    FILE_FORMAT => 'ndjson_query_format',
-    PATTERN => '.*[.]ndjson'
-);
-```
-
-**Metadata columns explained:**
-- `METADATA$FILENAME`: Shows which file each row came from - helpful when querying multiple files
-- `METADATA$FILE_ROW_NUMBER`: Shows the line number within the source file - useful for tracking specific records
-
-**Use cases:**
-- **Data lineage**: Track which source file contributed each record
-- **Debugging**: Identify problematic records by file and line number
-- **Incremental processing**: Process only specific files or ranges within files
 
 ## Related Documentation
 
 - [Loading NDJSON Files](../03-load-semistructured/03-load-ndjson.md) - How to load NDJSON data into tables
 - [NDJSON File Format Options](/sql/sql-reference/file-format-options#ndjson-options) - Complete NDJSON format configuration
-- [CREATE STAGE](/sql/sql-commands/ddl/stage/ddl-create-stage) - Managing external and internal stages
-- [Querying Metadata](./04-querying-metadata.md) - More details about metadata columns
+- [CREATE STAGE](/sql/sql-commands/ddl/stage/ddl-create-stage) - Managing external and internal stages
diff --git a/docs/en/guides/40-load-data/04-transform/04-querying-avro.md b/docs/en/guides/40-load-data/04-transform/04-querying-avro.md
@@ -3,32 +3,10 @@ title: Querying Avro Files in Stage
 sidebar_label: Avro
 ---
 
-## Query Avro Files in Stage
+## Syntax:
 
-Syntax:
-```sql
-SELECT [<alias>.]$1:<column> [, $1:<column> ...]
-FROM {@<stage_name>[/<path>] [<table_alias>] | '<uri>' [<table_alias>]}
-[(
-  [<connection_parameters>],
-  [ PATTERN => '<regex_pattern>'],
-  [ FILE_FORMAT => 'AVRO'],
-  [ FILES => ( '<file_name>' [ , '<file_name>' ] [ , ... ] ) ]
-)]
-```
-
-:::info Tips
-**Query Return Content Explanation:**
-
-* **Return Format**: Each row as a single variant object (referenced as `$1`)
-* **Access Method**: Use path expressions `$1:column_name`
-* **Example**: `SELECT $1:id, $1:name FROM @stage_name`
-* **Key Features**:
-  * Must use path notation to access specific fields
-  * Type casting required for type-specific operations (e.g., `CAST($1:id AS INT)`)
-  * Avro schema is mapped to variant structure
-  * Whole row is represented as a single variant object
-:::
+- [Query rows as Variants](./index.md#query-rows-as-variants)
+- [Query Metadata](./index.md#query-metadata)
 
 ## Avro Querying Features Overview
 

diff --git a/docs/en/guides/40-load-data/04-transform/04-querying-metadata.md b/docs/en/guides/40-load-data/04-transform/04-querying-metadata.md