--- slug: /zh/sql-reference/table-functions/s3 sidebar_position: 45 sidebar_label: s3 --- # S3 表函数 {#s3-table-function} 提供类似于表的接口来 select/insert [Amazon S3](https://aws.amazon.com/s3/)中的文件。这个表函数类似于[hdfs](../../sql-reference/table-functions/hdfs.md),但提供了 S3 特有的功能。 **语法** ``` sql s3(path, [aws_access_key_id, aws_secret_access_key,] format, structure, [compression]) ``` **参数** - `path` — 带有文件路径的 Bucket url。在只读模式下支持以下通配符: `*`, `?`, `{abc,def}` 和 `{N..M}` 其中 `N`, `M` 是数字, `'abc'`, `'def'` 是字符串. 更多信息见[下文](#wildcards-in-path). - `format` — 文件的[格式](../../interfaces/formats.md#formats). - `structure` — 表的结构. 格式像这样 `'column1_name column1_type, column2_name column2_type, ...'`. - `compression` — 压缩类型. 支持的值: `none`, `gzip/gz`, `brotli/br`, `xz/LZMA`, `zstd/zst`. 参数是可选的. 默认情况下,通过文件扩展名自动检测压缩类型. **返回值** 一个具有指定结构的表,用于读取或写入指定文件中的数据。 **示例** 从 S3 文件`https://storage.yandexcloud.net/my-test-bucket-768/data.csv`中选择表格的前两行: ``` sql SELECT * FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32') LIMIT 2; ``` ``` text ┌─column1─┬─column2─┬─column3─┐ │ 1 │ 2 │ 3 │ │ 3 │ 2 │ 1 │ └─────────┴─────────┴─────────┘ ``` 类似的情况,但来源是`gzip`压缩的文件: ``` sql SELECT * FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/data.csv.gz', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32', 'gzip') LIMIT 2; ``` ``` text ┌─column1─┬─column2─┬─column3─┐ │ 1 │ 2 │ 3 │ │ 3 │ 2 │ 1 │ └─────────┴─────────┴─────────┘ ``` ## 用法 {#usage-examples} 假设我们在S3上有几个文件,URI如下: - 'https://storage.yandexcloud.net/my-test-bucket-768/some_prefix/some_file_1.csv' - 'https://storage.yandexcloud.net/my-test-bucket-768/some_prefix/some_file_2.csv' - 'https://storage.yandexcloud.net/my-test-bucket-768/some_prefix/some_file_3.csv' - 'https://storage.yandexcloud.net/my-test-bucket-768/some_prefix/some_file_4.csv' - 'https://storage.yandexcloud.net/my-test-bucket-768/another_prefix/some_file_1.csv' - 'https://storage.yandexcloud.net/my-test-bucket-768/another_prefix/some_file_2.csv' - 'https://storage.yandexcloud.net/my-test-bucket-768/another_prefix/some_file_3.csv' - 'https://storage.yandexcloud.net/my-test-bucket-768/another_prefix/some_file_4.csv' 计算以数字1至3结尾的文件的总行数: ``` sql SELECT count(*) FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_{1..3}.csv', 'CSV', 'name String, value UInt32') ``` ``` text ┌─count()─┐ │ 18 │ └─────────┘ ``` 计算这两个目录中所有文件的行的总量: ``` sql SELECT count(*) FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV', 'name String, value UInt32') ``` ``` text ┌─count()─┐ │ 24 │ └─────────┘ ``` !!! warning "Warning" 如果文件列表中包含有从零开头的数字范围,请对每个数字分别使用带括号的结构,或者使用`?`。 计算名为 `file-000.csv`, `file-001.csv`, … , `file-999.csv` 文件的总行数: ``` sql SELECT count(*) FROM s3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV', 'name String, value UInt32'); ``` ``` text ┌─count()─┐ │ 12 │ └─────────┘ ``` 插入数据到 `test-data.csv.gz` 文件: ``` sql INSERT INTO FUNCTION s3('https://storage.yandexcloud.net/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip') VALUES ('test-data', 1), ('test-data-2', 2); ``` 从已有的表插入数据到 `test-data.csv.gz` 文件: ``` sql INSERT INTO FUNCTION s3('https://storage.yandexcloud.net/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip') SELECT name, value FROM existing_table; ``` **另请参阅** - [S3 引擎](../../engines/table-engines/integrations/s3.md)