--- toc_priority: 45 toc_title: s3 --- # S3 Table Function {#s3-table-function} Provides table-like interface to select/insert files in [Amazon S3](https://aws.amazon.com/s3/). This table function is similar to [hdfs](../../sql-reference/table-functions/hdfs.md), but provides S3-specific features. **Syntax** ``` sql s3(path, [aws_access_key_id, aws_secret_access_key,] format, structure, [compression]) ``` **Arguments** - `path` — Bucket url with path to file. Supports following wildcards in readonly mode: `*`, `?`, `{abc,def}` and `{N..M}` where `N`, `M` — numbers, `'abc'`, `'def'` — strings. For more information see [here](../../engines/table-engines/integrations/s3.md#wildcards-in-path). - `format` — The [format](../../interfaces/formats.md#formats) of the file. - `structure` — Structure of the table. Format `'column1_name column1_type, column2_name column2_type, ...'`. - `compression` — Parameter is optional. Supported values: `none`, `gzip/gz`, `brotli/br`, `xz/LZMA`, `zstd/zst`. By default, it will autodetect compression by file extension. **Returned value** A table with the specified structure for reading or writing data in the specified file. **Examples** Selecting the first two rows from the table from S3 file `https://storage.yandexcloud.net/my-test-bucket-768/data.csv`: ``` 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 │ └─────────┴─────────┴─────────┘ ``` The similar but from file with `gzip` compression: ``` 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 │ └─────────┴─────────┴─────────┘ ``` ## Usage {#usage-examples} Suppose that we have several files with following URIs on S3: - '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' Count the amount of rows in files ending with numbers from 1 to 3: ``` 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 │ └─────────┘ ``` Count the total amount of rows in all files in these two directories: ``` 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" If your listing of files contains number ranges with leading zeros, use the construction with braces for each digit separately or use `?`. Count the total amount of rows in files named `file-000.csv`, `file-001.csv`, … , `file-999.csv`: ``` 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 │ └─────────┘ ``` Insert data into file `test-data.csv.gz`: ``` sql INSERT INTO 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); ``` Insert data into file `test-data.csv.gz` from existing table: ``` sql INSERT INTO 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; ``` **See Also** - [S3 engine](../../engines/table-engines/integrations/s3.md) [Original article](https://clickhouse.tech/docs/en/sql-reference/table-functions/s3/)