--- toc_priority: 7 toc_title: S3 --- # S3 Table Engine {#table-engine-s3} This engine provides integration with [Amazon S3](https://aws.amazon.com/s3/) ecosystem. This engine is similar to the [HDFS](../../../engines/table-engines/special/file.md#table_engines-hdfs) engine, but provides S3-specific features. ## Create Table {#creating-a-table} ``` sql CREATE TABLE s3_engine_table (name String, value UInt32) ENGINE = S3(path, [aws_access_key_id, aws_secret_access_key,] format, [compression]) ``` **Engine parameters** - `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 [below](#wildcards-in-path). - `format` — The [format](../../../interfaces/formats.md#formats) of the file. - `aws_access_key_id`, `aws_secret_access_key` - Long-term credentials for the [AWS](https://aws.amazon.com/) account user. You can use these to authenticate your requests. Parameter is optional. If credentials are not specified, they are used from the configuration file. For more information see [Using S3 for Data Storage](../mergetree-family/mergetree.md#table_engine-mergetree-s3). - `compression` — Compression type. Supported values: `none`, `gzip/gz`, `brotli/br`, `xz/LZMA`, `zstd/zst`. Parameter is optional. By default, it will autodetect compression by file extension. **Example** 1. Set up the `s3_engine_table` table: ``` sql CREATE TABLE s3_engine_table (name String, value UInt32) ENGINE=S3('https://storage.yandexcloud.net/my-test-bucket-768/test-data.csv.gz', 'CSV', 'gzip'); ``` 2. Fill file: ``` sql INSERT INTO s3_engine_table VALUES ('one', 1), ('two', 2), ('three', 3); ``` 3. Query the data: ``` sql SELECT * FROM s3_engine_table LIMIT 2; ``` ```text ┌─name─┬─value─┐ │ one │ 1 │ │ two │ 2 │ └──────┴───────┘ ``` ## Virtual columns {#virtual-columns} - `_path` — Path to the file. - `_file` — Name of the file. For more information about virtual columns see [here](../../../engines/table-engines/index.md#table_engines-virtual_columns). ## Implementation Details {#implementation-details} - Reads and writes can be parallel - Not supported: - `ALTER` and `SELECT...SAMPLE` operations. - Indexes. - Replication. ## Wildcards In Path {#wildcards-in-path} `path` argument can specify multiple files using bash-like wildcards. For being processed file should exist and match to the whole path pattern. Listing of files is determined during `SELECT` (not at `CREATE` moment). - `*` — Substitutes any number of any characters except `/` including empty string. - `?` — Substitutes any single character. - `{some_string,another_string,yet_another_one}` — Substitutes any of strings `'some_string', 'another_string', 'yet_another_one'`. - `{N..M}` — Substitutes any number in range from N to M including both borders. N and M can have leading zeroes e.g. `000..078`. Constructions with `{}` are similar to the [remote](../../../sql-reference/table-functions/remote.md) table function. **Example** 1. Suppose we have several files in CSV format with the 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/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’ There are several ways to make a table consisting of all six files: The first way: ``` sql CREATE TABLE table_with_range (name String, value UInt32) ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_{1..3}', 'CSV'); ``` Another way: ``` sql CREATE TABLE table_with_question_mark (name String, value UInt32) ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_?', 'CSV'); ``` Table consists of all the files in both directories (all files should satisfy format and schema described in query): ``` sql CREATE TABLE table_with_asterisk (name String, value UInt32) ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV'); ``` If the listing of files contains number ranges with leading zeros, use the construction with braces for each digit separately or use `?`. **Example** Create table with files named `file-000.csv`, `file-001.csv`, … , `file-999.csv`: ``` sql CREATE TABLE big_table (name String, value UInt32) ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV'); ``` ## Virtual Columns {#virtual-columns} - `_path` — Path to the file. - `_file` — Name of the file. **See Also** - [Virtual columns](../../../engines/table-engines/index.md#table_engines-virtual_columns) ## S3-related settings {#settings} The following settings can be set before query execution or placed into configuration file. - `s3_max_single_part_upload_size` — The maximum size of object to upload using singlepart upload to S3. Default value is `64Mb`. - `s3_min_upload_part_size` — The minimum size of part to upload during multipart upload to [S3 Multipart upload](https://docs.aws.amazon.com/AmazonS3/latest/dev/uploadobjusingmpu.html). Default value is `512Mb`. - `s3_max_redirects` — Max number of S3 redirects hops allowed. Default value is `10`. - `s3_single_read_retries` — The maximum number of attempts during single read. Default value is `4`. Security consideration: if malicious user can specify arbitrary S3 URLs, `s3_max_redirects` must be set to zero to avoid [SSRF](https://en.wikipedia.org/wiki/Server-side_request_forgery) attacks; or alternatively, `remote_host_filter` must be specified in server configuration. ## Endpoint-based Settings {#endpoint-settings} The following settings can be specified in configuration file for given endpoint (which will be matched by exact prefix of a URL): - `endpoint` — Specifies prefix of an endpoint. Mandatory. - `access_key_id` and `secret_access_key` — Specifies credentials to use with given endpoint. Optional. - `use_environment_credentials` — If set to `true`, S3 client will try to obtain credentials from environment variables and [Amazon EC2](https://en.wikipedia.org/wiki/Amazon_Elastic_Compute_Cloud) metadata for given endpoint. Optional, default value is `false`. - `region` — Specifies S3 region name. Optional. - `use_insecure_imds_request` — If set to `true`, S3 client will use insecure IMDS request while obtaining credentials from Amazon EC2 metadata. Optional, default value is `false`. - `header` — Adds specified HTTP header to a request to given endpoint. Optional, can be speficied multiple times. - `server_side_encryption_customer_key_base64` — If specified, required headers for accessing S3 objects with SSE-C encryption will be set. Optional. - `max_single_read_retries` — The maximum number of attempts during single read. Default value is `4`. Optional. **Example:** ``` xml https://storage.yandexcloud.net/my-test-bucket-768/ ``` ## Usage {#usage-examples} Suppose we have several files in CSV format with the 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/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' 1. There are several ways to make a table consisting of all six files: ``` sql CREATE TABLE table_with_range (name String, value UInt32) ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_{1..3}', 'CSV'); ``` 2. Another way: ``` sql CREATE TABLE table_with_question_mark (name String, value UInt32) ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/some_file_?', 'CSV'); ``` 3. Table consists of all the files in both directories (all files should satisfy format and schema described in query): ``` sql CREATE TABLE table_with_asterisk (name String, value UInt32) ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/{some,another}_prefix/*', 'CSV'); ``` !!! warning "Warning" If the listing of files contains number ranges with leading zeros, use the construction with braces for each digit separately or use `?`. 4. Create table with files named `file-000.csv`, `file-001.csv`, … , `file-999.csv`: ``` sql CREATE TABLE big_table (name String, value UInt32) ENGINE = S3('https://storage.yandexcloud.net/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV'); ``` ## See also - [S3 table function](../../../sql-reference/table-functions/s3.md)