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Provides a table-like interface to `SELECT` and `INSERT` data from [Google Cloud Storage](https://cloud.google.com/storage/). Requires the [`Storage Object User` IAM role](https://cloud.google.com/storage/docs/access-control/iam-roles).

This is an alias of the [s3 table function](/docs/sql-reference/table-functions/s3).

If you have multiple replicas in your cluster, you can use the [s3Cluster function](/docs/sql-reference/table-functions/s3Cluster) (which works with GCS) instead to parallelize inserts.

## Syntax[​](#syntax "Direct link to Syntax")

```
gcs(url [, NOSIGN | hmac_key, hmac_secret] [,format] [,structure] [,compression_method])
gcs(named_collection[, option=value [,..]])
```

GCS

The GCS Table Function integrates with Google Cloud Storage by using the GCS XML API and HMAC keys.
See the [Google interoperability docs](https://cloud.google.com/storage/docs/interoperability) for more details about the endpoint and HMAC.

## Arguments[​](#arguments "Direct link to Arguments")

|  |  |  |  |  |  |  |  |  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Argument Description|  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `url` Bucket path to file. Supports following wildcards in readonly mode: `*`, `**`, `?`, `{abc,def}` and `{N..M}` where `N`, `M` — numbers, `'abc'`, `'def'` — strings.| `NOSIGN` If this keyword is provided in place of credentials, all the requests will not be signed.|  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | | `hmac_key` and `hmac_secret` Keys that specify credentials to use with given endpoint. Optional.|  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | | `format` The [format](/docs/sql-reference/formats) of the file.| `structure` Structure of the table. Format `'column1_name column1_type, column2_name column2_type, ...'`.| `compression_method` Parameter is optional. Supported values: `none`, `gzip` or `gz`, `brotli` or `br`, `xz` or `LZMA`, `zstd` or `zst`. By default, it will autodetect compression method by file extension. | | | | | | | | | | | | | |

GCS

The GCS path is in this format as the endpoint for the Google XML API is different than the JSON API:

```
  https://storage.googleapis.com/<bucket>/<folder>/<filename(s)>
```

and not ~~<https://storage.cloud.google.com>~~.

Arguments can also be passed using [named collections](/docs/operations/named-collections). In this case `url`, `format`, `structure`, `compression_method` work in the same way, and some extra parameters are supported:

|  |  |  |  |  |  |  |  |  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Parameter Description|  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `access_key_id` `hmac_key`, optional.| `secret_access_key` `hmac_secret`, optional.| `filename` Appended to the url if specified.|  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | | `use_environment_credentials` Enabled by default, allows passing extra parameters using environment variables `AWS_CONTAINER_CREDENTIALS_RELATIVE_URI`, `AWS_CONTAINER_CREDENTIALS_FULL_URI`, `AWS_CONTAINER_AUTHORIZATION_TOKEN`, `AWS_EC2_METADATA_DISABLED`.| `no_sign_request` Disabled by default.|  |  | | --- | --- | | `expiration_window_seconds` Default value is 120. | | | | | | | | | | | | | |

## Returned value[​](#returned_value "Direct link to Returned value")

A table with the specified structure for reading or writing data in the specified file.

## Examples[​](#examples "Direct link to Examples")

Selecting the first two rows from the table from GCS file `https://storage.googleapis.com/my-test-bucket-768/data.csv`:

```
SELECT *
FROM gcs('https://storage.googleapis.com/clickhouse_public_datasets/my-test-bucket-768/data.csv.gz', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
LIMIT 2;
```

```
┌─column1─┬─column2─┬─column3─┐
│       1 │       2 │       3 │
│       3 │       2 │       1 │
└─────────┴─────────┴─────────┘
```

The similar but from file with `gzip` compression method:

```
SELECT *
FROM gcs('https://storage.googleapis.com/clickhouse_public_datasets/my-test-bucket-768/data.csv.gz', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32', 'gzip')
LIMIT 2;
```

```
┌─column1─┬─column2─┬─column3─┐
│       1 │       2 │       3 │
│       3 │       2 │       1 │
└─────────┴─────────┴─────────┘
```

## Usage[​](#usage "Direct link to Usage")

Suppose that we have several files with following URIs on GCS:

- '<https://storage.googleapis.com/my-test-bucket-768/some_prefix/some_file_1.csv>'
- '<https://storage.googleapis.com/my-test-bucket-768/some_prefix/some_file_2.csv>'
- '<https://storage.googleapis.com/my-test-bucket-768/some_prefix/some_file_3.csv>'
- '<https://storage.googleapis.com/my-test-bucket-768/some_prefix/some_file_4.csv>'
- '<https://storage.googleapis.com/my-test-bucket-768/another_prefix/some_file_1.csv>'
- '<https://storage.googleapis.com/my-test-bucket-768/another_prefix/some_file_2.csv>'
- '<https://storage.googleapis.com/my-test-bucket-768/another_prefix/some_file_3.csv>'
- '<https://storage.googleapis.com/my-test-bucket-768/another_prefix/some_file_4.csv>'

Count the amount of rows in files ending with numbers from 1 to 3:

```
SELECT count(*)
FROM gcs('https://storage.googleapis.com/clickhouse_public_datasets/my-test-bucket-768/{some,another}_prefix/some_file_{1..3}.csv', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
```

```
┌─count()─┐
│      18 │
└─────────┘
```

Count the total amount of rows in all files in these two directories:

```
SELECT count(*)
FROM gcs('https://storage.googleapis.com/clickhouse_public_datasets/my-test-bucket-768/{some,another}_prefix/*', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
```

```
┌─count()─┐
│      24 │
└─────────┘
```

Note

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`:

```
SELECT count(*)
FROM gcs('https://storage.googleapis.com/clickhouse_public_datasets/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV', 'name String, value UInt32');
```

```
┌─count()─┐
│      12 │
└─────────┘
```

Insert data into file `test-data.csv.gz`:

```
INSERT INTO FUNCTION gcs('https://storage.googleapis.com/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:

```
INSERT INTO FUNCTION gcs('https://storage.googleapis.com/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip')
SELECT name, value FROM existing_table;
```

Glob \*\* can be used for recursive directory traversal. Consider the below example, it will fetch all files from `my-test-bucket-768` directory recursively:

```
SELECT * FROM gcs('https://storage.googleapis.com/my-test-bucket-768/**', 'CSV', 'name String, value UInt32', 'gzip');
```

The below get data from all `test-data.csv.gz` files from any folder inside `my-test-bucket` directory recursively:

```
SELECT * FROM gcs('https://storage.googleapis.com/my-test-bucket-768/**/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip');
```

For production use cases it is recommended to use [named collections](/docs/operations/named-collections). Here is the example:

```
CREATE NAMED COLLECTION creds AS
        access_key_id = '***',
        secret_access_key = '***';
SELECT count(*)
FROM gcs(creds, url='https://s3-object-url.csv')
```

## Partitioned Write[​](#partitioned-write "Direct link to Partitioned Write")

If you specify `PARTITION BY` expression when inserting data into `GCS` table, a separate file is created for each partition value. Splitting the data into separate files helps to improve reading operations efficiency.