s3Cluster Table Function

This is an extension to the s3 table function.

Allows processing files from Amazon S3 and Google Cloud Storage Google Cloud Storage in parallel from many nodes in a specified cluster. On initiator it creates a connection to all nodes in the cluster, discloses asterisks in S3 file path, and dispatches each file dynamically. On the worker node it asks the initiator about the next task to process and processes it. This is repeated until all tasks are finished.

Syntax

s3Cluster(cluster_name, url [, NOSIGN | access_key_id, secret_access_key, [session_token]] [,format] [,structure] [,compression_method],[,headers])
s3Cluster(cluster_name, named_collection[, option=value [,..]])

Arguments

cluster_name — Name of a cluster that is used to build a set of addresses and connection parameters to remote and local servers.
url — path to a file or a bunch of files. Supports following wildcards in readonly mode: *, **, ?, {'abc','def'} and {N..M} where N, M — numbers, abc, def — strings. For more information see Wildcards In Path.
NOSIGN — If this keyword is provided in place of credentials, all the requests will not be signed.
access_key_id and secret_access_key — Keys that specify credentials to use with given endpoint. Optional.
session_token - Session token to use with the given keys. Optional when passing keys.
format — The format 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.
headers - Parameter is optional. Allows headers to be passed in the S3 request. Pass in the format headers(key=value) e.g. headers('x-amz-request-payer' = 'requester'). See here for example of use.

Arguments can also be passed using named collections. In this case url, access_key_id, secret_access_key, format, structure, compression_method work in the same way, and some extra parameters are supported:

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

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

Examples

Select the data from all the files in the /root/data/clickhouse and /root/data/database/ folders, using all the nodes in the cluster_simple cluster:

SELECT * FROM s3Cluster(
    'cluster_simple',
    'http://minio1:9001/root/data/{clickhouse,database}/*',
    'minio',
    'minio123',
    'CSV',
    'name String, value UInt32, polygon Array(Array(Tuple(Float64, Float64)))'
) ORDER BY (name, value, polygon);

Count the total amount of rows in all files in the cluster cluster_simple:

Tip

If your listing of files contains number ranges with leading zeros, use the construction with braces for each digit separately or use ?.

For production use cases, it is recommended to use named collections. Here is the example:

CREATE NAMED COLLECTION creds AS
        access_key_id = 'minio',
        secret_access_key = 'minio123';
SELECT count(*) FROM s3Cluster(
    'cluster_simple', creds, url='https://s3-object-url.csv',
    format='CSV', structure='name String, value UInt32, polygon Array(Array(Tuple(Float64, Float64)))'
)

Accessing private and public buckets

Users can use the same approaches as document for the s3 function here.

Optimizing performance

For details on optimizing the performance of the s3 function see our detailed guide.

See Also

Accessing private and public buckets​

Optimizing performance​

Accessing private and public buckets

Optimizing performance