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COPY INTO <table>

The COPY INTO command in Databend enables data to be loaded from files in multiple locations.

One of its key features is that it provides idempotency by keeping track of files that have already been processed for a default period of 7 days.

This behavior can be customized using the load_file_metadata_expire_hours global setting.

See Also: COPY INTO location

Supported File Locations​

Your data files must be located in one of these locations for COPY INTO to work:

Syntax​

COPY INTO [<database>.]<table_name>
FROM { internalStage | externalStage | externalLocation }
[ FILES = ( '<file_name>' [ , '<file_name>' ] [ , ... ] ) ]
[ PATTERN = '<regex_pattern>' ]
[ FILE_FORMAT = ( TYPE = { CSV | TSV | NDJSON | PARQUET | XML} [ formatTypeOptions ] ) ]
[ copyOptions ]

Where:

internalStage​

internalStage ::= @<internal_stage_name>[/<path>]

externalStage​

externalStage ::= @<external_stage_name>[/<path>]

Also see How to Create External Stage.

externalLocation​

Databend's external location is a feature that allows users to access data stored outside of Databend's internal storage system, such as in cloud storage services like AWS S3 or Azure Blob Storage.

By defining an external location, users can query data stored in external systems directly from Databend without having to load it into Databend's internal storage.

externalLocation ::=
  's3://<bucket>[<path>]'
  CONNECTION = (
        ENDPOINT_URL = 'https://<endpoint-URL>'
        ACCESS_KEY_ID = '<your-access-key-ID>'
        SECRET_ACCESS_KEY = '<your-secret-access-key>'
        ROLE_ARN = '<your-ARN-of-IAM-role>'
        EXTERNAL_ID = '<your-external-ID>'
        SESSION_TOKEN = '<your-session-token>'
        REGION = '<region-name>'
        ENABLE_VIRTUAL_HOST_STYLE = 'true|false'
  )
note

To access your Amazon S3 buckets, you can use one of two methods: providing AWS access keys and secrets, or specifying an AWS IAM role and external ID for authentication.

By specifying an AWS IAM role and external ID, you can provide more granular control over which S3 buckets a user can access. This means that if the IAM role has been granted permissions to access only specific S3 buckets, then the user will only be able to access those buckets. An external ID can further enhance security by providing an additional layer of verification. For more information, see https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-role.html

ParameterDescriptionRequired
s3://<bucket>[<path>]External files located at the AWS S3 compatible object storage.Required
ENDPOINT_URLThe bucket endpoint URL starting with "https://". To use a URL starting with "http://", set allow_insecure to true in the [storage] block of the file databend-query-node.toml.Required
ACCESS_KEY_IDYour access key ID for connecting the AWS S3 compatible object storage. If not provided, Databend will access the bucket anonymously.Optional
SECRET_ACCESS_KEYYour secret access key for connecting the AWS S3 compatible object storage.Optional
ROLE_ARNAmazon Resource Name (ARN) of an AWS Identity and Access Management (IAM) role.Optional
EXTERNAL_IDYour external ID for authentication when accessing specific Amazon S3 buckets.Optional
SESSION_TOKENYour temporary credential for connecting the AWS S3 service.Optional
REGIONAWS region name. For example, us-east-1.Optional
ENABLE_VIRTUAL_HOST_STYLEIf you use virtual hosting to address the bucket, set it to "true".Optional

FILES = ( 'file1' [ , 'file2' ... ] )​

Specifies a list of one or more files names (separated by commas) to be loaded.

PATTERN = 'regex_pattern'​

A PCRE2-based regular expression pattern string, enclosed in single quotes, specifying the file names to match. Click here to see an example. For PCRE2 syntax, see http://www.pcre.org/current/doc/html/pcre2syntax.html.

FILE_FORMAT​

See Input & Output File Formats.

copyOptions​

copyOptions ::=
  [ SIZE_LIMIT = <num> ]
  [ PURGE = <bool> ]
  [ FORCE = <bool> ]
  [ ON_ERROR = { continue | abort } ]
ParameterDescriptionRequired
SIZE_LIMITSpecifies the maximum rows of data to be loaded for a given COPY statement. Defaults to 0 meaning no limits.Optional
PURGEIf True, the command will purge the files in the stage after they are loaded successfully into the table. Default: False.Optional
FORCEDefaults to False meaning the command will skip duplicate files in the stage when copying data. If True, duplicate files will not be skipped.Optional
ON_ERRORProvides options to handle a file containing errors. Select continue to skip the file and continue, or abort (default) to abort the load operation.Optional
note

The parameter ON_ERROR currently does not work for parquet files.

Examples​

Loading Data from an Internal Stage​

COPY INTO mytable FROM @my_internal_s1 pattern = 'books.*parquet' FILE_FORMAT = (TYPE = PARQUET);

Loading Data from an External Stage​

COPY INTO mytable FROM @my_external_s1 pattern = 'books.*parquet' FILE_FORMAT = (TYPE = PARQUET);

Loading Data from External Locations​

AWS S3 compatible object storage services

This example reads 10 rows from a CSV file and inserts them into a table:

-- Authenticated by AWS access keys and secrets.
COPY INTO mytable
  FROM 's3://mybucket/data.csv'
  CONNECTION = (
        ENDPOINT_URL = 'https://<endpoint-URL>'
        ACCESS_KEY_ID = '<your-access-key-ID>'
        SECRET_ACCESS_KEY = '<your-secret-access-key>')
  FILE_FORMAT = (type = CSV field_delimiter = ','  record_delimiter = '\n' skip_header = 1) size_limit=10;

-- Authenticated by AWS IAM role and external ID.
COPY INTO mytable
  FROM 's3://mybucket/data.csv'
  CONNECTION = (
        ENDPOINT_URL = 'https://<endpoint-URL>'
        ROLE_ARN = 'arn:aws:iam::123456789012:role/my_iam_role'
        EXTERNAL_ID = '123456')
  FILE_FORMAT = (type = csv field_delimiter = ',' record_delimiter = '\n' skip_header = 1) size_limit=10;

This example reads 10 rows from a CSV file compressed as GZIP and inserts them into a table:

COPY INTO mytable
  FROM 's3://mybucket/data.csv.gz'
  CONNECTION = (
        ENDPOINT_URL = 'https://<endpoint-URL>'
        ACCESS_KEY_ID = '<your-access-key-ID>'
        SECRET_ACCESS_KEY = '<your-secret-access-key>')
  FILE_FORMAT = (type = CSV field_delimiter = ',' record_delimiter = '\n' skip_header = 1 compression = 'GZIP') size_limit=10;

This example loads data from a CSV file without specifying the endpoint URL:

COPY INTO mytable
  FROM 's3://mybucket/data.csv'
  FILE_FORMAT = (type = CSV field_delimiter = ','  record_delimiter = '\n' skip_header = 1) size_limit=10;

This is an example loading data from a Parquet file:

COPY INTO mytable
  FROM 's3://mybucket/data.parquet'
  CONNECTION = (
      ACCESS_KEY_ID = '<your-access-key-ID>'
      SECRET_ACCESS_KEY = '<your-secret-access-key>')
  FILE_FORMAT = (TYPE = PARQUET);

Azure Blob storage

This example reads data from a CSV file and inserts it into a table:

COPY INTO mytable
    FROM 'azblob://mybucket/data.csv'
    CONNECTION = (
        ENDPOINT_URL = 'https://<account_name>.blob.core.windows.net'
        ACCOUNT_NAME = '<account_name>'
        ACCOUNT_KEY = '<account_key>'
    )
    FILE_FORMAT = (type = CSV);

Remote Files

As shown in this example, data is loaded from three remote CSV files, but a file will be skipped if it contains errors:

COPY INTO mytable
    FROM 'https://repo.databend.rs/dataset/stateful/ontime_200{6,7,8}_200.csv'
    FILE_FORMAT = (type = CSV) ON_ERROR=continue;

IPFS

This example reads data from a CSV file on IPFS and inserts it into a table:

COPY INTO mytable
    FROM 'ipfs://<your-ipfs-hash>' connection = (endpoint_url = 'https://<your-ipfs-gateway>')
    FILE_FORMAT = (type = CSV field_delimiter = ',' record_delimiter = '\n' skip_header = 1);

Loading Data with Pattern Matching​

This example uses pattern matching to only load from CSV files containing sales in their names:

COPY INTO mytable
  FROM 's3://mybucket/'
  PATTERN = '.*sales.*[.]csv'
  FILE_FORMAT = (type = CSV field_delimiter = ','  record_delimiter = '\n' skip_header = 1);

Where .* is interpreted as zero or more occurrences of any character. The square brackets escape the period character (.) that precedes a file extension.

If you want to load from all the CSV files, use PATTERN = '.*[.]csv':

COPY INTO mytable
  FROM 's3://mybucket/'
  PATTERN = '.*[.]csv'
  FILE_FORMAT = (type = CSV field_delimiter = ','  record_delimiter = '\n' skip_header = 1);

Tutorials​

Here are some tutorials to help you get started with COPY INTO: