COPY INTO <table>

COPY moves data between Databend tables and object storage system(Such as Amazon S3-like) files.

Loads data from staged files into a table, the files must be staged in one of the following locations:

• Named internal stage, files can be staged using the PUT to Stage.
• Named external stage that references an external location (Amazon S3 S3-like object storage system).
• External location (Amazon S3-like object storage system).

Syntax

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

Where:

internalStage

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

externalStage

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

externalLocation (for Amazon S3-like)

externalLocation (for Amazon S3) ::=
  's3://<bucket>[/<path>]'
  [ { CREDENTIALS = ( {  { AWS_KEY_ID = '<string>' AWS_SECRET_KEY = '<string>' } } ) } ]

Parameters	Description	Required
s3://<bucket>/[<path>]	Files are in the specified external location (S3-like bucket)	YES
[ { CREDENTIALS = ( { { AWS_KEY_ID = '<string>' AWS_SECRET_KEY = '<string>' } } ) } ]' ]	The credentials for connecting to AWS and accessing the private/protected S3 bucket where the files to load are staged.	Optional
[ ENDPOINT_URL = '<endpoint_url>' ]	S3-compatible endpoint URL like MinIO, default is https://s3.amazonaws.com	Optional

FILES = ( 'file_name' [ , 'file_name' ... ] )

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

PATTERN = 'regex_pattern'

A regular expression pattern string, enclosed in single quotes, specifying the file names to match.

formatTypeOptions

formatTypeOptions ::=
  RECORD_DELIMITER = '<character>' 
  FIELD_DELIMITER = '<character>' 
  SKIP_HEADER = <integer>

Parameters	Description	Required
RECORD_DELIMITER = '<character>'	One characters that separate records in an input file. Default '\n'	Optional
FIELD_DELIMITER = '<character>'	One characters that separate fields in an input file. Default ','	Optional
SKIP_HEADER = <integer>	Number of lines at the start of the file to skip. Default 0	Optional

copyOptions

copyOptions ::=
  [ SIZE_LIMIT = <num> ]

Parameters	Description	Required
SIZE_LIMIT = <num>	Number (> 0) that specifies the maximum rows of data to be loaded for a given COPY statement. Default 0	Optional

Examples

Loading Files from Internal Stage

First, create a named internal stage:

create stage my_internal_s1;

Then, PUT a local file to my_internal_s1 stage with PUT to Stage API:

curl  -H "stage_name:my_internal_s1" -F "upload=@books.parquet" -XPUT "http://localhost:8000/v1/upload_to_stage"

Final, copy the file into mytable from the my_internal_s1 named internal stage:

list @my_internal_s1;
copy into mytable from '@my_internal_s1' pattern = 'books.*parquet' file_format = (type = 'PARQUET');

Loading Files from External Stage

First, create a named external stage:

create stage my_external_s1 url = 's3://testbucket/admin/data/' credentials=(aws_key_id='minioadmin' aws_secret_key='minioadmin');

Then, copy the file into mytable from the my_external_s1 named external stage:

copy into mytable from '@my_external_s1' pattern = 'books.*parquet' file_format = (type = 'PARQUET');

Loading Files Directly from External Location

Amazon S3

Try to read 10 rows from csv and insert into the mytable.

mysql> copy into mytable
  from s3://mybucket/data.csv
  credentials=(aws_key_id='<AWS_ACCESS_KEY_ID>' aws_secret_key='<AWS_SECRET_ACCESS_KEY>')
  FILE_FORMAT = (type = "CSV" field_delimiter = ','  record_delimiter = '\n' skip_header = 1) size_limit=10;