COPY FROM

Imports data from a comma-separated values (CSV) file or a delimited text file into an existing table. Each line in the source file is imported as a row. All rows in the dataset must contain the same number of fields and have values in the PRIMARY KEY fields.

The process verifies the PRIMARY KEY and updates existing records. If HEADER = false and no column names are specified, the fields are imported in deterministic order. When HEADER = true, the first row of a file is a header row.

Only use COPY FROM to import datasets that have less than two million rows. To import large datasets, use sstableloader.

Synopsis

COPY table_name [ ( column_list ) ]
  FROM 'file_name'[ , 'file2_name', ... ] | STDIN
  [ WITH option = 'value' [ AND ... ] ]

COPY supports a list of one or more comma-separated file names or python glob expressions.

Syntax legend
Legend
Syntax conventions Description

UPPERCASE

Literal keyword.

Lowercase

Not literal.

< >

Variable value. Replace with a user-defined value.

[]

Optional. Square brackets ([]) surround optional command arguments. Do not type the square brackets.

( )

Group. Parentheses ( ( ) ) identify a group to choose from. Do not type the parentheses.

|

Or. A vertical bar (|) separates alternative elements. Type any one of the elements. Do not type the vertical bar.

...

Repeatable. An ellipsis ( ... ) indicates that you can repeat the syntax element as often as required.

'<Literal string>'

Single quotation (') marks must surround literal strings in CQL statements. Use single quotation marks to preserve upper case.

{ <key> : <value> }

Map collection. Braces ({ }) enclose map collections or key value pairs. A colon separates the key and the value.

<datatype2

Set, list, map, or tuple. Angle brackets ( < > ) enclose data types in a set, list, map, or tuple. Separate the data types with a comma.

<cql_statement>;

End CQL statement. A semicolon (;) terminates all CQL statements.

[--]

Separate the command line options from the command arguments with two hyphens ( -- ). This syntax is useful when arguments might be mistaken for command line options.

' <<schema\> ... </schema\>> '

Search CQL only: Single quotation marks (') surround an entire XML schema declaration.

@<xml_entity>='<xml_entity_type>'

Search CQL only: Identify the entity and literal value to overwrite the XML element in the schema and solrConfig files.

Setting copy options

Copy options set in the COPY statement take precedence over the cqlshrc file and the default settings. If an option is not set on the command line, the cqlshrc file takes precedence over the default settings.

<table_name>

Table for the copy operation.

<column_list>

List of columns in the table. All fields are included when no column names are specified. To omit columns, specify a column list with only the columns to include.

<file_name>, <file2_name>

CSV file name.

BOOLSTYLE

Boolean indicators for true and false. The values are case-insensitive. For example: yes,no and YES,NO are the same.

Default: True,False

CONFIGFILE

Directory that contains the cqlshrc configuration file.

Command line options always override the cqlshrc file.

DATETIMEFORMAT

Time format for reading or writing CSV time data. The timestamp uses the strftime format. If not set, the default value is set to the datetimeformat value in the cqlshrc file.

Default: %Y-%m-%d %H:%M:%S%z

DECIMALSEP

Decimal value separator.

Default: . (period)

DELIMITER

Field separator.

Default: , (comma)

ESCAPE

Single character that escapes literal uses of the QUOTE character.

Default: \ (backslash)

HEADER
  • true - first row contains headers (column names).

  • false - first row does not have headers. Default: false

MAXATTEMPTS

Maximum number of attempts for errors.

Default: 5

NULL

Value used when no value is in the field.

Default: <empty>

NUMPROCESSES

Number of worker processes. Maximum value is 16.

Default: -1

QUOTE

Encloses field values.

Default: " (double quotation mark)

REPORTFREQUENCY

Frequency with which status is displayed in seconds.

Default: 0.25

RATEFILE

Print output statistics to this file.

SKIPCOLS

Name of column to skip.

SKIPROWS

Number of rows starting from the first row of data to skip.

THOUSANDSSEP

Separator for thousands digit groups.

Default: None

CHUNKSIZE

Chunk size passed to worker processes.

Default: 1000

INGESTRATE

Approximate ingest rate in rows per second. Must be greater than the chunk size.

Default: 100000

MAXBATCHSIZE

Maximum size of an import batch.

Default: 20

MAXINSERTERRORS

Maximum global number of insert errors. Use -1 for no maximum.

Default: -1

MAXPARSEERRORS

Maximum global number of parsing errors. Use -1 for no maximum.

Default: -1

MAXROWS

Maximum number of rows. Use -1 for no maximum.

Default: -1

MINBATCHSIZE

Minimum size of an import batch.

Default: 2

Examples

Create the sample dataset

Set up the environment used for the COPY command examples:

  1. Using CQL, create a cycling keyspace:

    CREATE KEYSPACE cycling
    WITH REPLICATION = {
      'class' : 'NetworkTopologyStrategy',
      'datacenter1' : 1
    };
  2. Create the cycling.cyclist_name table:

    CREATE TABLE cycling.cyclist_name (
      id UUID PRIMARY KEY,
      lastname text,
      firstname text
    );
  3. Insert data into cycling.cyclist_name:

    INSERT INTO cycling.cyclist_name (id, lastname, firstname)
    VALUES (5b6962dd-3f90-4c93-8f61-eabfa4a803e2, 'VOS','Marianne');
    
    INSERT INTO cycling.cyclist_name (id, lastname, firstname)
    VALUES (e7cd5752-bc0d-4157-a80f-7523add8dbcd, 'VAN DER BREGGEN','Anna');
    
    INSERT INTO cycling.cyclist_name (id, lastname, firstname)
    VALUES (e7ae5cf3-d358-4d99-b900-85902fda9bb0, 'FRAME','Alex');
    
    INSERT INTO cycling.cyclist_name (id, lastname, firstname)
    VALUES (220844bf-4860-49d6-9a4b-6b5d3a79cbfb, 'TIRALONGO','Paolo');
    
    INSERT INTO cycling.cyclist_name (id, lastname, firstname)
    VALUES (6ab09bec-e68e-48d9-a5f8-97e6fb4c9b47, 'KRUIKSWIJK','Steven');
    
    INSERT INTO cycling.cyclist_name (id, lastname, firstname)
    VALUES (fb372533-eb95-4bb4-8685-6ef61e994caa, 'MATTHEWS', 'Michael');

Export and import data from the cyclist_name table

  1. Export only the id and lastname columns from the cyclist_name table to a CSV file:

    COPY cycling.cyclist_name (id,lastname)
    TO '../cyclist_lastname.csv' WITH HEADER = TRUE;

    The cyclist_lastname.csv file is created in the directory above the current working directory (indicated by ../). If the CSV file already exists, it is overwritten. If you do not have permission to create the file in the directory, you can use a different directory; for example, to use the current working directory, omit the directory path before the file name.

    Using 7 child processes
    
    Starting copy of cycling.cyclist_name with columns [id, lastname].
    Processed: 6 rows; Rate:      29 rows/s; Avg. rate:      29 rows/s
    6 rows exported to 1 files in 0.223 seconds.
  2. Copy the id and firstname to a different CSV file named cyclist_firstname.csv:

    COPY cycling.cyclist_name (id,firstname)
    TO '../cyclist_firstname.csv' WITH HEADER = TRUE;

    The CSV file is created:

    Using 7 child processes
    
    Starting copy of cycling.cyclist_name with columns [id, firstname].
    Processed: 6 rows; Rate:      30 rows/s; Avg. rate:      30 rows/s
    6 rows exported to 1 files in 0.213 seconds.
  3. Remove all records from the cyclist name table:

    TRUNCATE cycling.cyclist_name;
  4. Verify that there are no rows:

    SELECT *
    FROM cycling.cyclist_name;

    Query results are empty:

     id | firstname | lastname
    ----+-----------+----------
    
    (0 rows)
  5. Import the cyclist first names:

    COPY cycling.cyclist_name (id,firstname)
    FROM '../cyclist_firstname.csv' WITH HEADER = TRUE;

    The rows are imported:

    Using 7 child processes
    
    Starting copy of cycling.cyclist_name with columns [id, firstname].
    Processed: 6 rows; Rate:      10 rows/s; Avg. rate:      14 rows/s
    6 rows imported from 1 files in 0.423 seconds (0 skipped).
  6. Verify the new rows:

    SELECT *
    FROM cycling.cyclist_name;

    The rows were created with null last names because the lastname field was not in the imported data set:

     id                                   | firstname | lastname
    --------------------------------------+-----------+----------
     e7ae5cf3-d358-4d99-b900-85902fda9bb0 |      Alex |     null
     fb372533-eb95-4bb4-8685-6ef61e994caa |   Michael |     null
     5b6962dd-3f90-4c93-8f61-eabfa4a803e2 |  Marianne |     null
     220844bf-4860-49d6-9a4b-6b5d3a79cbfb |     Paolo |     null
     6ab09bec-e68e-48d9-a5f8-97e6fb4c9b47 |    Steven |     null
     e7cd5752-bc0d-4157-a80f-7523add8dbcd |      Anna |     null
    
    (6 rows)
  7. Import the last names:

    COPY cycling.cyclist_name (id,lastname)
    FROM '../cyclist_lastname.csv' WITH HEADER = TRUE;

    The records are imported but no new records are created:

    Using 7 child processes
    
    Starting copy of cycling.cyclist_name with columns [id, lastname].
    Processed: 6 rows; Rate:      10 rows/s; Avg. rate:      14 rows/s
    6 rows imported from 1 files in 0.422 seconds (0 skipped).
  8. Verify the that the records were updated:

    SELECT *
    FROM cycling.cyclist_name;

    The PRIMARY KEY id matched for all records and the lastname is populated.:

     id                                   | firstname | lastname
    --------------------------------------+-----------+-----------------
     e7ae5cf3-d358-4d99-b900-85902fda9bb0 |      Alex |           FRAME
     fb372533-eb95-4bb4-8685-6ef61e994caa |   Michael |        MATTHEWS
     5b6962dd-3f90-4c93-8f61-eabfa4a803e2 |  Marianne |             VOS
     220844bf-4860-49d6-9a4b-6b5d3a79cbfb |     Paolo |       TIRALONGO
     6ab09bec-e68e-48d9-a5f8-97e6fb4c9b47 |    Steven |      KRUIKSWIJK
     e7cd5752-bc0d-4157-a80f-7523add8dbcd |      Anna | VAN DER BREGGEN

Copy data from standard input to a table.

  1. Clear the data from the cyclist_name table:

    TRUNCATE cycling.cyclist_name;
  2. Start the copy input operation using the FROM STDIN option:

    COPY cycling.cyclist_name FROM STDIN;

    The line prompt changes to [copy]:

    Using 7 child processes
    
    Starting copy of cycling.cyclist_name with columns [id, firstname, lastname].
    [Use . on a line by itself to end input]
    [copy]
  3. Next to the [copy] prompt, enter the field values in a common-separated list; on the last line of data, enter a period:

    [copy] e7cd5752-bc0d-4157-a80f-7523add8dbcd,Anna,VAN DER BREGGEN
    [copy] .
  4. Press Enter after the period:

    Processed: 1 rows; Rate:       0 rows/s; Avg. rate:       0 rows/s
    1 rows imported from 1 files in 36.991 seconds (0 skipped).
  5. Run this query to view the contents of the cyclist_name table:

    SELECT *
    FROM cycling.cyclist_name;
     id                                   | firstname | lastname
    --------------------------------------+-----------+-----------------
     e7cd5752-bc0d-4157-a80f-7523add8dbcd |      Anna | VAN DER BREGGEN
    
    (1 rows)

Copy to and from a table with a vector data type

To copy data from a table with a vector data type to a CSV file, use the following command:

COPY cycling.comments_vs (record_id,id,commenter,comment,created_at,comment_vector) 
  TO '../CSV/comments-vs-new.csv' WITH HEADER=TRUE;

To copy data from a CSV file to a table with a vector data type, use the following command:

COPY cycling.comments_vs (record_id,id,commenter,comment,created_at,comment_vector) 
  FROM '../CSV/comments-vs.csv' WITH HEADER=TRUE AND DELIMITER='|';

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