Insert from CSV

This guide covers inserting data from CSV files into SQream DB using the COPY FROM method.

1. Prepare CSVs

Prepare the source CSVs, with the following requirements:

  • Files should be a valid CSV. By default, SQream DB’s CSV parser can handle RFC 4180 standard CSVs , but can also be modified to support non-standard CSVs (with multi-character delimiters, unquoted fields, etc).

  • Files are UTF-8 or ASCII encoded

  • Field delimiter is an ASCII character or characters

  • Record delimiter, also known as a new line separator, is a Unix-style newline (\n), DOS-style newline (\r\n), or Mac style newline (\r).

  • Fields are optionally enclosed by double-quotes, or mandatory quoted if they contain one of the following characters:

    • The record delimiter or field delimiter
    • A double quote character
    • A newline
  • If a field is quoted, any double quote that appears must be double-quoted (similar to the string literals quoting rules. For example, to encode What are "birds"?, the field should appear as "What are ""birds""?".

    Other modes of escaping are not supported (e.g. 1,"What are \"birds\"?" is not a valid way of escaping CSV values).

  • NULL values can be marked in two ways in the CSV:

    • An explicit null marker. For example, col1,\N,col3
    • An empty field delimited by the field delimiter. For example, col1,,col3


    If a text field is quoted but contains no content ("") it is considered an empty text field. It is not considered NULL.

2. Place CSVs where SQream DB workers can access

During data load, the COPY FROM command can run on any worker (unless explicitly speficied with the Workload Manager). It is important that every node has the same view of the storage being used - meaning, every SQream DB worker should have access to the files.

  • For files hosted on NFS, ensure that the mount is accessible from all servers.
  • For HDFS, ensure that SQream DB servers can access the HDFS name node with the correct user-id. See our Using SQream in an HDFS Environment guide for more information.
  • For S3, ensure network access to the S3 endpoint. See our Amazon S3 guide for more information.

3. Figure out the table structure

Prior to loading data, you will need to write out the table structure, so that it matches the file structure.

For example, to import the data from nba.csv, we will first look at the file:

Name Team Number Position Age Height Weight College Salary
Avery Bradley Boston Celtics 0.0 PG 25.0 6-2 180.0 Texas 7730337.0
Jae Crowder Boston Celtics 99.0 SF 25.0 6-6 235.0 Marquette 6796117.0
John Holland Boston Celtics 30.0 SG 27.0 6-5 205.0 Boston University  
R.J. Hunter Boston Celtics 28.0 SG 22.0 6-5 185.0 Georgia State 1148640.0
Jonas Jerebko Boston Celtics 8.0 PF 29.0 6-10 231.0   5000000.0
Amir Johnson Boston Celtics 90.0 PF 29.0 6-9 240.0   12000000.0
Jordan Mickey Boston Celtics 55.0 PF 21.0 6-8 235.0 LSU 1170960.0
Kelly Olynyk Boston Celtics 41.0 C 25.0 7-0 238.0 Gonzaga 2165160.0
Terry Rozier Boston Celtics 12.0 PG 22.0 6-2 190.0 Louisville 1824360.0
  • The file format in this case is CSV, and it is stored as an S3 object.
  • The first row of the file is a header containing column names.
  • The record delimiter was a DOS newline (\r\n).
  • The file is stored on S3, at s3://sqream-demo-data/nba.csv.

We will make note of the file structure to create a matching CREATE TABLE statement.

   Name varchar(40),
   Team varchar(40),
   Number tinyint,
   Position varchar(2),
   Age tinyint,
   Height varchar(4),
   Weight real,
   College varchar(40),
   Salary float

4. Bulk load the data with COPY FROM

The CSV is a standard CSV, but with two differences from SQream DB defaults:

  • The record delimiter is not a Unix newline (\n), but a Windows newline (\r\n)
  • The first row of the file is a header containing column names, which we’ll want to skip.
COPY nba
   FROM 's3://sqream-demo-data/nba.csv'
        OFFSET 2;

Repeat steps 3 and 4 for every CSV file you want to import.

Loading different types of CSV files

COPY FROM contains several configuration options. See more in the COPY FROM elements section.

Loading a standard CSV file from a local filesystem

COPY table_name FROM '/home/rhendricks/file.csv';

Loading a PSV (pipe separated value) file

COPY table_name FROM '/home/rhendricks/file.psv' WITH DELIMITER '|';

Loading a TSV (tab separated value) file

COPY table_name FROM '/home/rhendricks/file.tsv' WITH DELIMITER '\t';

Loading a text file with non-printable delimiter

In the file below, the separator is DC1, which is represented by ASCII 17 decimal or 021 octal.

COPY table_name FROM 'file.txt' WITH DELIMITER E'\021';

Loading a text file with multi-character delimiters

In the file below, the separator is '|.

COPY table_name FROM 'file.txt' WITH DELIMITER '''|';

Loading files with a header row

Use OFFSET to skip rows.


When loading multiple files (e.g. with wildcards), this setting affects each file separately.

COPY  table_name FROM 'filename.psv' WITH DELIMITER '|' OFFSET  2;

Loading files formatted for Windows (\r\n)

COPY table_name FROM 'filename.psv' WITH DELIMITER '|' RECORD DELIMITER '\r\n';

Loading a file from a public S3 bucket


The bucket must be publicly available and objects can be listed

COPY nba FROM 's3://sqream-demo-data/nba.csv' WITH OFFSET 2 RECORD DELIMITER '\r\n';

Loading files from an authenticated S3 bucket

COPY nba FROM 's3://secret-bucket/*.csv' WITH OFFSET 2 RECORD DELIMITER '\r\n' AWS_ID '12345678' AWS_SECRET 'super_secretive_secret';

Loading files from an HDFS storage

COPY nba FROM 'hdfs://*.csv' WITH OFFSET 2 RECORD DELIMITER '\r\n';

Saving rejected rows to a file

See Unsupported Field Delimiters for more information about the error handling capabilities of COPY FROM.

COPY  table_name FROM 'filename.psv'  WITH DELIMITER '|'
                                      ERROR_LOG  '/temp/load_error.log' -- Save error log
                                      ERROR_VERBOSITY 0; -- Only save rejected rows

Stopping the load if a certain amount of rows were rejected

COPY  table_name  FROM  'filename.csv'   WITH  delimiter  '|'
                                         ERROR_LOG  '/temp/load_err.log' -- Save error log
                                         OFFSET 2 -- skip header row
                                         LIMIT  100 -- Only load 100 rows
                                         STOP AFTER 5 ERRORS; -- Stop the load if 5 errors reached

Load CSV files from a set of directories

Use glob patterns (wildcards) to load multiple files to one table.

COPY table_name  from  '/path/to/files/2019_08_*/*.csv';

Rearrange destination columns

When the source of the files does not match the table structure, tell the COPY command what the order of columns should be

COPY table_name (fifth, first, third) FROM '/path/to/files/*.csv';


Any column not specified will revert to its default value or NULL value if nullable

Loading non-standard dates

If files contain dates not formatted as ISO8601, tell COPY how to parse the column. After parsing, the date will appear as ISO8601 inside SQream DB.

In this example, date_col1 and date_col2 in the table are non-standard. date_col3 is mentioned explicitly, but can be left out. Any column that is not specified is assumed to be ISO8601.

COPY table_name FROM '/path/to/files/*.csv' WITH PARSERS 'date_col1=YMD,date_col2=MDY,date_col3=default';


The full list of supported date formats can be found under the Supported date formats section of the COPY FROM reference.