GdcCsvParser Options
CloudConnect is a legacy tool and will be discontinued. We recommend that to prepare your data you use the GoodData data pipeline as described in Data Preparation and Distribution. For data modeling, see Data Modeling in GoodData to learn how to work with Logical Data Modeler.
GdcCsvParser accepts the following parameters:
| Parameter Name | Type | Default | Definition |
|---|---|---|---|
| ENCLOSED BY | single character | " | A character used to quote individual columns. Can be any character, but typically is a single or double quotation mark. |
| ESCAPE | single character | \ | A character used to escape special characters in quoted columns. If a column is not quoted, is interpreted as a regular (non-special) character and does not escape special characters. |
| RECORD TERMINATOR | single character | \n | A character ending a row. If found inside a quoted column value, is interpreted as a regular (non-special) character. |
| DELIMITER | single character | , | A character ending a column. If found inside a quoted column value, is interpreted as a regular (non-special) character. |
| NULL | string | empty string | A string marking a column value as NULL. Can be specified globally and per column. When specified per column, overrides the global setting for the corresponding column. NOTE: A quoted column of a string type (CHAR, VARCHAR) can never be NULL. |
| SKIP | integer | 0 | The number of rows at the beginning of a data file to be skipped. Typically, is set to 0 (skip none) or 1 (skip the header). |
| FORMAT | string | empty string | The format of a column of date/time types. If not specified, the parser tries to extract as much meaningful data from the value as possible. For more information, see the Vertica online documentation. |
| TRAILING NULLCOLS | Boolean | false | Specifies whether to convert missing columns at the end of a line to NULL (true) or reject them (false; default). If set to true and NULL is not allowed, an error is thrown. |
For information about other Data Warehouse parsers, see Choose a Data Warehouse Parser.