Issues when loading data in Snowflake and Amazon Redshift

Column type 'VALUE' is not recognized

Example: Timestamp 'WEB' is not recognized.

The order of columns in the file is not matching the order of columns in the table

This is most likely caused by the incorrect order of fields in the file to load.

Solution: enable "Reorder columns to load to match the order of columns in the target table." under Mapping/Parameters/Handling schema changes.

The data type of the column in the file is not matching the data type of the column in the table

If the table in the Snowflake is created by the flow it is possible that the flow will create a column with the wrong data type. If that happened the Snowflake COPY INTO command could fail when attempting to load data. For example, if the data column contains the alphanumeric values and the column in the table is NUMBER the COPY INTO command will fail with the "Column type is not recognized" error.

To make sure that the tables in the Snowflake are created with the correct data types enable the Save metadata parameter for the CSV format used in the Snowflake flow.

The other option is to enable All fields are strings in which case all columns in the Snowflake tables created by the flow will have a TEXT data type. 

End of the record reached while expected to parse column "COLUMN NAME"

This is most likely caused by the presence of special characters in the data which prevents Snowflake or Redshift from parsing the generated CSV file.

To fix, modify the CSV format as following:

1. Set "Enclosure Character" to "

2. Enable "Always Enclose"

3. Enable "Escape double-quotes"