The CSVReader Controller Service, expects input in such a way that the first line of a FlowFile specifies the name of each column in the data. Following the first line, the rest of the FlowFile is expected to be valid CSV data from which to form appropriate Records. The reader allows for customization of the CSV Format, such as which character should be used to separate CSV fields, which character should be used for quoting and when to quote fields, which character should denote a comment, etc.
When a record is parsed from incoming data, it is separated into fields. Each of these fields is then looked up against the configured schema (by field name) in order to determine what the type of the data should be. If the field is not present in the schema, that field is omitted from the Record. If the field is found in the schema, the data type of the received data is compared against the data type specified in the schema. If the types match, the value of that field is used as-is. If the schema indicates that the field should be of a different type, then the Controller Service will attempt to coerce the data into the type specified by the schema. If the field cannot be coerced into the specified type, an Exception will be thrown.
The following rules apply when attempting to coerce a field value from one data type to another:
8 can be coerced into any numeric type. However, the String value 8.2 can be coerced into a Double or Float
type but not an Integer.If none of the above rules apply when attempting to coerce a value from one data type to another, the coercion will fail and an Exception will be thrown.
As an example, consider a FlowFile whose contents consists of the following:
id, name, balance, join_date, notes
1, John, 48.23, 04/03/2007 "Our very
first customer!"
2, Jane, 1245.89, 08/22/2009,
3, Frank Franklin, "48481.29", 04/04/2016,
Additionally, let's consider that this Controller Service is configured with the Schema Registry pointing to an AvroSchemaRegistry and the schema is configured as the following:
{
"namespace": "nifi",
"name": "balances",
"type": "record",
"fields": [
{ "name": "id", "type": "int" },
{ "name": "name": "type": "string" },
{ "name": "balance": "type": "double" },
{ "name": "join_date", "type": {
"type": "int",
"logicalType": "date"
},
{ "name": "notes": "type": "string" }
]
}
In the example above, we see that the 'join_date' column is a Date type. In order for the CSV Reader to be able to properly parse a value as a date,
we need to provide the reader with the date format to use. In this example, we would configure the Date Format property to be MM/dd/yyyy
to indicate that it is a two-digit month, followed by a two-digit day, followed by a four-digit year - each separated by a slash.
In this case, the result will be that this FlowFile consists of 3 different records. The first record will contain the following values:
| Field Name | Field Value |
|---|---|
| id | 1 |
| name | John |
| balance | 48.23 |
| join_date | 04/03/2007 |
| notes | Our very first customer! |
The second record will contain the following values:
| Field Name | Field Value |
|---|---|
| id | 2 |
| name | Jane |
| balance | 1245.89 |
| join_date | 08/22/2009 |
| notes |
The third record will contain the following values:
| Field Name | Field Value |
|---|---|
| id | 3 |
| name | Frank Franklin |
| balance | 48481.29 |
| join_date | 04/04/2016 |
| notes |