# ColumnDataType
<a name="dqdl-rule-types-ColumnDataType"></a>

 Checks if the values in a given column can be cast in Apache Spark to the provided type. Accepts a `with threshold` expression to check for a subset of the values in the column. 

 **Syntax** 

```
ColumnDataType <COL_NAME> = <EXPECTED_TYPE>
```
+ **COL\$1NAME** – The name of the column that you want to evaluate the data quality rule against.

  Supported column types: String type

  **Supported column types**: Byte, Decimal, Double, Float, Integer, Long, Short
+ **EXPECTED\$1TYPE** – The expected type of the values in the column.

  Supported values: Boolean, Date, Timestamp, Integer, Double, Float, Long

  **Supported column types**: Byte, Decimal, Double, Float, Integer, Long, Short
+ **EXPRESSION** – An optional expression to specify the percentage of values that should be of the expected type.

  **Supported column types**: Byte, Decimal, Double, Float, Integer, Long, Short

 **Example: Column data type integers as strings** 

 The following example rule checks whether the values in the given column, which is of type string, can be cast as integers.

```
ColumnDataType "colA" = "INTEGER"
```

 **Example: Column data type integers as strings check for a subset of the values** 

 The following example rule checks whether more than 90% of the values in the given column, which is of type string, can be cast as integers. 

```
ColumnDataType "colA" = "INTEGER" with threshold > 0.9
```