ARRAY data type

This article describes the specifics of the ARRAY complex data type.

Syntax for ARRAY

column_name ARRAY < type >
type ::= primitive_type | complex_type

ARRAY data types represent collections with arbitrary numbers of elements, where each element is the same type. An ARRAY type is like a miniature table, with two columns:


Position of element in the array

Access as array_name.pos


Value of array element that may be a scalar, or another complex type (another ARRAY, a STRUCT, or a MAP)

Access as array_name.item

If an array contains a STRUCT, access as array_name.item.field_name, or as array_name.field_name

Arrays in the Dataset Field interface

In the Dataset Fields interface, an example of a basic ARRAY data type may look like the following example. You can see that each level of a complex data type may be expanded to show component details, or collapsed for simplicity.

In the example of the dataset Complex Sales Table, you can see that the Dimensions Customer Name and the derived Truncated Customer Name are primitive types (both are Strings, marked with the symbol A), along with the Measures Orderid (Integer, marked with the symbol #) and Overalldiscount (Real, marked with the symbol 1.2). However, the Dimensions Category, Product, Amount, Qty and Orderitemid are all Array data types, symbolized by [A].

When we click Edit Fields, you can see that while primitive types can be cast as alternate data types (such as Integer into Real), the complex data type Array cannot be changed to another type. However, the primitive components of the array may be cast as other primitive data types. Additionally, unlike other data types, Cloudera Data Visualization uses complex datatypes only as Dimensions. They or their components cannot be redefined as Measurements of the dataset.

Arrays in visuals

When building a visual with complex data, you cannot use the complex type directly, as a whole. However, you can add the primitive components of the complex type to the shelves of the visual.

For example, in a Bars visual you might place Customer Name on the X Axis shelf, the Amount:Item component on the Y Axis shelf, and grouped on the Colors shelf by Product:Item component.

Changing field properties

It is very simple to change field properties for a component of a complex data type.

For example, you can change the Product:Item component on the Tooltips shelf from the default max() aggregation to the count() function.

Arrays in Expression Editor

The expression editor fully supports the use of Arrays, both in the Dataset and the Visual interfaces. This enables advanced data manipulation and customization, leveraging the capabilities of ARRAY data type in your data visualization tasks.