By utilizing the aggregation and grouping features, you can establish groups within the Result Matrix and subsequently perform aggregation operations on these groups. Such , such as SUM, COUNT, etc.
| Table of Contents | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Supported Aggregations
AVG
COUNT
MAX
MIN
SUM
...
| Code Block | ||
|---|---|---|
| ||
def groupByData = api.newMatrix()
// Definition of result matrix (columns, rows).
.withColumns('TextColumn1', 'TextColumn2', 'NumericColumn3', 'NumericColumn4')
.withRows(entriesrows)
// Property `.withGroupBy` defines that the `TextColumn1` and `NumericColumn3` are used for group by (The order is important).
.withGroupBy(['TextColumn1', 'NumericColumn3'])
// Property `.withColumnAggregation` defines that the values for subtotal rows that will be calculated as SUM.
// Values are based on the group by definition (`NumericColumn3`) and are to be calculated as SUM. This definition is optional.. This definition is optional.
// When not used, like e.g. for TextColumn1`TextColumn1`, there will be no aggregation calculated for the `TextColumn1`.
.withColumnAggregation('NumericColumn3', SUM)
// Property `.calculateGroupByData` is an end statement for group definition.
// This statement is only used together with `.withColumnAggregation`.
.calculateGroupByData() |
Description
...
Definition of result matrix (columns, rows).
...
Property .withGroupBy defines that the TextColumn1 and NumericColumn3 are used for group by (The order is important).
...
( |
...
) |
...
| Info | |||||
|---|---|---|---|---|---|
Static import is required to use a predefined enum with aggregation types.
|
Examples
Grouping Example
In the following example, we retrieve the data from the Products table and group them by the Business Unit, Product Group, and Size columns.
Code
| Code Block | ||
|---|---|---|
| ||
import net.pricefx.common.api.FieldFormatType
def productList = null
List<String> fields = ["ProductId", "label", "ProductGroup", "currency", "BusinessUnit", "ProductClass", "Size", "ProductLifeCycle" ]
productList = api.find("P", 0, api.getMaxFindResultsLimit(), "ProductId", fields)
def columnFormats = [
"ProductId": FieldFormatType.TEXT,
"label": FieldFormatType.TEXT,
"ProductGroup": FieldFormatType.TEXT,
"currency": FieldFormatType.MONEY_EUR,
"BusinessUnit": FieldFormatType.TEXT,
"ProductClass": FieldFormatType.TEXT,
"Size": FieldFormatType.TEXT,
"ProductLifeCycle": FieldFormatType.TEXT,
]
def rows = productList
def resultMatrix = api.newMatrix()
.withColumnFormats(columnFormats)
.withRows(rows)
.withGroupBy(['BusinessUnit'])
.withGroupBy(['ProductGroup'])
.withGroupBy(['Size'])
return resultMatrix |
Result
...
Aggregation Example
In the following example, we retrieve the data from the Product Extensions table. We apply group by Currency column and then aggregate SUM on ListPrice column.
Code
| Code Block | ||
|---|---|---|
| ||
import net.pricefx.common.api.FieldFormatType
import static net.pricefx.server.dto.calculation.ResultMatrixGrouping.AggregateFunctionType
import static net.pricefx.server.dto.calculation.ResultMatrixGrouping.AggregateFunctionType.SUM
def listPriceItems = null
def filter = [
Filter.equal("name", "ListPrice"),
]
List<String> fields = ["ProductId", "ListPrice", "Currency"]
def listPriceItems = api.find("PX3", 0, api.getMaxFindResultsLimit(), "ProductId", fields, *filter)
def rows = listPriceItems
def columnFormats = [
"ProductId": FieldFormatType.TEXT,
"ListPrice": FieldFormatType.MONEY,
"Currency" : FieldFormatType.MONEY,
]
def resultMatrix = api.newMatrix()
.withEnableClientFilter(true)
.withColumnFormats(columnFormats)
.withRows(rows)
.withGroupBy(['Currency'])
.withColumnAggregation('ListPrice', SUM)
.calculateGroupByData()
return resultMatrix |
Result
...