By utilizing the aggregation and grouping features, you can establish groups within the Result Matrix and subsequently perform aggregation operations on these groups, such as SUM, COUNT, etc.
Supported Aggregations
AVG
COUNT
MAX
MIN
SUM
Definition
def groupByData = api.newMatrix()
// Definition of result matrix (columns, rows).
.withColumns('TextColumn1', 'TextColumn2', 'NumericColumn3', 'NumericColumn4')
.withRows(rows)
// Property `.withGroupBy` defines that the `TextColumn1` and `NumericColumn3` are used for group by (The order is important).
.withGroupBy(['TextColumn1', 'NumericColumn3'])
// Property `.withColumnAggregation` defines the values for subtotal rows that will be calculated as SUM.
// Values are based on the group by definition (`NumericColumn3`). This definition is optional.
// When not used, like e.g. for `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()
Static import is required to use a predefined enum with aggregation types.
import static net.pricefx.server.dto.calculation.ResultMatrixGrouping.AggregateFunctionType import static net.pricefx.server.dto.calculation.ResultMatrixGrouping.AggregateFunctionType.AVG import static net.pricefx.server.dto.calculation.ResultMatrixGrouping.AggregateFunctionType.COUNT import static net.pricefx.server.dto.calculation.ResultMatrixGrouping.AggregateFunctionType.MAX import static net.pricefx.server.dto.calculation.ResultMatrixGrouping.AggregateFunctionType.MIN
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
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
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 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
