By utilizing the aggregation and grouping features, you can establish groups within the Result Matrix and perform aggregation operations on these groups, such as SUM, COUNT, etc.
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Supported Aggregations
Definition
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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 `TextColumn1`.
.withColumnAggregation('NumericColumn3', SUM)
// Property `.calculateGroupByData` is an end statement for group definition.
// This statement is only used together with `.withColumnAggregation`.
.calculateGroupByData() |
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Static import is required to use a predefined enum with aggregation types. | Code Block |
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| 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 |
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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
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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
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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
