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When configured for local binding, the PivotGridV2 for ASP.NET Core will serialize the data as part of its data source and will perform all data operations on the client.

To bind the PivotGridV2 for ASP.NET Core to local flat data:

  1. Define a model class or use an existing one from your application.

    public class ProductViewModel
    {
        [ScaffoldColumn(false)]
        public int ProductID
        {
            get;
            set;
        }
    
        [Required]
        [Display(Name = "Product name")]
        public string ProductName
        {
            get;
            set;
        }
    
        [Display(Name = "Unit price")]
        [DataType(DataType.Currency)]
        [Range(0, int.MaxValue)]
        public decimal UnitPrice
        {
            get;
            set;
        }
    
        [Display(Name = "Units in stock")]
        [DataType("Integer")]
        [Range(0, int.MaxValue)]
        public int UnitsInStock
        {
            get;
            set;
        }
    
        public bool Discontinued
        {
            get;
            set;
        }
    
        [Display(Name = "Last supply")]
        [DataType(DataType.Date)]
        public DateTime LastSupply
        {
            get;
            set;
        }
    
        [DataType("Integer")]
        public int UnitsOnOrder
        {
            get;
            set;
        }
    
        [UIHint("ClientCategory")]
        public CategoryViewModel Category
        {
            get;
            set;
        }
    
        public int? CategoryID { get; set; }
    
        public string QuantityPerUnit { get; set; }
    }
    
  2. In the Index action return an IEnumerable of the model type with the view.

    public ActionResult Index()
    {
        var entities = new SampleEntities();
    
        var result = entities.Products.Select(product => new ProductViewModel
        {
            ProductID = product.ProductID,
            ProductName = product.ProductName,
            UnitPrice = product.UnitPrice.HasValue ? product.UnitPrice.Value : default(decimal),
            UnitsInStock = product.UnitsInStock.HasValue ? product.UnitsInStock.Value : default(short),
            QuantityPerUnit = product.QuantityPerUnit,
            Discontinued = product.Discontinued,
            UnitsOnOrder = product.UnitsOnOrder.HasValue ? (int)product.UnitsOnOrder.Value : default(int),
            CategoryID = product.CategoryID,
            Category = new CategoryViewModel()
            {
                CategoryID = product.Category.CategoryID,
                CategoryName = product.Category.CategoryName
            },
            LastSupply = DateTime.Today
        }).ToList();
    
        return View(result);
    }
    
  3. In the Index.cshtml view declare the model, an IEnumerable of the model type. Declare and configure the PivotGridV2.

        @model IEnumerable<MyApplication.Models.ProductViewModel>
    
        @(Html.Kendo().PivotContainer()
        .Name("container")
        .ConfiguratorPosition("left")
        .Content(@<text>
            @(Html.Kendo().PivotConfiguratorV2()
                .Name("configurator")
                .Sortable()
                .Filterable())
    
            @(Html.Kendo().PivotGridV2<Kendo.Mvc.Examples.Models.ProductViewModel>()
                .Name("pivotgrid")
                .HtmlAttributes(new { @class = "hidden-on-narrow" })
                .Configurator("#configurator")
                .ColumnWidth(120)
                .Height(570)
                .BindTo(Model)
                .DataSource(dataSource => dataSource
                    .Custom()
                    .Schema(schema => schema
                        .Model(m => m.Field("CategoryName", typeof(string)).From("Category.CategoryName"))
                        .Cube(cube => cube
                            .Dimensions(dimensions =>
                            {
                                dimensions.Add(model => model.ProductName).Caption("All Products");
                                dimensions.Add("CategoryName").Caption("All Categories");
                                dimensions.Add(model => model.Discontinued).Caption("Discontinued");
                            })
                            .Measures(measures =>
                            {
                                measures.Add("Average").Format("{0:c}").Field(model => model.UnitPrice).AggregateName("average");
                                measures.Add("Sum").Format("{0:c}").Field(model => model.UnitPrice).AggregateName("sum");
                            })
                        ))
                    .Columns(columns =>
                    {
                        columns.Add("CategoryName").Expand(true);
                        columns.Add("ProductName");
                    })
                    .Rows(rows => rows.Add("Discontinued").Expand(true))
                    .Measures(measures => measures.Values("Sum"))
                    .Events(e => e.Error("onError"))
                )
            )
    
            @(Html.Kendo().PivotConfiguratorButton()
                .Name("Button")
                .Configurator("configurator")
            )
    
        </text>))
    
        <script>
            function onError(e) {
                alert("error: " + kendo.stringify(e.errors[0]));
            }
        </script>
    

For a full example, refer to the PivotGridV2 Local Binding demo.

Known Limitations

When the PivotGridV2 is bound to a flat data structure, the component processes the data on the client (browser) and creates a client cube representation (configuration). The PivotGridV2 relies on the processing power of the browser to project the data and produce the required categorized data output. The PivotGridV2 does not restrict the maximum amount of data that you can load into it, but there are limitations related to the browser's capability to handle the loaded dataset.

The symptoms for an overloaded browser are:

  • The browser is loading extremely slowly or gets unresponsive for a long time.
  • The browser is crashing when loading or updating the dimensions/measures.

If you observe any of these symptoms, this means you have hit the processing limit of the browser. To work around this issue, use a dedicated OLAP solution like Microsoft SSAS.

See Also

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