Sorting

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Demo

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Description

Sorting on the client side is really easy, you simply need to enable sortable (when not provided, it is considered as disabled) on each columns you want to sort and it will sort as a type string. Oh but wait, sorting as string might not always be ideal, what if we want to sort by number or by date? The answer is to simply pass a type as shown below.

Usage

To use any of them, you can use the FieldType interface or enter a type via a string as shown below. Also please note that FieldType.string is the default and you don't necessarily need to define it, though you could if you wish to see it in your column definition.

import { FieldType } from 'aurelia-slickgrid';

export class Example {
  columnDefinitions: Column[];
  gridOptions: GridOption;
  dataset: any[];

  constructor() {
    // define the grid options & columns and then create the grid itself
    this.defineGrid();
  }

  defineGrid() {
    this.columnDefinitions = [
      { id: 'title', name: 'Title', field: 'title', sortable: true },
      { id: 'duration', name: 'Duration (days)', field: 'duration', sortable: true, type: FieldType.number },
      { id: '%', name: '% Complete', field: 'percentComplete', sortable: true, type: FieldType.float},
      { id: 'start', name: 'Start', field: 'start', sortable: true, type: FieldType.dateIso },
      { id: 'finish', name: 'Finish', field: 'finish', sortable: true, type: FieldType.dateIso },
      { id: 'effort-driven', name: 'Effort Driven', field: 'effortDriven', sortable: true }
    ];
  }
}

How to Sort Complex Objects?

You can sort complex objects using the dot (.) notation inside the field property defined in your Columns Definition.

For example, let say that we have this dataset

const dataset = [
 { item: 'HP Desktop', buyer: { id: 1234, address: { street: '123 Belleville', zip: 123456 }} },
 { item: 'Lenovo Mouse', buyer: { id: 456, address: { street: '456 Hollywood blvd', zip: 789123 }} }
];

We can now filter the zip code from the buyer's address using this filter:

this.columnDefinitions = [
  {
    // the zip is a property of a complex object which is under the "buyer" property
    // it will use the "field" property to explode (from "." notation) and find the child value
    id: 'zip', name: 'Zip Code', field: 'buyer.address.zip', sortable: true
  }
  // { id: 'street',  ... },
];

Custom Sort Comparer

If the builtin sort comparer methods are not sufficient for your use case, you could add your own custom Sort Comparer in your Column Definitions as shown below. Note that we are only showing a simple numeric sort, just adjust it to your needs.

this.columnDefinitions = [{
  id: 'myField', name: 'My Field',
  sorter: (a, b) => a > b ? 1 : -1,
}];

similarly with a complex object

// data = { user: { firstName: 'John', lastName: 'Doe', fullName: 'John Doe' }, address: { zip: 123456 } }};

this.columnDefinitions = [{
  id: 'firstName', name: 'First Name', field: 'user.firstName',
  sorter: (a, b) => a.fullName > b.fullName ? 1 : -1,
}];

Update Sorting Dynamically

You can update/change the Sorting dynamically (on the fly) via the updateSorting method from the SortService. Note that calling this method will override all sorting (sorters) and replace them with the new array of sorters provided. For example, you could update the sorting from a button click or a select dropdown list with predefined filter set.

View

<button class="btn btn-default btn-sm" data-test="set-dynamic-sorting" click.trigger="setSortingDynamically()">
    Set Sorting Dynamically
</button>

<aurelia-slickgrid grid-id="grid1"
   columnDefinitions.bind="columnDefinitions"
   gridOptions.bind="gridOptions"
   dataset.bind="dataset"
   on-aurelia-grid-created.trigger="aureliaGridReady($event.detail)">
</aurelia-slickgrid>

Component

export class Example {
  aureliaGrid: AureliaGridInstance;

  aureliaGridReady(aureliaGrid: AureliaGridInstance) {
    this.aureliaGrid = aureliaGrid;
  }

  setSortingDynamically() {
    this.aureliaGrid.sortService.updateSorting([
      // orders matter, whichever is first in array will be the first sorted column
      { columnId: 'duration', direction: 'ASC' },
      { columnId: 'start', direction: 'DESC' },
    ]);
  }
}

Extra Arguments

The updateSorting method has 2 extra arguments:

  • 2nd argument, defaults to true, is to emit a sort changed event (the GridStateService uses this event)

    • optional and defaults to true updateSorting([], true)

  • 3rd argument is to trigger a backend query (when using a Backend Service like OData/GraphQL), this could be useful when using updateFilters & updateSorting and you wish to only send the backend query once.

    • optional and defaults to true updateSorting([], true, true)

Dynamic Query Field

What if you a field that you only know which field to query only at run time and depending on the item object (dataContext)? We can defined a queryFieldNameGetterFn callback that will be executed on each row when Filtering and/or Sorting.

queryFieldNameGetterFn: (dataContext) => {
  // do your logic and return the field name will be queried
  // for example let say that we query "profitRatio" when we have a profit else we query "lossRatio"
  return dataContext.profit > 0 ? 'profitRatio' : 'lossRatio';
},

Pre-Parse Date Columns for better perf

requires v8.8.0 and higher

Sorting very large dataset with dates can be extremely slow when dates formated date strings, the reason is because these strings need to first be parsed and converted to real JS Dates before the Sorting process can actually happen (i.e. US Date Format). However parsing a large dataset can be slow and to make it worst, a Sort will revisit the same items over and over which mean that the same date strings will have to be reparsed over and over (for example while trying to Sort a dataset of 100 items, I saw some items being revisit 10 times and I can only imagine that it is exponentially worst with a large dataset).

So what can we do to make this faster with a more reasonable time? Well, we can simply pre-parse all date strings once and only once and convert them to JS Date objects. Then once we get Date objects, we'll simply read the UNIX timestamp which is what we need to Sort. The first pre-parse takes a bit of time and will be executed only on the first date column Sort (any sort afterward will read the pre-parsed Date objects).

What perf do we get with pre-parsing versus regular non-parsing? The benchmark was pulled using 50K items with 2 date columns (with US date format)

  • without non-parsing: ~15sec

  • with pre-parsing: ~1.4sec (1st pre-parse) and any subsequent Date sort is about ~0.2sec => so about ~1.5sec total

The summary, is that we get a 10x boost but not only that, we also get an extremely fast subsequent sort afterward (sorting Date objects is as fast as sorting Numbers).

Usage

You can use the preParseDateColumns grid option, it can be either set as either boolean or a string but there's big distinction between the 2 approaches (both approaches will mutate the dataset).

  1. string (i.e. set to "__", it will parse a "start" date string and assign it as a Date object to a new "__start" prop)

  2. boolean (i.e. parse "start" date string and reassign it as a Date object on the same "start" prop)

Note this option does not work with Backend Services because it simply has no effect.

For example if our dataset has 2 columns named "start" and "finish", then pre-parse the dataset,

with the 1nd approach (string), let's use "__" (which is in reality a prefix) it will mutate the dataset by adding new props (where Date is a Date object)

data = [
-  { id: 0, start: '02/28/24', finish: '03/02/24' },
-  { id: 1, start: '01/14/24', finish: '02/13/24' },
+  { id: 0, start: '02/28/24', finish: '03/02/24', __start: Date, __finish: Date },
+  { id: 1, start: '01/14/24', finish: '02/13/24', __start: Date, __finish: Date },
]

with the 2nd approach (boolean), it will instead mutate the dataset by overwriting the same properties

data = [
-  { id: 0, start: '02/28/24', finish: '03/02/24' },
-  { id: 1, start: '01/14/24', finish: '02/13/24' },
+  { id: 0, start: Date, finish: Date },
+  { id: 1, start: Date, finish: Date },
]

Which approach to choose? Both have pros and cons, overwriting the same props might cause problems with the column type that you use, you will have to give it a try yoursel. On the other hand, with the other approach, it will duplicate all date properties and take a bit more memory usage and when changing cells we'll need to make sure to keep these props in sync, however you will likely have less type issues.

What happens when we do any cell changes (for our use case, it would be Create/Update), for any Editors we simply subscribe to the onCellChange change event and we re-parse the date strings when detected. We also subscribe to certain CRUD functions as long as they come from the GridService then all is fine... However, if you use the DataView functions directly then we have no way of knowing when to parse because these functions from the DataView don't have any events. Lastly, if we overwrite the entire dataset, we will also detect this (via an internal flag) and the next time you sort a date then the pre-parse kicks in again.

Can I call the pre-parse myself?

Yes, if for example you want to pre-parse right after the grid is loaded, you could call the pre-parse yourself for either all items or a single item

  • all item pre-parsing: this.sgb.sortService.preParseAllDateItems();

    • the items will be read directly from the DataView

  • a single item parsing: this.sgb.sortService.preParseSingleDateItem(item);

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