Asynchronous data providing

The ListView in Cascades can display large amounts of data while still maintaining good performance. To achieve this performance, only a small subset of list items is held in memory at any given time (the items that are currently within the visible area and a handful above and below). Whether a ListView has ten items or 2000 items in its DataModel, it has the same performance.

When a user scrolls the list, the ListView requests new data from the DataModel in the direction that the list is scrolling. Instead of creating new list items for the data, the ListView reuses list items that have been scrolled out of the visible area of the screen.

Diagram showing scrolling in a list view.

For the list to perform well, it needs to be able to retrieve and process new data quickly. Here are some of the functions that are called while a ListView is scrolling:


Creates a VisualNode for each visible list item when the ListView is initialized.


Updates the list item based on the provided type, index path, and data. This function is called whenever a new item is going to be displayed in the list. Whether or not this function returns quickly enough doesn't affect the performance of the list, but it does affect whether the correct data is displayed in the list item.


Returns the number of children of a list item specified by an indexPath. This value is used by the ListView to display a scroll bar that's an appropriate size for the list. This function is always called if you implement your own DataModel.


Returns the item type of the list item, based on the data that it contains. This function is only called if a ListItemTypeMapper is registered on the ListView.

For the list to be able to scroll quickly and load data right away, you must ensure that your DataModel is ready to respond immediately to the calls mentioned above. You should create your DataModel so that it acts as a cache that pre-fetches data asynchronously so that data that is always available to the ListView. Asynchronous database requests are handled using the SqlConnection class.

If you are working with large amounts of data, the AsyncDataModel class provides a caching mechanism to manage data loading and ensure smooth scrolling in a list. For more information, see Working with large amounts of data.

Asynchronous data providing for lists

Depending on your app, there are a few different ways that you might want to construct your DataModel. Here are two possible approaches that you can use.

Approach #1

In the first approach, the DataModel only reports the items already loaded into its internal data structure (the amount of data in the DataModel is specified by DataModel::childCount()). When the list gets closer to the end of this internal data structure, you can add more items to the edge of the internal data structure in the direction the list is being scrolled. When new items are added to the model's internal data structure, it emits the itemAdded() signal. When the internal data structure of the DataModel gets too large, you can remove items from the side of the data structure in the opposite direction that the user is scrolling. When items are removed, the model emits the itemRemoved() signal.

The advantage of this approach is that the list stops scrolling when there aren't any items loaded in the cache, allowing you to show an ActivityIndicator at the bottom of the list. The drawback to this approach is that the scroll bar for the list jumps when new items are added and removed. The approach is mostly suited for online data since this type of scroll bar behavior is normal in those cases.

Approach #2

In the second approach, list items are never fully removed from the internal structure of the DataModel when it gets too large. Even though the data itself is thrown away, the DataModel always retains the database ID of the items so that a list item's indexPath in the model always corresponds to an item in the database. One of the benefits of this approach is that the scroll bar always appears at an accurate position in the list. One of the drawbacks is that some list items might not display their data initially when loading doesn't happen quickly enough.

Here are the steps for how to populate the model using this approach.

  1. First, you create the ListView with an empty DataModel and optionally start an ActivityIndicator so that the user knows that the app is working.
  2. Next, you load a small set of data from the data source and store it in the internal data structure of the DataModel.
  3. When the initial set of data loads, you asynchronously load a larger set of data.
  4. With the initial set of data in place, the DataModel reports on the number of items in its internal data structure to the ListView using DataModel::childCount().
  5. While the list is scrolling, the ListView calls ListItemProvider::updateItem() to update list items with data before they are displayed. If the index path of the list item is approaching the end of what's available in the internal structure, you must asynchronously load more data into the internal data structure.
  6. When the internal data structure gets too large, you must remove data from the internal structure on the end furthest from the current scroll position of the ListView (the scroll position can be estimated using ListItemProvider::updateItem()). The database IDs for the list items must not be removed as they are required to track the correct positions of list items in the DataModel.


Let's have a closer look at how approach #2 is implemented. The first step is to create the DataModel. In addition to overriding some of the standard DataModel functions, we also create functions for loading and removing items from the DataModel, and for requesting/receiving data from a SQL data source.

class MySqlDataModel: public DataModel {

	virtual ~MySqlDataModel();

	// Implementing the DataModel class
	int childCount(const QVariantList &indexPath);Q_INVOKABLE
	bool hasChildren(const QVariantList &indexPath);Q_INVOKABLE
	QVariant data(const QVariantList &indexPath);

	// Functions for loading data and removing items
	void removeItems();Q_INVOKABLE
	void loadData();

	// A signal that's emitted when the initial set of data
	//  has been loaded into the DataModel
	void initialItemsLoaded();

	// Signals and slots used for initiating the SQL request
	void loadSQLData(const QString&);Q_SIGNAL
	void onLoadData(const QString& sql);Q_SLOT

	// A slot that asynchronously receives the reply data 
	//  from the SQL request
public Q_SLOTS:
	void onReply(const bb::data::DataAccessReply& dar);

	void removeLoadingItem();

	SqlWorker *m_pSqlWorker;
	SqlConnection *m_pSqlConnection;

	QVariantList modelList;
	int mState;

The next step is to implement an IndexMapper, which allows the DataModel to maintain the correct indices for list items when data is added and removed.


#include <bb/cascades/DataModel>

class MyIndexMapper: public bb::cascades::DataModel::IndexMapper {
	MyIndexMapper(int index, int count, bool deleted);
	bool newIndexPath(QVariantList *pNewIndexPath, 
            int *pReplacementIndex,
			const QVariantList &oldIndexPath) const;

	int mIndex;
	int mCount;
	bool mDeleted;

#endif /* MYINDEXMAPPER_H_ */

IndexMapper contains a function called newIndexPath(), which is invoked for every item in a data model's internal data structure, each time the itemsChanged() signal is emitted (this happens every time an item is added to or removed from the DataModel). In our implementation of IndexMapper, we need to be able to handle three different scenarios when itemsChanged() is emitted.

Items with an unchanged index
Generally, these items have a lower index than the added or removed items. No action needs to be taken for these items.
Items with a changed index
Generally, items have a higher index than the added or removed items. The index path for these items must be readjusted depending on how many items were added or removed.
Deleted items
For these items, you return the index that the deleted item would have had so that the items are removed from the correct location in the ListView. If a number of sequential items are removed at the same time, the same index is returned for each one, if they are children of the same parent.
bool MyIndexMapper::newIndexPath(QVariantList *pNewIndexPath,
		int *pReplacementIndex, 
        const QVariantList &oldIndexPath) const {

	// Unaffected indices
	if (oldIndexPath[0].toInt() < mIndex) {
		return true;

	// Deleted indices
	} else if (mDeleted && oldIndexPath[0].toInt() <= mIndex + mCount) {
		*pReplacementIndex = mIndex;
		return false;

	// Indices after a deletion or addition
	} else {
		if (mDeleted)
			(*pNewIndexPath).append(oldIndexPath[0].toInt() - mCount);
			(*pNewIndexPath).append(oldIndexPath[0].toInt() + mCount);
		return true;

The final step is implementing the asynchronous requests for SQL data. The loadData() function shows how the SQL data is gradually obtained over a few steps. First, a small set of data is requested, followed by a larger set of data, and then the remainder of the data.

void MySqlDataModel::loadData() {
	switch (mState) {
	case 0:
		emit loadSQLData("select * from contact limit 20");
	case 1:
		emit loadSQLData("select * from contact limit 30 offset 20");
	case 2:
		emit loadSQLData("select * from contact limit 50000 offset 50");

To asynchronously request the data, you create a SqlConnection object and connect its reply() signal to a slot that you create to handle the reply (onReply()). You start the request by calling execute().

void MySqlDataModel::onLoadData(const QString& sql) {
	if (!m_pSqlWorker) {
		m_pSqlWorker = 
                new SqlWorker("app/native/assets/sql/contacts1k.db",
		m_pSqlConnection = new SqlConnection(m_pSqlWorker, this);		
		bool res;
		res =  connect(m_pSqlConnection,
			     SIGNAL(reply(const bb::data::DataAccessReply&)), 
				 SLOT(onReply(const bb::data::DataAccessReply&)));


When you receive the reply data asynchronously, you can append the data to the DataModel and inform the app that new data has been added.

To view the complete code for the examples described in this document, download the AsynchronousDataLoading project.

Last modified: 2015-04-16

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