Best Practices: Display Large Data

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A chart's performance directly relates to how many points and elements it displays: fewer elements result in higher performance. This topic explains how to reduce the number of data points and enhance the chart's performance.

Data Aggregation

You can use the Data Aggregation functionality to configure a more compact and readable view for a large amount of data. When using data aggregation, the chart splits the x-axis into intervals (according to the measurement unit value), and automatically aggregates data for each interval using an aggregation function. The following images illustrate this feature:

Non-aggregated data Data aggregated by year
non-aggregated-chart aggregated-chart-data

Refer to the Data Aggregation document for more details.

Loading Data

The following approaches can help you to accelerate loading data:

  • If possible, store all data points in a few series. Since the Chart control is optimized for rendering a small number of series that have many points, rather than rendering a large number of series with a few points. For example, a single series with a million points is processed faster than 10 series with 100000 points each.
  • Since v16.1, the Chart Control loads data and applies settings when a chart is being rendered. This means you do not have to use the ChartControl.BeginInit and ChartControl.EndInit methods, or the SeriesPointCollection's ChartCollectionBase.BeginUpdate and ChartCollectionBase.EndUpdate methods to accelerate loading data.
  • Manual series point creation is faster than individual series binding (series points are generated based on a data source) and series template binding (series and points are generated based on a data source). However, data binding does not cause a significant performance loss.

    You can use the Series.DataSourceSorted property to notify the chart that the series's data source is already sorted to prevent the chart's internal sorting procedures.

  • The best way to add points to the series is using a single operation instead of adding each point separately. The code below demonstrates this approach:

    SeriesPoint[] points = new SeriesPoint[PointsCount];
    for (int i = 0; i < PointsCount; i++) {
        points[i] = new SeriesPoint(i, i);

Automatic Calculations

Range, scale type and layout's automatic calculations require additional resources. The following steps can help accelerate rendering a chart:

Rendering Visual Elements

Follow the steps below to decrease the time needed for rendering a chart's visual elements:

Interactivity Optimization

The runtime hit testing, selection and tooltips features require additional CPU and RAM resources and may decrease performance.

Changeable Data

This section contains tips that allow you to increase performance when a chart shows a dataset that changes frequently.

  • Remove an existing point and add a new one instead to update the chart's data. Changing an existing SeriesPoint's argument or value results in unnecessary calculations. For example, changing the SeriesPoint.Values property calls the ChartControl.RefreshData method and updates the chart's data.
  • Since v17.1, the Chart Control completely processes the following event arguments to avoid reloading all the data when the chart is bound to a dataset that updates frequently:

    For this reason, use the IBindingList objects to process data efficiently when a chart frequently updates data.