Create a New KNIME Extension: Quickstart Guide


This quickstart guide describes how to create a new KNIME Extension, i.e. write a new node implementation to be used in KNIME Analytics Platform. You’ll learn how to set up a KNIME SDK, how to create a new KNIME Extension project, how to implement a simple manipulation node, how to test the node, and how to easily deploy the node in order to make it available for others.

For this purpose, we created a reference extension you can use as orientation. This KNIME Extension project can be found in the org.knime.examples.numberformatter folder of the knime-examples GitHub repository. It contains all required project and configuration files and an implementation of a simple Number Formatter example node, which performs number formatting of numeric values of the input table. We will use this example implementation to guide you through all necessary steps that are involved in the creation of a new KNIME Extension.

Set up a KNIME SDK

In order to start developing KNIME source code, you need to set up a KNIME SDK. A KNIME SDK is a configured Eclipse installation which contains KNIME Analytics Platform dependencies. This is necessary as Eclipse is the underlying base of KNIME Analytics Platform i.e. KNIME Analytics Platform is a set of plug-ins that are put on top of Eclipse and the Eclipse infrastructure. Furthermore, Eclipse is an IDE, which you will use to write the actual source code of your new node implementation.

To set up your KNIME SDK, we start with an "Eclipse IDE for RCP and RAP Developers" installation (this version of Eclipse provides tools for plug-in development) and add all KNIME Analytics Platform dependencies. In order to do that, please follow the SDK Setup instructions. Apart from giving instructions on how to set up a KNIME SDK, the SDK Setup will give some background about the Eclipse infrastructure, its plug-in mechanism, and further useful topics like how to explore KNIME source code.

Create a New KNIME Extension Project

After Eclipse is set up and configured, create a new KNIME Extension project. A KNIME Extension project is an Eclipse plug-in project and contains the implementation of one or more nodes and some KNIME Analytics Platform specific configuration. The easiest way to create a KNIME Extension project, is by using the KNIME Node Wizard, which will automatically generate the project structure, the plug in manifest and all required Java classes. Furthermore, the wizard will take care of embedding the generated files in the KNIME framework.

The KNIME Node Wizard

  1. Install the KNIME Node Wizard

    Open the Eclipse installation wizard at Help → Install New Software… , enter the following update site location: in the location box labelled Work with:.

    Replace the version number in the update site location with the latest version of KNIME Analytics Platform (excluding bugfix version). The latest version number can be found here.

    Hit the Enter key, and put KNIME Node Wizard in the search box. Tick the KNIME Node Wizard under the category KNIME Node Development Tools, click the Next button and follow the instructions. Finally, restart Eclipse.

    install node wizard
    Figure 1. The KNIME Node Wizard installation dialog.
  2. Start the KNIME Node Wizard

    After Eclipse has restarted, start the KNIME Node Wizard at File → New → Other… , select Create a new KNIME Node-Extension (can be found in the category Other), and hit the Next button.

    start new node wizard
    Figure 2. The KNIME Node Wizard start dialogs.
  3. Create a KNIME Extension Project

    In the Create new KNIME Node-Extension dialog window enter the following values:

    • New Project Name: org.knime.examples.numberformatter

    • Node class name: NumberFormatter

    • Package name: org.knime.examples.numberformatter

    • Node vendor: <your_name>

    • Node type: Select Manipulator in the drop down menu.

    Replace <your_name> with the name that you like to be the author of the created extension. Leave all other options as is and click Finish.

    node wizard dialog
    Figure 3. The KNIME Node Wizard dialog.

    After some processing, a new project will be displayed in the Package Explorer view of Eclipse with the project name you gave it in the wizard dialog.

    Make sure that the checkbox Include sample code in generated classes is checked. This will include the code of the aforementioned Number Formatter node in the generated files.
    Figure 4. A view of Eclipse after the KNIME Node Wizard has run.

    In the Package Explorer view of Eclipse (left side) you should now see three projects. The two projects org.apache.xmlbeans and org.knime.sdk.setup which you imported in the SDK Setup, and the project org.knime.examples.numberformatter that you just created using the KNIME Node Wizard.

Test the Example Extension

At this point, all parts that are required for a new KNIME Extension are contained in your Eclipse workspace and are ready to run. To test your node, follow the instructions provided in the Launch KNIME Analytics Platform Section of the SDK Setup. After you started KNIME Analytics Platform from Eclipse, the Number Formatter node will be available at the root level of the node repository. Create a new workflow using the node (see Figure below), inspect the input and output tables, and play around with the node.

Figure 5. KNIME Analytics Platform development version started from Eclipse showing an example workflow. The Number Formatter node contained in the Eclipse workspace is displayed at the bottom of the node repository.

The node will perform simple rounding of numbers from the input table. To change the number of decimal places the node should round to, change the digit contained in the format String that can be entered in the node configuration (e.g. %.2f will round to two decimal places,the default value is %.3f). After you are done, close KNIME Analytics Platform.

Project Structure

Next, let’s review the important parts of the extension project you’ve just created. First, we’ll have a look at the files located in org.knime.examples.numberformatter.

The files contained in this folder correspond to the actual node implementation. There are four Java classes implementing what the node should do, how the dialog and the view looks like, one XML file that contains the node description, and an image which is used as the node icon (in this case a default icon) displayed in the workflow view of KNIME Analytics Platform. Generally, a node implementation comprises of the following classes: NodeFactory, NodeModel, NodeDialog, NodeView. In our case, these classes are prefixed with the name you gave the node in the KNIME Node Wizard, i.e. NumberFormatter.


    The NodeFactory bundles all parts that make up a node. Thus, the factory provides creation methods for the NodeModel, NodeDialog, and NodeView. Furthermore, the factory will be registered via a KNIME extension point such that the node is discoverable by the framework and will be displayed in the node repository view of KNIME Analytics Platform. The registration of this file happens in the plugin.xml (see description of the plugin.xml file below).


    The NodeModel contains the actual implementation of what the node is supposed to do. Furthermore, it specifies the number of inputs and outputs of a node. In this case the node model implements the actual number formatting.

  • (optional)

    The NodeDialog provides the dialog window that opens when you configure (double click) a node in KNIME Analytics Platform. It provides the user with a GUI to adjust node specific configuration settings. In the case of the Number Formatter node this is just a simple text box where the user can enter a format String. Another example would be the file path for a file reader node.

  • (optional)

    The NodeView provides a view of the output of the node. In the case of the Number Formatter node there will be no view as the output is a simple table. Generally, an example for a view could be a tree view of a node creating a decision tree model.

  • NumberFormatterNodeFactory.xml

    This XML file contains the node description and some metadata of the node. The root element must be a <knimeNode> … </knimeNode> tag. The attributes of this tag further specify the location of the node icon (icon=”…​”) and the type of the node (type=”…​”). Note that this is the type you selected in the dialog of the Node Wizard earlier. The most common types are Source, Manipulator, Predictor, Learner, Sink, Viewer, and Loop. The description of the node is specified in the children of the root tag. Have a look at the contents of the file for some examples. The .xml must be located in the same package as the NodeFactory and it has to have the same name (only the file ending differs).

  • default.png

    This is the icon of the node displayed in the workflow editor. The path to the node icon is specified in the NumberFormatterNodeFactory.xml (icon attribute of the knimeNode tag). In this case the icon is just a placeholder displaying a question mark. For your own node, replace it with an appropriate image representative of what the node does. It should have a resolution of 16x16 pixels.

Apart from the Java classes and the factory .xml, which define the node implementation, there are two files that specify the project configuration:

  • plugin.xml and META-INF/MANIFEST.MF

    These files contain important configuration data about the extension project, like dependencies to other plug-ins and the aforementioned extension points. You can double click on the plugin.xml to open an Eclipse overview and review some of the configuration options (e.g. the values we entered in KNIME Node Wizard are shown on the overview page under General Information on the left). However, you do not have to change any values at the moment.

plugin xml
Figure 6. Eclipse overview of the plugin.xml and MANIFEST.MF.

Number Formatter Node Implementation

Once you have reviewed the project structure, we have a look at some implementation details. We will cover the most important parts as the example code in the project you created earlier already contains detailed comments in the code of the implemented methods (also have a look at the reference implementation in the org.knime.examples.numberformatter folder of the knime-examples repository).

Generally, the Number Formatter node takes a data table as input and applies a user specified format String to each Double column of the input table. For simplicity, the output table only contains the formatted numeric columns as String columns. This basically wraps the functionality of the Java String.format(…​) function applied to a list of Double values into a node usable in KNIME Analytics Platform.

Let’s work through the most important methods that each node has to implement. The functionality of the node is implemented in the class:

protected NumberFormatterNodeModel() {
    super(1, 1);

The super(1, 1) call in the constructor of the node model specifies the number of output and input tables the node should have. In this case it is one input and one output table.

BufferedDataTable[] execute(final BufferedDataTable[] inData, final ExecutionContext exec)

The actual algorithm of the node is implemented in the execute method. The method is invoked only after all preceding nodes have been successfully executed and all data is therefore available at the input ports. The input table will be available in the given array inData which contains as many data tables as specified in the constructor. Hence, the index of the array corresponds to the port index of the node. The type of the input is BufferedDataTable, which is the standard type of all tabular data in KNIME Analytics Platform. The persistence of the table (e.g. when the workflow is saved) is automatically handled by the framework. Furthermore, a BufferedDataTable is able to handle data larger than the size of the main memory as the data will be automatically flushed to disk if necessary. A table contains DataRow objects, which in turn contain DataCell objects. DataCells provide the actual access to the data. There are a lot of DataCell implementation for all types of data, e.g. a DoubleCell containing a floating point number in double precision (for a list of implementations have a look at the type hierarchy of the DataCell class). Additionally, each DataCell implements one or multiple DataValue interfaces. These define which access methods the cell has i.e. which types it can be represented as. For example, a BooleanCell implements IntValue as a Boolean can be easily represented as 0 and 1. Hence, for each DataValue there could be several compatible DataCell classes.
The second argument exec of the method is the ExecutionContext which provides means to create/modify BufferedDataTable objects and report the execution status to the user. The most straightforward way to create a new DataTable is via the createDataContainer(final DataTableSpec spec) method of the ExecutionContext. This will create an empty container where you can add rows to. The added rows must comply with the DataTableSpec the data container was created with. E.g. if the container was created with a table specification containing two Double columns, each row that is added to the container must contain two DoubleCells. After you are finished adding rows to the container close it via the close() method and retrieve the BufferedDataTable with getTable(). This way of creating tables is also used in the example code (see Apart from creating a new data container, there are more powerful ways to modify already existing input tables. However, these are not in the scope of this quickstart guide, but you can have a look at the methods of the ExecutionContext.
The execute method should return an array of output BufferedDataTable objects with the length of the number of tables as specified in the constructor. These tables contain the output of the node.

DataTableSpec[] configure(final DataTableSpec[] inSpecs)

The configure method has two responsibilities. First, it has to check if the incoming data table specification is suitable for the node to execute with respect to the user supplied settings. For example, a user may disallow a certain column type in the node dialog, then we need to check if there are still applicable columns in the input table according to this setting. Second, to calculate the table specification of the output of the node based on the inputs. For example: imagine the Number Formatter node gets a table containing two Double columns and one String column as input. Then this method should return a DataTableSpec (do not forget to wrap it in an array) containing two DataColumnSpec of type String (the Double columns will be formatted to String, all other columns are ignored). Analogously to the execute method, the configure method is called with an array of input DataTableSpec objects and outputs an array of output DataTableSpec objects containing the calculated table specification. If the incoming table specification is not suitable for the node to execute or does not fit the user provided configuration, throw an InvalidSettingsException with an informative message for the user.

saveSettingsTo(final NodeSettingsWO settings)


loadValidatedSettingsFrom(final NodeSettingsRO settings)

These methods handle the loading and saving of settings that control the behaviour of the node, i.e. the settings entered by the user in the node dialog. This is used for communication between the node model and the node dialog and to persist the user settings when the workflow is saved. Both methods are called with a NodeSettings object (in a read only (RO) and write only (WO) version) that stores the settings and manages writing or reading them to or from a file. The NodeSettings object is a key-value storage, hence it is easy to write or read to or from the settings object. Just have a look at the provided methods of the NodeSettings object in your Eclipse editor. In our example, we do not write settings directly to the NodeSettings object as we are using a SettingsModel object to store the user defined format String. SettingsModel objects already know how to write and read settings from the NodeSettings (via methods that accept NodeSettings) and help to keep settings synchronization between the model and dialog simple. Furthermore, they can be used to create simple dialogs where the loading and saving of settings is already taken care of.

You can find the actual algorithm of the Number Formatter node in the execute method in the class. We encourage you to read through the code of the above mentioned classes to get a deeper understanding of all parts of a node. For a more thorough explanation about how a node should behave consult the KNIME Noding Guidelines.

Deploy your Extension

This section describes how to deploy the node after you have finished the implementation. This can be done using the Deployable plug-ins and fragments Wizard from within Eclipse. Go to File → Export → Plug-in Development → Deployable plug-ins and fragments and click Next. The dialog that opens will show a list of deployable plug-ins from your workspace. Check the checkbox next to org.knime.examples.numberformatter. At the bottom of the dialog you are able to select the export method. Choose Directory and supply a path to a folder where you want to export your plugin to. At last click Finish.

Figure 7. The dialog of the deploy wizard.

After the export has finished, the selected folder will contain a .jar file containing your plugin. To install it into any Eclipse or KNIME Analytics Platform installation, place the .jar file in the dropins folder of the KNIME/Eclipse installation folder. Note that you have to restart KNIME/Eclipse for the new plugin to be discovered. In this example, the node is then displayed at the top level of the node repository in KNIME Analytics Platform.
If you think your new node or extension could be valuable for others and you want to make it available as a Community Extension, you could become a community contributor. By providing a Community Extension your nodes will be installable via the Community Extension update site.

Further Reading