NodeDate&Time Input

QuickForm

Outputs a string flow variable with a given date&time value. The value can also be controlled from a quick form (web port).

The node supports custom CSS styling. You can simply put CSS rules into a single string and set it as a flow variable 'customCSS' in the node configuration dialog. You will find the list of available classes and their description on our documentation page.

Output ports

  1. Flow Variable Output Type: Flowvariable
    Variable output with the given variable defined.

  1. KNIME Server Log Parsing

    REST API KNIMEServer Logs Logfiles Analysis
    This workflow parses logfiles created during the operation of KNIME Server. The workflow was developed using KNIME Serve…
    knime > Examples > 09_Enterprise > 01_Server > 03_Using_KNIMEServer_REST_API > 07_Log_Parser_and_Usage_Reporting_on_KNIME_Server

  2. Empty the Server Trash Bin

    REST API KNIMEServer
    You can use this workflow to connect to a KNIME Server, list the trash contents and select a cutoff date to retain workf…
    knime > Examples > 09_Enterprise > 01_Server > 03_Using_KNIMEServer_REST_API > 03_Empty_Trash_on_KNIME_Server

  3. Emil the TeacherBot - Deployment via WebPortal Interface

    KNIME WebPortal KNIME Server Emil Teacher Bot text processing Micro Services NLP Natural Language Processing
    This workflow deploys a teacher bot. That is: - it displays a textbox for the user to ask a question - it parses the tex…
    knime > Examples > 50_Applications > 33_Emil_the_TeacherBot > 01_Emil_the_TeacherBot

  4. Showing quickforms in the webportal

    This workflow show the user different quickform which require its input. Afterwards they are shown in one table.
    knime > Examples > 09_Enterprise > 02_WebPortal > 03_Quickforms_to_table

  5. Anomaly Detection. Time Series AR Deployment

    anomaly detection time series analysis auto-regressive models time alignment IoT Internet of Things
    This workflow applies a previously trained auto-regressive model to predict signal values. The model was trained for nor…
    knime > Examples > 50_Applications > 17_AnomalyDetection > 03a_Time_Series_AR_Deployment

  6. Model Deployment Dashboard WebPortal

    Deployment Model Prediction Dashboard WebPortal Interactivity Guided Analytics Flight Delay
    This workflow demontstrates a mode of deploying a model with KNIME. The workflow uploads new unseen data from a local fi…
    knime > Examples > 50_Applications > 27_Deployment_Options > 04_Model_Deployment_dashboard_WebPortal

  7. JavaScript Line Plot Examples - Advanced

    This workflow shows different options available for creating a JavaScript Line Plot. The example data show the developme…
    knime > Examples > 03_Visualization > 02_JavaScript > 03_Example_for_JS_Line_Plot_Advanced

  8. Taxi Demand Prediction Training Workflow

    Demand prediction random forest time series prediction Spark cluster NYC taxi datset IoT Internet of Things
    In this use case, we use the NYC taxi dataset and a Random Forest to train a simple time series prediction model to pred…
    knime > Examples > 10_Big_Data > 02_Spark_Executor > 11_Taxi_Demand_Prediction > Training_workflow

  9. Emil the TeacherBot - WebPortal Interface - Re-Labeling I

    NLP Natural Language Processing
    This workflow is part of a number of other workflows that address a data mining scenario at the intersection of active l…
    knime > Examples > 50_Applications > 33_Emil_the_TeacherBot > 05_AL_Re-label_Uncertain_Classes

  10. Send data to tableau server example

    Tableau
    This workflow reads the data of the last 24 hours from a database and sends it to a tableau server. If the workflow is u…
    kathrin > Forum_Question_Tableau_Example > Send_Data_to_Tableau_Server