Date&Time-based Row Filter

Manipulator

Extracts all rows where the time value of the selected column lies within a given time window from the input. The time window is specified by a start and either an end date (and time), a duration or a numerical value combined with a granularity.

Input Ports

  1. Type: Data
    Input table.

Output Ports

  1. Type: Data
    Filtered output table.

  1. 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…
    Users > knime > Examples > 09_Enterprise > 01_Server > 03_Using_KNIMEServer_REST_API

  2. Inventory Optimization Use Case: Guided Analytics Workflow

    WebPortal based business application, allowing review of inventory KPIs, consumption forecast, setting of service level …
    Users > knime > Examples > 50_Applications > 41_Inventory_Optimization

  3. 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…
    Users > knime > Examples > 09_Enterprise > 01_Server > 03_Using_KNIMEServer_REST_API

  4. Time filtering on the webportal

    We here demonstrate how a date/time column can be filtered to contain only the last k month or week or days. On the webp…
    Users > knime > Examples > 09_Enterprise > 02_WebPortal

  5. Anomaly Detection. Time Series AR Deployment

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

  6. Example: Time Series

    This workflow demonstrates different time series functionality. As the usage of various time series nodes for analyzing …
    Users > knime > Examples > 04_Analytics > 07_Time_Series

  7. Anomaly Detection. Time Series AR Deployment

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

  8. Anomaly Detection. Time Series AR Training

    anomaly detection time series analysis auto-regressive models time alignment
    This workflow trains an auto-regressive model to predict signal values. Only time series values from normal functioning …
    Users > knime > Examples > 50_Applications > 17_AnomalyDetection

  9. Example: Time Series

    This workflow demonstrates different time series functionality. As the usage of various time series nodes for analyzing …
    Users > shima0011 > 04_Analytics > 07_Time_Series

  10. Anomaly Detection. Time Series AR Training

    anomaly detection time series analysis auto-regressive models time alignment
    This workflow trains an auto-regressive model to predict signal values. Only time series values from normal functioning …
    Users > knime > Examples > 50_Applications > 17_AnomalyDetection

Extension

This node is part of the extension

KNIME Core

 v4.0.0

Short Link

Drag node into KNIME Analytics Platform