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Taxi_​Visualization

Interactive Big Data Exploration and Visualization
Interactive Big Data Exploration and VisualizationThe NYC taxi dataset contains over 1 billion taxi trips in New York City between January 2009 and December 2017 and is provided by the NYC Taxi and LimousineCommision (TLC)[1]. It contains not only information about the regular yellow cabs, but also green taxis, which started in August 2013, and For-Hire Vehicle (e.gUber) starting from January 2015. In the data, each taxi trip is recorded with information such as the pickup and dropoff locations, datetime, number of passengers,trip distance, fare amount, tip amount, etc. This workflow showcases the combination of using Spark to analyse huge amount of data, while still making the process interactive via the Webportal. Please note that the workflow uses extensions from our Trusted Community Contributions Update Sites. These update sites are not enabled by default. If you havenot already done so, you will need to do this in KNIME via File->Preferences->Install/Update->Available Update Sites.To execute this workflow, please save it to your local workspace first.[1] http://www.nyc.gov/html/tlc/html/home/home.shtml Loading and processing... First Page Filtering and persisting... Second Page Third Page overview ofa specific boroughoverview ofall taxi typesforward only dataframe thatcorresponds to the selected taxi typeoverview of a taxi typeoverview of a taxi typeoverview ofa specific boroughfilter boroughs,years, etc 3rd Page 1st Page Spark case switch Java Edit Variable CASE SwitchVariable (Start) 2nd Page -Yellow and Green 2nd Page - FHV 3rd Page Persist SparkDataFrame/RDD Processing Filtering... Choose whether to use remoteor local Big Data env Load Parquetfiles into Spark Interactive Big Data Exploration and VisualizationThe NYC taxi dataset contains over 1 billion taxi trips in New York City between January 2009 and December 2017 and is provided by the NYC Taxi and LimousineCommision (TLC)[1]. It contains not only information about the regular yellow cabs, but also green taxis, which started in August 2013, and For-Hire Vehicle (e.gUber) starting from January 2015. In the data, each taxi trip is recorded with information such as the pickup and dropoff locations, datetime, number of passengers,trip distance, fare amount, tip amount, etc. This workflow showcases the combination of using Spark to analyse huge amount of data, while still making the process interactive via the Webportal. Please note that the workflow uses extensions from our Trusted Community Contributions Update Sites. These update sites are not enabled by default. If you havenot already done so, you will need to do this in KNIME via File->Preferences->Install/Update->Available Update Sites.To execute this workflow, please save it to your local workspace first.[1] http://www.nyc.gov/html/tlc/html/home/home.shtml Loading and processing... First Page Filtering and persisting... Second Page Third Page overview ofa specific boroughoverview ofall taxi typesforward only dataframe thatcorresponds to the selected taxi typeoverview of a taxi typeoverview of a taxi typeoverview ofa specific boroughfilter boroughs,years, etc 3rd Page 1st Page Spark case switch Java Edit Variable CASE SwitchVariable (Start) 2nd Page -Yellow and Green 2nd Page - FHV 3rd Page Persist SparkDataFrame/RDD Processing Filtering... Choose whether to use remoteor local Big Data env Load Parquetfiles into Spark

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Created by: myAdmin
Created at: 2018-08-21
On NodePit since: 2019-07-12
Last update: 2024-04-18
Created with KNIME version: v3.7.1
Tags: big datadata explorationvisualizationwebportalIoTInternet of Things

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