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HDF > Develop with Hadoop > Hello World

Analyze Transit Patterns with Apache NiFi

Build a NiFi Process Group to Validate the GeoEnriched Data

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With the transit data being pulled from NextBus API simulator, it shows location in form of latitude and longitude, but it does not indicate more meaningful insights like neighborhoods that the transits pass by on their routes. You will add that capability to the NiFi flow by integrating Google Places API. Additionally you will add the capability to automate validation of the geo enriched data. You will add a new process group called ValidateGeoEnrichedTransitData.


  • Completed the prior tutorials within this tutorial series


If you prefer to build the dataflow manually step-by-step, continue on to Approach 1. Else if you want to see the NiFi flow in action within minutes, refer to Approach 2.

You will need to understand Google Places API, so that it will be easier to incorporate this API’s data into the NiFi flow, which will be built in Approach 1.

Google Places API Basics

Google Places API Web Service returns information about places: establishments, geographic locations and prominent points of interest based on Latitude and Longitude coordinates that are passed into HTTP requests. The Places API includes six place requests: Place Searches, Place Details, Place Add, Place Photos, Place Autocomplete and Query Autocomplete. Read more about these place requests in Introducing the API.

All requests are accessed through an HTTP request and return either JSON or XML response.

What are the necessary components to use the Places API?

  • https:// protocol
  • API Key

Approach 1: Manually Build ValidateGeoEnrichedTransitData Process Group (PG)

Step 1: Obtain API Key for NiFi’s InvokeHTTP Processor

For our dataflow, our task is to enrich the data by searching for neighborhoods within proximity of a vehicle’s varying location. Currently location is represented as Latitude and Longitude coordinates. You will enhance these insights to retrieve two parameters from this location data: name of the neighborhoods and San Francisco Muni Transit Agency. So, you will integrate Nearby Search HTTP request with NiFi.

The Nearby Search request is an HTTP URL of the following definition, which we will need for NiFi:

The output can come in two formats: json or xml. We will use json for this tutorial.

Let’s obtain the required parameters to initiate a Nearby Search request.

1. You will need to obtain an API key, so it can identify our application for quota management and places added from the application are instantly available to our app (NiFi).

2. You will use a standard Google Places API. Click on the blue Get A Key button to activate the API Web Service.

3. A window will appear that says Enable Google Places API Web Service. Select Yes. Then Create And Enable API. Wait a few seconds for the new window to load.

4. Now a screen with your unique API key will appear similar to the screen below:


Now you have the API Key parameter for our HTTP request. We also have the other required parameters: location and radius, which can be a distance that does not surpass 50,000 meters. You can use one optional parameter type to signify what type of place you are interested in searching for.

5. Let’s build the HTTP URL with the parameters below, so we can insert the URL as a property value into InvokeHTTP later in the tutorial.

  • API Key = AIzaSyDY3asGAq-ArtPl6J2v7kcO_YSRYrjTFug
  • Latitude = ${Latitude}
  • Longitude = ${Longitude}
  • radius = 500
  • type = neighborhood${Latitude},${Longitude}&radius=500&type=neighborhood&key=AIzaSyDY3asGAq-ArtPl6J2v7kcO_YSRYrjTFug

Note: Your API Key will be different than the one in the URL above. You will need to use the ONE you get from Google Places API Web Service.

Step 2: Create Process Group and Label For It

1. Add a Label label_icon onto the NiFi canvas for the new process group. Right click, Change color to Purple.

2. Right click, select configure and name it Geo Enrich via Google Places API and Validate Transit Data for empty values.


3. Add a new Process Group onto the NiFi canvas and name it ValidateGeoEnrichedTransitData


4. Double click on the new process group to enter it.


Step 3: Add an Input Port to Ingest Data Into this PG

1. Add the Input Port output_port component onto the NiFi canvas. Name it IngestParsedTransitEvents.


Step 4: Add RouteOnAttribute to Validate NextBus Simulator Data

1. Add the RouteOnAttribute processor onto the NiFi canvas.

2. Connect IngestParsedTransitEvents input port to RouteOnAttribute processor. When the Create Connection window appears, click Add.


Figure 1: Connect IngestParsedTransitEvents input port to RouteOnAttribute processor

3. Open the processor configuration properties tab. Add a new dynamic property for NiFi expression, select the ( + ) button. Insert the following property name and value into your properties tab as shown in the table below:

Table 1: Add to RouteOnAttribute Properties Tab

Property Value
ValidateTransitObservations ${Direction_of_Travel:isEmpty():not():and(${Last_Time:isEmpty():not()}):and(${Latitude:isEmpty():not()}):and(${Longitude:isEmpty():not()}):and(${Vehicle_ID:isEmpty():not()}):and(${Vehicle_Speed:equals('0'):not()})}

Filter_Attributes uses the FlowFile Attribute key values obtained from XPath Expressions to filter out any FlowFiles that either have at least one empty Attribute value or the speed attribute value equals 0. Else the FlowFiles are passed to the remaining processors.

4. Open the processor config Settings tab, change the name from RouteOnAttribute to ValidateNextBusData. under Auto terminate relationships, check the unmatched checkbox. Click Apply.

Step 5: Add InvokeHTTP to Pull GeoEnriched Data from Google Places API

1. Add the InvokeHTTP processor onto the NiFi graph. Connect ValidateNextBusData to InvokeHTTP processor. When the Create Connection window appears, verify ValidateTransitObservations checkbox is checked, if not check it. Click Add.


Figure 2: Connect ValidateNextBusData to InvokeHTTP

2. Open InvokeHTTP configure properties tab and add the property listed in Table 2.

Table 2: Update InvokeHTTP Properties Tab

Property Value
Remote URL${Latitude},${Longitude}&radius=500&type=neighborhood&key=AIzaSyDY3asGAq-ArtPl6J2v7kcO_YSRYrjTFug

Remote URL connects to the HTTP URL we created using Google Places API and feeds that data into the dataflow. Notice we use two NiFi expressions for location parameter. This is because those two values change as new FlowFiles pass through this processor.

3. Navigate to the Settings tab, change the name from InvokeHTTP to GoogleNearbySearchAPI. Under Auto terminate relationships check the Failure, No Retry, Original and Retry checkboxes. Click Apply button.

Step 6: Add EvaluateJsonPath to Extract GeoEnriched Transit Data

1. Add the EvaluateJsonPath processor onto the NiFi graph. Connect GoogleNearbySearchAPI to EvaluateJsonPath processor. When the Create Connection window appears, select Response checkbox. Click Add.


Figure 3: Connect GoogleNearbySearchAPI to EvaluateJsonPath

2. Open EvaluateJsonPath configure properties tab and update the original properties with the properties listed in Table 3. Note: add city and neighborhoods_nearby property by clicking the ( + ) button, then insert their values into the properties tab.

Table 3: Update EvaluateJsonPath Properties Tab

Property Value
Destination flowfile-attribute
Return Type json
city $.results[0].vicinity
neighborhoods_nearby $.results[*].name
  • Destination result from JSON Path Evaluation stored in FlowFile attributes.
  • 2 user-defined attributes each hold a value that is used in the NiFi Expression language filtering condition in the next processor.

3. Navigate to the Settings tab, change the name from EvaluateJsonPath to ExtractGeoEnrichedData. Under Auto terminate relationships check the unmatched and failure checkboxes. Click Apply button.

Step 7: Add RouteOnAttribute to Validate Google Places Data

1. Add the RouteOnAttribute processor onto the NiFi graph. Connect ExtractGeoEnrichedData to RouteOnAttribute processor. When the Create Connection window appears, select matched checkbox. Click Add.


Figure 4: Connect ExtractGeoEnrichedData to RouteOnAttribute

2. Open RouteOnAttribute configure properties tab and click on New property button to add ValidateGooglePlacesData to property name and insert its NiFi expression value listed in Table 4.

Table 4: Update ValidateGooglePlacesData Properties Tab

Property Value
ValidateGooglePlacesData ${city:isEmpty():not():and(${neighborhoods_nearby:isEmpty():not()})}

ValidateGooglePlacesData uses the FlowFile Attribute values obtained from JSON Path Expressions to filter out any FlowFiles that have at least one empty Attribute value. Else the FlowFiles are passed to the remaining processors.

3. Navigate to the Settings tab, change the name from RouteOnAttribute to ValidateGooglePlacesData. Under Auto terminate relationships check the unmatched checkbox. Click Apply button.

Step 8: Add an Output Port to Route Data Outside this PG

1. Add the Output Port output_port component onto the NiFi canvas. Name it SendGeoEnrichedTranistEvents.

2. Connect ValidateGooglePlacesData to SendGeoEnrichedTranistEvents output port. When the Create Connection window appears, verify ValidateGooglePlacesData checkbox is checked, if not check it. Click Add.


Figure 5: Connect ValidateGooglePlacesData to SendGeoEnrichedTranistEvents

Step 9: Connect ParseTransitEvents to ValidateGeoEnrichedTransitData

1. Re-enter the NiFi Flow breadcrumb to exit ValidateGeoEnrichedTransitData.

2. Connect ParseTransitEvents to ValidateGeoEnrichedTransitData process group. When the Create Connection window appears, verify From Output = ParsedTransitEvents and connects to To Input = IngestParsedTransitEvents. Click Add.


Figure 6: Connect ParseTransitEvents to ValidateGeoEnrichedTransitData Process Group

Step 10: Run the DataFlow

1. Hold Shift and drag your mouse across the entire dataflow. You should see the dataflow is highlighted.


Figure 7: Selected the entire dataflow

2. In the Operate panel, you should see the header says Multiple components are selected. Press the Start button.


Figure 8: Started the entire dataflow

Step 11: Verify GeoEnriched Data Routed by ValidateGooglePlacesData is Valid

Inside the ValidateGeoEnrichedTransitData process group, we will inspect ValidateGooglePlacesData processor. We will look at the flowfiles that pass through this processor and analyze their attributes. We need to make sure that each flowfile’s attribute keys city and neighborhoods_nearby do not have an empty corresponding value. FlowFile attributes are in key/value format.

1. Jump into ValidateGeoEnrichedTransitData process group.

2. Right click on the ValidateGooglePlacesData connector downstream from ValidateGooglePlacesData processor, select List queue to see provenance events.


Figure 9: List Queue for Connector between ValidateGooglePlacesData and SendGeoEnrichedTranistEvents

3. View any event by selecting the view provenance event icon i_symbol_nifi

4. Click on the Attributes tab. As long as you see that city and neighborhoods_nearby have values, you have verified the ValidateGooglePlacesData processor is successfully routing flowfiles based on this condition.


Figure 10: Data Provenance for FlowFile attribute (key/value): city contains San Francisco.


Figure 11: Data Provenance for FlowFile attribute (key/value): neighborhoods_nearby contains [“Saint Francis Wood”,”West Portal”]

Approach 2: Import Enriched NiFi Flow Via Places API

Warning 1: If you Imported the Previous DataFlow, Read these steps first

1. In your process group, if there are any queues left with data, remove the data. Right click the queue, select Empty queue, click EMPTY.

2. Navigate back to the NiFi Flow breadcrumb level to delete your flow.

To delete your previous flow, hold command or ctrl and press A to highlight your dataflow, then press delete or backspace.

Import the New DataFlow Template

3. Download the tutorial-5-ValidateGeoEnrichedTransitData.xml template file. Then upload the template file into NiFi.

4. Use the template icon nifi_template_icon located in the Operate Palette.

5. Browse, find the template file, click Open and hit Upload.

6. From the Components Toolbar, drag the template icon nifi_template_icon onto the graph and select the tutorial-4-ParseTransitEvents.xml template file.

Warning 2: If you didn’t Obtain Google API Key, then follow the steps

7. Refer to Step 1 in Approach 1 to obtain the Google API key and set up Google Places API: HTTP URL.

8. Replace the InvokeHTTP processor’s Remote URL property value with the new Google Places API: HTTP URL value.

9. Hit the start button start_button_nifi_iot. to activate the dataflow.


Figure 12: tutorial-5-ValidateGeoEnrichedTransitData.xml template includes a NiFi Flow that pulls in San Francisco Muni Transit Events from the XML Simulator, parses through the data to extract key values and stores the transit observations as a JSON file.

Overview of the Process Groups and their Processors:

  • SimulateXmlTransitEvents (Process Group)

    • GetFile fetches the vehicle location simulator data for files in a directory.
    • UnpackContent decompresses the contents of FlowFiles from the traffic simulator zip file.
    • ControlRate controls the rate at which FlowFiles are transferred to follow-on processors enabling traffic simulation.
    • UpdateAttribute renames every FlowFile to give them unique names
    • PutFile stores data to local file system
    • Output Port makes the connection for the process group to connect to other components (process groups, processors, etc)
  • ParseTransitEvents (Process Group)

    • Input Port ingests data from SimulateXmlTransitEvents Process Group
    • ExtractTimestamp extracts the timestamp of the last update for vehicle location data returned from each FlowFile.
    • SplitXML splits the parent’s child elements into separate FlowFiles. Since vehicle is a child element in our xml file, each new vehicle element is stored separately.
    • ExtractTransitObservations extracts attributes: vehicle id, direction, latitude, longitude and speed from vehicle element in each FlowFile.
    • Output Port outputs data with the new FlowFile attribute (key/values) to the rest of the flow
  • ValidateGooglePlacesData (Process Group)

    • Input Port ingests data from ParseTransitEvents Process Group
    • ValidateNextBusData checks the NextBus Simulator data by routing FlowFiles only if their attributes contain transit observation data (Direction_of_Travel, Last_Time, Latitude, Longitude, Vehicle_ID, Vehicle_Speed)
    • InvokeHTTP sends a rest call to Google Places API to pull in geo enriched data for transit location
    • EvaluateJSONPath parses the flowfile content for city and neighborhoods_nearby
    • ValidateGooglePlacesData checks the new Google Places data by routing FlowFiles only if their attributes contain geo enriched data (city, neighborhoods_nearby)
    • Output Port outputs data with nonempty FlowFile attributes (key/values) to the rest of the flow


Congratulations! For the Geo Enrichment section of the dataflow, you learned to use InvokeHTTP to access geographic location of nearby places with Google Places Search API. You learned to add NiFi expression variables into InvokeHTTP property RemoteURL, so that the values for latitude and longitude constantly change in the URL when new FlowFiles pass through this processor. You learned to use EvaluateJsonPath similar to EvaluateXPath, except JSON Expression is used to extract JSON elements (neighborhoods_nearby & city) from a JSON structure. Now you know how to incorporate external API’s into NiFi further enhance the dataflow.

Further Reading