Data In Motion

Real-Time Irish Transit Analytics

Apache NiFi, Postgresql, GenAI, Apache Kafka, Apache Flink, JSON, GTFS

Let’s hop on a bus in Ireland!

We need to load static (rarely changing lookup data). We can do this with NiFi very easily. We build and insert these into new Postgresql tables.

See me here:

ChatGPT Authored Introduction:

Unlocking the Future of Transportation: Real-Time Irish Transit Analytics

In the bustling landscape of modern transportation, the ability to harness real-time data is not just a competitive advantage; it’s a necessity. In Ireland, where efficient transit systems are the lifeblood of daily commutes and city connectivity, the fusion of cutting-edge technologies is revolutionizing how we understand and optimize public transportation. This article delves into the world of Real-Time Irish Transit Analytics, where Apache NiFi, PostgreSQL, GenAI, Apache Kafka, Apache Flink, JSON, and GTFS converge to create a dynamic and responsive ecosystem.

Every day, thousands of passengers rely on Ireland’s public transit systems to navigate cities, reach work, or simply explore the beauty of the countryside. Yet, behind the scenes of this seemingly seamless operation lies a complex network of data streams, from vehicle locations to passenger counts, schedules to service updates. Here, Apache NiFi emerges as a pivotal tool, seamlessly orchestrating the flow of data from various sources into a unified pipeline.

PostgreSQL steps in as the reliable database backbone, providing a robust foundation for storing and querying vast amounts of transit data. With the power of GenAI, machine learning algorithms sift through this data trove, uncovering valuable insights into passenger behaviors, traffic patterns, and optimal routes.

But data is only as valuable as its timeliness, and this is where Apache Kafka and Apache Flink shine. Kafka acts as the real-time messaging hub, ensuring that updates from buses, trains, and stations are instantly propagated through the system. Flink’s stream processing capabilities then come into play, analyzing incoming data on the fly to generate actionable intelligence.

In the realm of data interchange, JSON (JavaScript Object Notation) emerges as the lingua franca, facilitating seamless communication between different components of the analytics ecosystem. And anchoring it all is the General Transit Feed Specification (GTFS), a standardized format for public transit schedules and geographic information, ensuring interoperability and accuracy across the board.

Join us on a journey through the intricacies of Real-Time Irish Transit Analytics, where these technologies converge to enhance efficiency, improve passenger experiences, and pave the way for the future of smart transportation.

An important source of data is the static GTFS lookup tables provided a zip file of CSV. We can download and parse this automagically in NiFi. No need to know and precreate tables. NiFi will determine the fields for you.

https://www.transportforireland.ie/transitData/Data/GTFS_Realtime.zip

GTFS Static Data Load

Skip shapes.txt as we aren’t loading those

Set a Default Primary Key

Setting All the Correct Primary Keys for all the Static Files/Tables

Split Up Tables into 1,000 Row Chunks to Make it Easier for Postgresql

We converted CSV to JSON and split up in 1 step

Update the SQL Automagically

we do not manually set field names, no SQL injection here

Send this SQL to the Database

A list of Ireland Lookup Trips loaded from trips.txt

Let’s parse the real time transit information for Ireland.

GTFS Real-Time

Vehicle Positions is the primary API to get where the buses are.

API REST TEST

APIs: Details
Discover APIs, learn how to use them, try them out interactively, and sign up to acquire keys.developer.nationaltransport.ie

GET https://api.nationaltransport.ie/gtfsr/v2/gtfsr?format=json HTTP/1.1

Cache-Control: no-cache

x-api-key: dddddd

As opposed to most transit systems we have seen in GTFS and GTFS-R feeds they don’t have three types, just the two. They are missing alerts.

[ Trip Updates, Vehicle Positions]

APIs: Details
Discover APIs, learn how to use them, try them out interactively, and sign up to acquire keys.developer.nationaltransport.ie

The GTFS-R API contains real-time updates for services provided by Dublin Bus, Bus Éireann, and Go-Ahead Ireland.

You have to sign up and subscribe to the API to use this.

x-api-key is the header for our private key

Example Vehicle Position as JSON

[ {
  "recordid" : "V56",
  "route_id" : "3924_62692",
  "directionid" : "0",
  "latitude" : "53.3537788",
  "tripid" : "3924_16321",
  "starttime" : "22:50:00",
  "vehicleid" : "274",
  "startdate" : "20240322",
  "uuid" : "8a50c084-0aea-496e-b4c3-dbed373e812e",
  "longitude" : "-6.40118694",
  "timestamp" : "1711150967",
  "ts" : "1711167213555"
} ]

Vehicle Position Slack Message

Irish Transit Tracking
Direction ${directionid}
Request ${invokehttp.request.url} ${invokehttp.status.message} ${invokehttp.tx.id}
Lat/Long ${latitude}/${longitude}
Vehicle ${vehicleid}
Route ${route_id}
Scheduled? ${scheduled}
Start Date/Time/TS ${startdate} / ${starttime}  / ${timestamp}
IDs ${uuid} ${recordid} TripID ${tripid}
Scheduled: ${scheduled}

Trip Updates

Example Trip Update as JSON

{
  "triptimestamp" : "1711415067",
  "stopsequence" : "10",
  "schedulerelationship" : "SCHEDULED",
  "tripstarttime" : "21:30:00",
  "stopid" : "8530B1520901",
  "departuredelay" : "-104",
  "tripid" : "3950_45558",
  "tripschedulerelationship" : "SCHEDULED",
  "tripstartdate" : "20240325",
  "uuid" : "46595e37-4fdd-48db-8431-216bcabe4dd7",
  "departuretime" : "",
  "tripdirectionid" : "0",
  "arrivaltime" : "",
  "arrivaldelay" : "-104",
  "triprouteid" : "3950_62756",
  "ts" : "1711476673867",
  "route_long_name" : "Dublin - Airport - Cavan - Donegal",
  "stop_name" : "Topaz Belleek"
}

Trip Update Slack Message

Irish Transit Tracking Trip Updates
Request ${invokehttp.request.url} ${invokehttp.status.message} ${invokehttp.tx.id}
IDs ${uuid} 
Arrival Delay / Time: ${arrivaldelay} / ${arrivaltime}
Departure Delay / Time: ${departuredelay} / ${departuretime}
Schedule: ${schedulerelationship} ${tripschedulerelationship}
Stop ID/Sequence: ${stopid} / ${stopsequence}
Trip Direction: ${tripdirectionid} ${tripid}
Trip Route: ${triprouteid}
Trip Start Date / Time / TS: ${tripstartdate} / ${tripstarttime} / ${triptimestamp}

Create Table in Flink

Query Kafka Topic — Flink SQL Table in SSB

Installing CSP Community Edition
You need to access the Downloads Page of Cloudera Stream Processing (CSP) to download the Community Edition version of…docs.cloudera.com

Send Messages

Lookups From Postgresql Table

Finally Send Messages to Slack

stop_idUnique ID

Reference - General Transit Feed Specification
This document defines the format and structure of the files that comprise a GTFS dataset. The key words "MUST", "MUST…gtfs.org

Primary key (trip_id, stop_sequence)

Reference - General Transit Feed Specification
This document defines the format and structure of the files that comprise a GTFS dataset. The key words "MUST", "MUST…gtfs.org

DUBLIN BIKES

data.smartdublin.ie
Edit descriptiondata.smartdublin.ie

RAILROAD

IRISH STATIONS

{"StationDesc":"Millstreet","StationAlias":null,
"StationLatitude":52.0776,"StationLongitude":-9.06973,
"StationCode":"MLSRT","StationId":24,"ts":"1711496919762",
"uuid":"f6e71a76-41cc-4a8e-8795-323c3b43d62f"}

IRISH TRAIN RECORD

{
"TrainStatus":"R","TrainLatitude":53.4169,
"TrainLongitude":-6.1512,"TrainCode":"P617",
"TrainDate":"27 Mar 2024",
"PublicMessage":"P617\\n16:02 - Drogheda to Dublin Pearse (1 mins late)\\nDeparted Portmarnock next stop Dublin Connolly",
"Direction":"Southbound","ts":"1711557932947",
"uuid":"b485cefb-67e8-482d-86ba-1ca43e0b523a"
}

IRISH STATION RECORD

{
"StationDesc":"Midleton",
"StationAlias":null,
"StationLatitude":51.9212,
"StationLongitude":-8.17579,
"StationCode":"MDLTN",
"StationId":68,
"ts":"1711558009615",
"uuid":"1f5ae394-4726-4f3e-8e53-7f50f95ae05e"
}

SOURCE CODE

GitHub - tspannhw/FLaNK-IrelandTransit: Transit in Ireland
Transit in Ireland. Contribute to tspannhw/FLaNK-IrelandTransit development by creating an account on GitHub.github.com

FLINK SQL KAFKA TABLE

CREATE TABLE `ssb`.`Meetups`.`irelandvehicle` (
  `recordid` VARCHAR(2147483647),
  `route_id` VARCHAR(2147483647),
  `directionid` VARCHAR(2147483647),
  `latitude` VARCHAR(2147483647),
  `tripid` VARCHAR(2147483647),
  `starttime` VARCHAR(2147483647),
  `vehicleid` VARCHAR(2147483647),
  `startdate` VARCHAR(2147483647),
  `uuid` VARCHAR(2147483647),
  `longitude` VARCHAR(2147483647),
  `timestamp` VARCHAR(2147483647),
  `ts` VARCHAR(2147483647),
  `route_long_name` VARCHAR(2147483647),
  `trip_short_name` VARCHAR(2147483647),
  `trip_headsign` VARCHAR(2147483647),
  `eventTimeStamp` TIMESTAMP(3) WITH LOCAL TIME ZONE METADATA FROM 'timestamp',
  WATERMARK FOR `eventTimeStamp` AS `eventTimeStamp` - INTERVAL '3' SECOND
) WITH (
  'scan.startup.mode' = 'group-offsets',
  'deserialization.failure.policy' = 'ignore_and_log',
  'properties.request.timeout.ms' = '120000',
  'properties.auto.offset.reset' = 'earliest',
  'format' = 'json',
  'properties.bootstrap.servers' = 'kafka:9092',
  'connector' = 'kafka',
  'properties.transaction.timeout.ms' = '900000',
  'topic' = 'irelandvehicle',
  'properties.group.id' = 'irelandconsumersbb1'
)