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Apache Pinot
Datasets
OpenSky

OpenSky

This dataset contains cleaned data from the OpenSky dataset, which was compiled to illustrate how air traffic was affected by the COVID-19 pandemic. It spans a variety of flights from 2019 until 2022. You can learn more about the dataset at Crowdsourced air traffic data from The OpenSky Network 2020 (opens in a new tab).

Prerequisites

To follow the code examples in this guide, you must install Docker (opens in a new tab) locally and download recipes.

Navigate to recipe

  1. If you haven't already, download recipes.
  2. In terminal, go to the recipe by running the following command:
cd pinot-recipes/recipes/opensky-dataset

Download flight data

The dataset contains .csv.gz files with flight data from the start of 2019 until the end of 2022. You will need to download at least one of these files from https://zenodo.org/record/7923702 (opens in a new tab), unpack it, and then put the resulting CSV file(s) into the data directory.

Launch Pinot Cluster

You can spin up a Pinot Cluster by running the following command:

 
docker compose up

This command will run a single instance of the Pinot Controller, Pinot Server, Pinot Broker, and Zookeeper. You can find the docker-compose.yml (opens in a new tab) file on GitHub.

Pinot Schema and Table

Now let's create a Pinot Schema and Table.

First, the schema:

{
    "schemaName": "flights",
    "dimensionFieldSpecs": [
      {
        "name": "callsign",
        "dataType": "STRING"
      },
      {
        "name": "number",
        "dataType": "STRING"
      },
      {
        "name": "icao24",
        "dataType": "STRING"
      },
      {
        "name": "registration",
        "dataType": "STRING"
      },
      {
        "name": "typecode",
        "dataType": "STRING"
      },
      {
        "name": "origin",
        "dataType": "STRING"
      },
      {
        "name": "destination",
        "dataType": "STRING"
      },
      {
        "name": "latitude_1",
        "dataType": "FLOAT"
      },
      {
        "name": "longitude_1",
        "dataType": "FLOAT"
      },
      {
        "name": "altitude_1",
        "dataType": "FLOAT"
      },
      {
        "name": "latitude_2",
        "dataType": "FLOAT"
      },
      {
        "name": "longitude_2",
        "dataType": "FLOAT"
      },
      {
        "name": "altitude_2",
        "dataType": "FLOAT"
      }
    ],
    "dateTimeFieldSpecs": [
      {
        "name": "firstSeen",
        "dataType": "TIMESTAMP",
        "format": "1:MILLISECONDS:EPOCH",
        "granularity": "1:MILLISECONDS"
      },
      {
        "name": "lastSeen",
        "dataType": "TIMESTAMP",
        "format": "1:MILLISECONDS:EPOCH",
        "granularity": "1:MILLISECONDS"
      },
      {
        "name": "daySeen",
        "dataType": "TIMESTAMP",
        "format": "1:MILLISECONDS:EPOCH",
        "granularity": "1:MILLISECONDS"
      }
    ],
    "metricFieldSpecs": [
 
    ]
  }

config/schema.json

We'll also have the following table config:

{
    "tableName": "flights",
    "tableType": "OFFLINE",
    "segmentsConfig": {
      "replication": 1,
      "schemaName": "flights",
      "timeColumnName": "firstSeen"
    },
    "tenants": {},
    "tableIndexConfig": {},
    "ingestionConfig": {
        "transformConfigs": [
          {"columnName": "firstSeen", "transformFunction": "FromDateTime(firstseen, 'YYYY-MM-dd HH:mm:ssZ')" },
          {"columnName": "lastSeen", "transformFunction": "FromDateTime(lastseen, 'YYYY-MM-dd HH:mm:ssZ')" },
          {"columnName": "daySeen", "transformFunction": "FromDateTime(day, 'YYYY-MM-dd HH:mm:ssZ')" }
        ],
        "filterConfig": {
            "filterFunction": "strcmp(coalesce(origin, ''), '') = 0 OR strcmp(coalesce(destination, ''), '') = 0"
          }
      },
    
    "metadata": {}
  }

config/table.json

You can create the table and schema by running the following command:`

docker run \
   --network opensky \
   -v $PWD/config:/config \
   apachepinot/pinot:1.0.0 AddTable \
     -schemaFile /config/schema.json \
     -tableConfigFile /config/table.json \
     -controllerHost "pinot-controller-opensky" \
    -exec

Ingesting CSV files

We're going to use Pinot's SQL insert syntax to import the CSV files. Navigate to the Pinot UI (opens in a new tab) and click on Query Console You can then run the following query to run the ingestion job:

SET taskName = 'flights-dataload';
SET input.fs.className = 'org.apache.pinot.spi.filesystem.LocalPinotFS';
SET includeFileNamePattern='glob:**/*.csv';
INSERT INTO flights 
FROM FILE 'file:///data/';

Wait a few minutes for the job to complete. You can check on the status by navigating to the Minion Task Manager (opens in a new tab) page.

Querying the dataset

Once the data is loaded, we can run some queries:

select origin as airport, count(*)
from flights
group by airport
order by count(*) DESC
limit 10
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