melbourne-vic-gov-au/onstreet-car-parking-sensor-data-2018-5532-ig9r
Icon for Socrata external plugin

Query the Data Delivery Network

Query the DDN

The easiest way to query any data on Splitgraph is via the "Data Delivery Network" (DDN). The DDN is a single endpoint that speaks the PostgreSQL wire protocol. Any Splitgraph user can connect to it at data.splitgraph.com:5432 and query any version of over 40,000 datasets that are hosted or proxied by Splitgraph.

For example, you can query the onstreet_car_parking_sensor_data_2018 table in this repository, by referencing it like:

"melbourne-vic-gov-au/onstreet-car-parking-sensor-data-2018-5532-ig9r:latest"."onstreet_car_parking_sensor_data_2018"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "sign", -- Parking sign in effect at the time of the parking event.
    "streetid", -- A GIS key that describes the street segment where the sensor is located. A street segment is the section of street, between two 
    "streetname", -- Street upon which the vehicle parked.
    "betweenstreet2", -- Closest Intersecting street with the street parked on. Ideally the next one in front of the parked vehicle.
    "sidename", -- Side Of Street name
    "signplateid", -- Parking sign id that was in effect at the time of the parking event.
    "inviolation", -- True = In violation False  = Not in violation
    "areaname", -- City area - used for administrative purposes.
    "bayid", -- The unique ID of the bay that the even occurred
    "streetmarker", -- The street marker that is located next to the parking bay with a unique id for the bay. Often a small round, metal plaque found on the pavement next to the bay.
    "sideofstreet", -- Side of the street on which the parking event occurred. 1 = Centre 2 = North 3 = East 4 = South 5 = West
    "durationminutes", -- Time difference between arrival and departure events (measured in minutes).
    "departuretime", -- Date & Time that the sensor detected a vehicle no longer located over it.
    "arrivaltime", -- Date & Time that the sensor detected a vehicle located over it.
    "betweenstreet1id", -- Closest Intersecting street ID with the street parked on. Ideally the next one in front of the parked vehicle.
    "betweenstreet1", -- Closest Intersecting street with the street parked on. Ideally the next one in front of the parked vehicle.
    "betweenstreet2id", -- Closest Intersecting street ID with the street parked on. Ideally the next one in front of the parked vehicle.
    "vehiclepresent", -- True = Vehicle present False = Vehicle not present
    "deviceid" -- Serial number of the in-ground sensor.
FROM
    "melbourne-vic-gov-au/onstreet-car-parking-sensor-data-2018-5532-ig9r:latest"."onstreet_car_parking_sensor_data_2018"
LIMIT 100;

Connecting to the DDN is easy. All you need is an existing SQL client that can connect to Postgres. As long as you have a SQL client ready, you'll be able to query melbourne-vic-gov-au/onstreet-car-parking-sensor-data-2018-5532-ig9r with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.melbourne.vic.gov.au. When you querymelbourne-vic-gov-au/onstreet-car-parking-sensor-data-2018-5532-ig9r:latest on the DDN, we "mount" the repository using the socrata mount handler. The mount handler proxies your SQL query to the upstream data source, translating it from SQL to the relevant language (in this case SoQL).

We also cache query responses on the DDN, but we run the DDN on multiple nodes so a CACHE_HIT is only guaranteed for subsequent queries that land on the same node.

Query Your Local Engine

Install Splitgraph Locally
bash -c "$(curl -sL https://github.com/splitgraph/splitgraph/releases/latest/download/install.sh)"
 

Splitgraph Cloud is built around Splitgraph Core (GitHub), which includes a local Splitgraph Engine packaged as a Docker image. Splitgraph Cloud is basically a scaled-up version of that local Engine. When you query the Data Delivery Network or the REST API, we mount the relevant datasets in an Engine on our servers and execute your query on it.

It's possible to run this engine locally. You'll need a Mac, Windows or Linux system to install sgr, and a Docker installation to run the engine. You don't need to know how to actually use Docker; sgrcan manage the image, container and volume for you.

There are a few ways to ingest data into the local engine.

For external repositories (like this repository), the Splitgraph Engine can "mount" upstream data sources by using sgr mount. This feature is built around Postgres Foreign Data Wrappers (FDW). You can write custom "mount handlers" for any upstream data source. For an example, we blogged about making a custom mount handler for HackerNews stories.

For hosted datasets, where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.

Mounting Data

This repository is an external repository. It's not hosted by Splitgraph. It is hosted by data.melbourne.vic.gov.au, and Splitgraph indexes it. This means it is not an actual Splitgraph image, so you cannot use sgr clone to get the data. Instead, you can use the socrata adapter with the sgr mount command. Then, if you want, you can import the data and turn it into a Splitgraph image that others can clone.

First, install Splitgraph if you haven't already.

Mount the table with sgr mount

sgr mount socrata \
  "melbourne-vic-gov-au/onstreet-car-parking-sensor-data-2018-5532-ig9r" \
  --handler-options '{
    "domain": "data.melbourne.vic.gov.au",
    "tables": {
        "onstreet_car_parking_sensor_data_2018": "5532-ig9r"
    }
}'

That's it! Now you can query the data in the mounted table like any other Postgres table.

Query the data with your existing tools

Once you've loaded the data into your local Splitgraph engine, you can query it with any of your existing tools. As far as they're concerned, melbourne-vic-gov-au/onstreet-car-parking-sensor-data-2018-5532-ig9r is just another Postgres schema.

Related Documentation: