citydata-mesaaz-gov/parks-locations-and-amenities-djym-pkpp

  • map
  • parks
  • places
  • pools
  • recreation

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 procotol. 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 parks_locations_and_amenities table in this repository, by referencing it like:

"citydata-mesaaz-gov/parks-locations-and-amenities-djym-pkpp:latest"."parks_locations_and_amenities"

or in a full query, like:

SELECT 
    ":id", -- Socrata column ID
    "street_number", -- The street number of the park or basin address.
    "street_name", -- The street name of the park or basin address.
    "longitude", -- The longitude for the park or basin
    "location_address",
    "street_type", -- The street type of the park or basin address.
    "basketball", -- Does the Park have basketball courts and if so, how many and are they lighted.
    "ramada", -- Does the park have a ramada, and if so is can it be reserved. Is it shaded.
    "horsehoes", -- Does the park have horseshoe pits
    "volleyball", -- Does the park have volleyball courts, and if so how many, what type and are they lighted.
    "restroom", -- Does the park have restroom facilities
    "barbecue_grills", -- Does the park have barbecue grills
    "picnic_tables", -- Does the park have picnic tables, and if so are they shaded
    "lake", -- Does the park have a lake amenity
    "baseball", -- Does the park have baseball fields, and if so how many, what type and are they lighted
    "raquetball", -- Does this park have racquetball courts and if so, are they lighted.
    "trails", -- Does the park have walking or hiking trails
    "playground", -- Does the park have playground amenities, and if so are they shaded.
    "splashpad", -- Does the park have a splash pad amenity, and if so is it shaded.
    "bleachers", -- Are there bleacher amenities at this park
    "pickelball", -- Does this park have pickelball courts and if so, are they lighted.
    "tennis", -- Does this park have tennis courts and if so, are they lighted.
    "name", -- Name of Park or Basin
    "facility_id", -- Unique identifier for each park or basin. Parks are indicated by PKPK followed by a number, Basins are indicated by PKBN followed be a number. 
    "location_state",
    ":@computed_region_fcpr_wj2n",
    "park_site_map", -- Link to additional information about the park, may include a site map
    "dog_area", -- Does this park have a designated dog area
    "soccer", -- Does the park have soccer fields, and if so how many and are they lighted
    "street_direction", -- The street direction of the park or basin address.
    "disc_golf", -- Does this park have disc golf amenities
    "exercise_course", -- Does this park have a designated exercise course amenity
    "city", -- City where the park or basin is located
    "latitude", -- The latitude for the park or basin
    "location_zip",
    "location_city",
    "location", -- Geo coded location of the park or basin
    "type", -- Is the facility a park or basin. Basins are undeveloped green spaces managed by the city. Typically used for community water drainage and/or retention basins.
    "number_of_acres", -- Estimated number of acres 
    "full_address" -- The street address for the park or basin
FROM
    "citydata-mesaaz-gov/parks-locations-and-amenities-djym-pkpp:latest"."parks_locations_and_amenities"
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 citydata-mesaaz-gov/parks-locations-and-amenities-djym-pkpp with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at citydata.mesaaz.gov. When you querycitydata-mesaaz-gov/parks-locations-and-amenities-djym-pkpp: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 citydata.mesaaz.gov, 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 \
  "citydata-mesaaz-gov/parks-locations-and-amenities-djym-pkpp" \
  --handler-options '{
    "domain": "citydata.mesaaz.gov",
    "tables": {
        "parks_locations_and_amenities": "djym-pkpp"
    }
}'

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, citydata-mesaaz-gov/parks-locations-and-amenities-djym-pkpp is just another Postgres schema.

Related Documentation: