usaid-gov/predict-event-animal-production-pytc-ijy8
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 predict_event_animal_production table in this repository, by referencing it like:

"usaid-gov/predict-event-animal-production-pytc-ijy8:latest"."predict_event_animal_production"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "nhppurposeofproduction", -- The purpose of producing non-human primates.
    "dogsinproduction", -- Are dogs in production at the site?
    "animalwastepresent", -- The types of animal waste present at this event site.
    "cattlepurposeofproduction", -- The purpose of producing cattle/buffalo.
    "horsesinproduction", -- Are horses in production at the site?
    "camelspurposeofproduction", -- The purpose of producing camels.
    "poultrypurposeofproduction", -- The purpose of producing poultry/other fowl.
    "nhpinproduction", -- Are non-human primates in production at the site?
    "batsinproduction", -- Are bats in production at the site?
    "country", -- The name of the country where the sampling occurred.  Is auto assigned by system by linking to the event ID.
    "catspurposeofproduction", -- The purpose of producing cats.
    "dogspurposeofproduction", -- The purpose of producing dogs.
    "swinepurposeofproduction", -- The purpose of producing swine.
    "pangolinspurposeofproduction", -- The purpose of producing pangolins.
    "carnivorespurposeofproduction", -- The purpose of producing carnivores.
    "rodentspurposeofproduction", -- The purpose of the production of rodents/shrews.
    "predict_eventid", -- The numeric key to the event which the animal production data belongs to. This can be used to link this dataset to the Site/EventCharacterization dataset.
    "swineinproduction", -- Are swine in production at the site?
    "horsespurposeofproduction", -- The purpose of producing horses.
    "ungulatesinproduction", -- Are ugulates in production at the site?
    "batspurposeofproduction", -- The purpose of producing bats.
    "birdsinproduction", -- Are birds in production at the site?
    "birdspurposeofproduction", -- The purpose of producing birds.
    "goatspurposeofproduction", -- The purpose of producing goats/sheep.
    "wilddomestictogether", -- Are wild and domestic animals held together in one cage?
    "catsinproduction", -- Are cats in production at the site?
    "biosecuritymeasures", -- The types of biosecurity measures are practised at this site.
    "camelsinproduction", -- Are camels in production at the site?
    "goatsinproduction", -- Are goats/sheep in production at the site?
    "pangolinsinproduction", -- Are pangolins in production at the site?
    "ungulatespurposeofproduction", -- The purpose of producing ungulates.
    "rodentsinproduction", -- Are rodents/shrews in production at the site?
    "cattleinproduction", -- Are cattle/buffalo in production at the site?
    "typeofproduction", -- The type of production system at the site.
    "poultryinproduction", -- Are poultry/other fowl in production at the site?
    "taxatogether", -- Are there multiple taxa in one holding area or cage?
    "animalsindwellings", -- Are there animals living in the human dwellings?
    "carnivoresinproduction" -- Are carnivores in production at the site?
FROM
    "usaid-gov/predict-event-animal-production-pytc-ijy8:latest"."predict_event_animal_production"
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 usaid-gov/predict-event-animal-production-pytc-ijy8 with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.usaid.gov. When you queryusaid-gov/predict-event-animal-production-pytc-ijy8: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)"
 

Read the installation docs.

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.usaid.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 \
  "usaid-gov/predict-event-animal-production-pytc-ijy8" \
  --handler-options '{
    "domain": "data.usaid.gov",
    "tables": {
        "predict_event_animal_production": "pytc-ijy8"
    }
}'

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, usaid-gov/predict-event-animal-production-pytc-ijy8 is just another Postgres schema.