Query the Data Delivery Network
Query the DDNThe 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:
"datahub-usaid-gov/predict-event-animal-production-pytc-ijy8:latest"."predict_event_animal_production"or in a full query, like:
SELECT
":id", -- Socrata column ID
"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.
"goatspurposeofproduction", -- The purpose of producing goats/sheep.
"birdspurposeofproduction", -- The purpose of producing birds.
"birdsinproduction", -- Are birds in production at the site?
"batspurposeofproduction", -- The purpose of producing bats.
"ungulatesinproduction", -- Are ugulates in production at the site?
"horsespurposeofproduction", -- The purpose of producing horses.
"swineinproduction", -- Are swine in production at the site?
"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?
"poultryinproduction", -- Are poultry/other fowl in production at the site?
"taxatogether", -- Are there multiple taxa in one holding area or cage?
"carnivoresinproduction", -- Are carnivores in production at the site?
"dogsinproduction", -- Are dogs in production at the site?
"typeofproduction", -- The type of production system at the site.
"animalsindwellings", -- Are there animals living in the human dwellings?
"nhppurposeofproduction" -- The purpose of producing non-human primates.
FROM
"datahub-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 datahub-usaid-gov/predict-event-animal-production-pytc-ijy8 with SQL in under 60 seconds.
Query Your Local Engine
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, 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 (like this repository), where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.
Cloning Data
Because datahub-usaid-gov/predict-event-animal-production-pytc-ijy8:latest is a Splitgraph Image, you can clone the data from Spltgraph Cloud to your local engine, where you can query it like any other Postgres database, using any of your existing tools.
First, install Splitgraph if you haven't already.
Clone the metadata with sgr clone
This will be quick, and does not download the actual data.
sgr clone datahub-usaid-gov/predict-event-animal-production-pytc-ijy8Checkout the data
Once you've cloned the data, you need to "checkout" the tag that you want. For example, to checkout the latest tag:
sgr checkout datahub-usaid-gov/predict-event-animal-production-pytc-ijy8:latestThis will download all the objects for the latest tag of datahub-usaid-gov/predict-event-animal-production-pytc-ijy8 and load them into the Splitgraph Engine. Depending on your connection speed and the size of the data, you will need to wait for the checkout to complete. Once it's complete, you will be able to query the data like you would any other Postgres database.
Alternatively, use "layered checkout" to avoid downloading all the data
The data in datahub-usaid-gov/predict-event-animal-production-pytc-ijy8:latest is 0 bytes. If this is too big to download all at once, or perhaps you only need to query a subset of it, you can use a layered checkout.:
sgr checkout --layered datahub-usaid-gov/predict-event-animal-production-pytc-ijy8:latestThis will not download all the data, but it will create a schema comprised of foreign tables, that you can query as you would any other data. Splitgraph will lazily download the required objects as you query the data. In some cases, this might be faster or more efficient than a regular checkout.
Read the layered querying documentation to learn about when and why you might want to use layered queries.
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, datahub-usaid-gov/predict-event-animal-production-pytc-ijy8 is just another Postgres schema.