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 parks_closure_status_due_to_covid19_athletic table in this repository, by referencing it like:
"cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbc:latest"."parks_closure_status_due_to_covid19_athletic"or in a full query, like:
SELECT
":id", -- Socrata column ID
"dimensions", -- The dimensions of the Athletic Facility
"borough", -- Borough in which the athletic facility is located.
"name", -- The name of the Athletic Facility
"system", -- Internal unique identifier for the Athletic Facility
"primarysport", -- The main usage sport for the athletic facility, the sport it was designed or is maintained for
"propertyname", -- The name of the property the Athletic Facility is within
"approx_date_reopened", -- Date Athletic Facility reopened from Covid closure
"closuretype", -- Indicates the type of closure
"nets_rims_goals_removed", -- Indicates whether the nets, rims, or goals were removed from the facility
"yellow_sign_removed", -- Indicates whether a yellow sign dictating no group play was removed
"approx_date_closed", -- Approximate date Athletic Facility closed because of Covid
"surfacetype", -- The playing surface of the Athletic Facility
"subpropertyname", -- The Name of the subproperty (Zone or Playground) that the feature falls within
"nets_rims_goals_added", -- Indicates whether nets, rims, or goals were added back to an athletic facility
"fieldnumber", -- The number of the athletic facility, if a field has a physical sign with a number on it, this is that number, but not all fields have physical signs
"omppropid", -- Unique identification number for a property or portion of a property. In some cases – a standalone, smaller park for example – this number will be equivalent to the GIS Property Number. In other cases – a zone, playground or other site within a larger park – an additional designation of letters and/or numbers will be added.
"cemspermittable", -- Indicates whether the Athoetic Facility is available for permitting through the Citywide Event Management System (CEMS)
"polygon", -- Location (POLYGON) of athletic facility
"red_sign_installed", -- Indicates whether a red closed sign was installed
"status", -- Indicates whether the athletic facility is still active and open to the public, has been closed to observe COVID-19 social distancing, has been reopened following COVID-19 closure, or is under construction.
"editdate", -- Last edited date
"parkdistrict", -- Name of the Parks maintenance district that contains the Athletic Facility.
"gispropnum", -- Unique identification number for the property the Athletic Facility is within
"approx_date_nets_rims_goals_added" -- Indicates date of reinstallation of net, rim, or goal to an athletic facility
FROM
"cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbc:latest"."parks_closure_status_due_to_covid19_athletic"
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 cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbc 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 cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbc: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 cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbcCheckout 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 cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbc:latestThis will download all the objects for the latest tag of cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbc 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 cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbc: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 cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbc: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, cityofnewyork-us/parks-closure-status-due-to-covid19-athletic-g3xg-qtbc is just another Postgres schema.