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 broadband_adoption_and_infrastructure_by table in this repository, by referencing it like:
"cityofnewyork-us/broadband-adoption-and-infrastructure-by-3kx3-7svp:latest"."broadband_adoption_and_infrastructure_by"or in a full query, like:
SELECT
":id", -- Socrata column ID
"no_mobile_broadband_adoption_1", -- Percentage of Households in the neighborhood without a cellular data plan internet service subscription by quartile.
"commercial_fiber_max_isp", -- The maximum number of commercial fiber internet service providers reported to be available per census block by council district; Fiber is short for Fiber Optic Technology. Fiber transmits data at speeds far exceeding current DSL or cable modem speeds, typically by tens or even hundreds of Mbps. Commercial Fiber is based on the Federal Communications Commissions Form 477 data. Commercial Fiber is defined as where a Provider can or does offer business/government service in the block and also offers fiber to business end user.
"mobile_broadband_adoption", -- Percentage of Households in the neighborhood with a cellular data plan internet service subscription.
"no_mobile_broadband_adoption", -- Percentage of Households in the neighborhood without a cellular data plan internet service subscription.
"no_home_broadband_adoption", -- Percentage of Households without a broadband internet service subscription; The Federal Communications Commission (FCC) sets a standard for “broadband” as an internet service with a download speed of at least 25 megabits per second (Mbps) and an upload speed of at least 3 Mbps.
"density_of_poles_reserved", -- Total poles, reserved by Mobile Telecom Franchisee with or without equipment installed, per street mile in the NTA.
"pole_with_equipment_installed", -- Poles in use for the Mobile Telecom Franchise, with equipment installed.
"oid", -- Origin Identification Number
"workstations_in_pccs", -- Number of computer workstations, defined as desktop or laptop computers, available for public use at the center
"public_computer_center_count", -- Total Number of Public Computer Centers
"home_broadband_adoption", -- Percentage of Households with a broadband internet service subscription by neighborhood.; The Federal Communications Commission (FCC) sets a standard for “broadband” as an internet service with a download speed of at least 25 megabits per second (Mbps) and an upload speed of at least 3 Mbps.
"no_internet_access_percentage", -- Percentage of Households without access to an internet service; The American Community Survey frames this questions as having "No access to the internet at this house, apartment, or mobile home."
"poles_reserved_by_mobile", -- Poles that the City has reserved for use for the Mobile Telecommunications Franchise, without equipment installed.
"public_wi_fi_count", -- Indicates the number of public Wi-Fi access points within the specified NTA.
"avg_training_hrs_per_week", -- Average number of hours per week that the center provides digital literacy training programs.
"congressional_district", -- New York City area Congressional District name; Boundaries of Congressional Districts
"no_home_broadband_adoption_1" -- Percentage of Households without a broadband internet service subscription by quartile.
FROM
"cityofnewyork-us/broadband-adoption-and-infrastructure-by-3kx3-7svp:latest"."broadband_adoption_and_infrastructure_by"
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/broadband-adoption-and-infrastructure-by-3kx3-7svp 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/broadband-adoption-and-infrastructure-by-3kx3-7svp: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/broadband-adoption-and-infrastructure-by-3kx3-7svpCheckout 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/broadband-adoption-and-infrastructure-by-3kx3-7svp:latestThis will download all the objects for the latest tag of cityofnewyork-us/broadband-adoption-and-infrastructure-by-3kx3-7svp 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/broadband-adoption-and-infrastructure-by-3kx3-7svp: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/broadband-adoption-and-infrastructure-by-3kx3-7svp: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/broadband-adoption-and-infrastructure-by-3kx3-7svp is just another Postgres schema.