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 mta_subway_stations table in this repository, by referencing it like:
"ny-gov/mta-subway-stations-39hk-dx4f:latest"."mta_subway_stations"or in a full query, like:
SELECT
":id", -- Socrata column ID
"south_direction_label", -- The southbound direction for lines stopping at the station, such as Downtown & Brooklyn, Canarsie - Rockaway Parkway, and Brighton Beach & Coney Island. This is blank if the station is the southern terminal of a line.
"gtfs_longitude", -- The longitude for the centroid of the station
"gtfs_latitude", -- The latitude for the centroid of the station
"complex_id", -- The Complex Master Reference Number.
"gtfs_stop_id", -- The ID used for the station in the General Transit Feed Specification (GTFS), an open standard used to display public transit schedule data.
"georeference", -- Open Data platform-generated geocoding information from supplied address components. Point-type location is the centroid of the address components provided and does not reflect a specific address if the street address component is not provided. Point-type location is supplied in "POINT (<geocoded longitude> <geocoded latitude>)" format.
"north_direction_label", -- The northbound direction for lines stopping at the station, such as Astoria - Ditmars Blvd, Uptown & The Bronx, and Manhattan. This is blank if the station is the northern terminal of a line.
"stop_name", -- The name of the subway station.
"ada_southbound", -- 0 if the station is not ADA-accessible in the southbound direction, 1 if the station is fully accessible in the southbound direction
"structure", -- The type of structure the subway station is located on or in (At Grade, Elevated, Embankment, Open Cut, Subway, Viaduct, etc.). For stations part of a complex, this indicates the construction type for that part of the complex only. Some complexes have more than one construction type across their constituent stations.
"daytime_routes", -- The subway routes that serve the station during weekdays.
"cbd", -- This indicates whether or not a station is in Manhattan’s Central Business District (CBD). This value is either TRUE or FALSE.
"ada_northbound", -- 0 if the station is not ADA-accessible in the northbound direction, 1 if the station is fully accessible in the northbound direction
"line", -- The operational line of the subway system the station is located on, such as Queens Blvd, Lexington Av, or Sea Beach.
"ada_notes", -- Notes on the direction a station is accessible in if it is only accessible in one direction, such as Manhattan-bound only, Downtown only, and Uptown & The Bronx local only.
"station_id", -- The Station Master Reference Number.
"borough", -- The borough the station is in. Bx for Bronx, B for Brooklyn, M for Manhattan, Q for Queens, SI for Staten Island.
":@computed_region_yamh_8v7k", -- This column was automatically created in order to record in what polygon from the dataset 'NYS Municipal Boundaries' (yamh-8v7k) the point in column 'georeference' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_wbg7_3whc", -- This column was automatically created in order to record in what polygon from the dataset 'New York Zip Codes' (wbg7-3whc) the point in column 'georeference' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"ada", -- 0 if the station is not ADA-accessible, 1 if the station is fully accessible, 2 if the station is partially accessible.
":@computed_region_kjdx_g34t", -- This column was automatically created in order to record in what polygon from the dataset 'Counties' (kjdx-g34t) the point in column 'georeference' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"division" -- The division of the subway system (IRT, BMT, or IND) that the station is a part of.
FROM
"ny-gov/mta-subway-stations-39hk-dx4f:latest"."mta_subway_stations"
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 ny-gov/mta-subway-stations-39hk-dx4f 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 ny-gov/mta-subway-stations-39hk-dx4f: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 ny-gov/mta-subway-stations-39hk-dx4fCheckout 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 ny-gov/mta-subway-stations-39hk-dx4f:latestThis will download all the objects for the latest tag of ny-gov/mta-subway-stations-39hk-dx4f 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 ny-gov/mta-subway-stations-39hk-dx4f: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 ny-gov/mta-subway-stations-39hk-dx4f: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, ny-gov/mta-subway-stations-39hk-dx4f is just another Postgres schema.