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 waste_tire_abatement_sites table in this repository, by referencing it like:
"ny-gov/waste-tire-abatement-sites-dapt-ejhb:latest"."waste_tire_abatement_sites"or in a full query, like:
SELECT
":id", -- Socrata column ID
"status", -- Site abatement status.
"county", -- County where the site is located.
"dec_region", -- DEC Region where the site is located. Regions are defined as follows: 1 = Nassau & Suffolk counties; 2 = New York City; 3 = Dutchess, Orange, Putnam, Rockland, Sullivan, Ulster &Westchester; 4 = Albany, Columbia, Delaware, Greene, Montgomery, Otsego, Rensselaer, Schenectady & Schoharie; 5 = Clinton, Essex, Franklin, Fulton, Hamilton, Saratoga, Warren & Washington; 6 = Herkimer, Jefferson, Lewis, Oneida & St. Lawrence; 7 = Broome, Cayuga, Chenango, Cortland, Madison, Onondaga, Oswego, Tioga & Tompkins; 8 = Chemung, Genesee, Livingston, Monroe, Ontario, Orleans, Schuyler, Seneca, Steuben, Wayne & Yates; 9 = Allegany, Cattaraugus, Chautauqua, Erie, Niagara & Wyoming
"stream", -- Denotes whether the site is within 250 meters of a stream which is suitable for fish propagation and survival, and for primary and secondary contact recreational uses.
"primary_aquifer", -- Denotes whether the site is over a productive aquifer which is presently used as a source of public water supply by major municipal water supply systems.
"est_number_of_tires", -- The estimated number of tires at the site. If blank, the number of tires is unknown.
"noncompliant_site_name", -- Name of the site
"city_town", -- City or town where site is located.
"school", -- Denotes whether the site is within 1 kilometer of a school, using data from the NYS Dept. of Education containing primary public and private schools.
"site_id", -- Site identification number
"latitude", -- Latitude value corresponding to easting coordinate for GIS mapping.
"wetland", -- Denotes whether the site within 250 meters of a wetland that is regulated under NYS Freshwater Wetlands Act outside the Adirondack Park.
"population_center", -- Denotes whether the facility is within 1 kilometer of an area with a population density of 1,000 individuals or greater per square kilometer.
"hospital", -- Denotes whether the site is within 1 kilometer of a hospital, based on Data provided by NYS Dept. of Health containing acute care facilities licensed by the NYS Dept. of Health and covered by Article 28. It does not include psychiatric or federal hospitals.
"environmental_justice_areas", -- Denotes whether the site is within or immediately adjacent to a census block group that exceeds specific thresholds for poverty and minority composition using 2000 census data as specified in Commissioner Policy #29 (https://www.dec.ny.gov/regulations/36951.html).
":@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.
":@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.
":@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.
"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.
"longitude" -- Longitude value corresponding to northing coordinate for GIS mapping.
FROM
"ny-gov/waste-tire-abatement-sites-dapt-ejhb:latest"."waste_tire_abatement_sites"
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/waste-tire-abatement-sites-dapt-ejhb 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/waste-tire-abatement-sites-dapt-ejhb: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/waste-tire-abatement-sites-dapt-ejhbCheckout 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/waste-tire-abatement-sites-dapt-ejhb:latestThis will download all the objects for the latest tag of ny-gov/waste-tire-abatement-sites-dapt-ejhb 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/waste-tire-abatement-sites-dapt-ejhb: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/waste-tire-abatement-sites-dapt-ejhb: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/waste-tire-abatement-sites-dapt-ejhb is just another Postgres schema.