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 individual_landmark_sites table in this repository, by referencing it like:
"cityofnewyork-us/individual-landmark-sites-buis-pvji:latest"."individual_landmark_sites"or in a full query, like:
SELECT
":id", -- Socrata column ID
"lot", -- The four digit tax map lot number, without leading zeros (ex. Lot 0456 appears as 456).
"lpc_name", -- Name of designated individual landmark.
"address", -- The address of the building or structure as written in the designation report.
"shape_area",
"lpc_altern", -- The "A.K.A." name of a designated individual landmark.
"shape_leng",
"borough", -- Borough expressed as a two-character abbreviation (MN=Manhattan, BX=Bronx, BK=Brooklyn, QN=Queens, and SI=Staten Island).
"bbl", -- Concatenation of the borough code (1=MN, 2=BX,3=BK,4=QN,5=SI), the five-digit tax map block, and the four-digit tax map lot numbers (ex. Manhattan Tax Map Block 123 Lot 45 would appear as 1001230045). Note: numbers in this field are not auto-updated and so some may be outdated. Because this file contains both building and non-building landmarks (such as monuments or vacant lots) as well as some landmarks not located on tax map lots (such as bridges), some records display “dummy” BBLs. The following BBLs serve only as “dummy” BBLs: 1000000000, 2000000000, 3000000000, 4000000000, 5000000000.
"the_geom", -- Geometry column
"block", -- The five-digit tax map block number, without leading zeros (ex. Block 00123 appears as 123).
"desdate", -- "Date of designation (the day the Landmarks Preservation Commission voted to designate as an Individual Landmark). "
"objectid", -- GIS-determined unique identifier.
"lpc_lpnumb", -- Internal LPC identifier (LP-XXXXX) used to identify a single designation (one LP number is assigned per Historic District, Individual, Scenic, or Interior Landmark).
"landmarkty", -- Type of landmark. This data set only looks at Individual Landmarks of the four types of landmarks used by the LPC.
"lpc_sitede", -- Description of landmark site. If the field says "too long," please refer to the associated designation report for the description.
"lpc_sitest",
"url_report" -- Link to LPC designation report for property.
FROM
"cityofnewyork-us/individual-landmark-sites-buis-pvji:latest"."individual_landmark_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 cityofnewyork-us/individual-landmark-sites-buis-pvji 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/individual-landmark-sites-buis-pvji: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/individual-landmark-sites-buis-pvjiCheckout 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/individual-landmark-sites-buis-pvji:latestThis will download all the objects for the latest tag of cityofnewyork-us/individual-landmark-sites-buis-pvji 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/individual-landmark-sites-buis-pvji: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/individual-landmark-sites-buis-pvji: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/individual-landmark-sites-buis-pvji is just another Postgres schema.