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 nyc_citywide_annualized_calendar_sales_update table in this repository, by referencing it like:
"cityofnewyork-us/nyc-citywide-annualized-calendar-sales-update-w2pb-icbu:latest"."nyc_citywide_annualized_calendar_sales_update"or in a full query, like:
SELECT
":id", -- Socrata column ID
"apartment_number",
"tax_class_as_of_final_roll", -- Present Tax Class. Every property in the city is assigned to one of four tax classes (Classes 1,2, 3, and 4) based on the use of the property; See Data dictionary for more detail
"neighborhood", -- DOF assessors determine the neighborhood name in the course of valuing properties.
"borough", -- The name of the borough in which the property is located
"building_class_as_of_final", -- The building classification is used to describe a property's constructive use; See Data dictionary for more detail
"lot", -- A tax Lot is a subdivision of a tax Block and represents the property unique location
"block", -- A Tax Block is a sub-division of the borough on which real properties are located
"bin", -- The BIN (Building Identification Number) is a unique identifier for each building in the City.
"bbl", -- The BBL (Borough, Block, and Lot) is a unique identifier for each tax lot in the City.
"census_tract_2020",
"address", -- The street address of the property as listed on the Sales File. Coop sales include the apartment in the address field
"nta_code",
"commercial_units", -- The number of commercial units at the listed property
"building_class_category", -- This identifies properties broad usage (e.g. One Family Home).
"nta", -- The Neighborhood Tabulation Area field indicates the New York City Neighborhood area where the building is located.
"council_district", -- The Council District field indicates the New York City Council District where the building is located.
"community_board", -- The Community Board field indicates the New York City Community District where the building is located.
"longitude", -- Longitude of the building's location.
"latitude", -- Latitude of the building's location.
"sale_price", -- Price paid for the property
"building_class_at_time_of", -- The building classification at the time of sale
"gross_square_feet", -- The total area of all e floors of a building as measured from the exterior surfaces of the outside walls of the building , including the land area and space within any building structure on the property
"total_units", -- The total number of units at the listed property
"census_tract", -- The Census Tract field indicates the U.S. Census Tract where the building is located.
"sale_date", -- A $0 sale price indicates that there was a transfer of ownership without a cash consideration.
"tax_class_at_time_of_sale", -- Tax Class at time of sale
"year_built", -- Year the structure on the property was built.
"land_square_feet", -- The land are of the property listed in square feet
"residential_units", -- The number of residential units at the listed property
"zip_code", -- The property's postal code
"ease_ment" -- An easement is a right, such as a right of way, which allows an entity to make limited use of another's real property
FROM
"cityofnewyork-us/nyc-citywide-annualized-calendar-sales-update-w2pb-icbu:latest"."nyc_citywide_annualized_calendar_sales_update"
LIMIT 100;Connecting to the DDN is easy. All you need is an existing SQL client that can connect to Postgres. As long as you have a SQL client ready, you'll be able to query cityofnewyork-us/nyc-citywide-annualized-calendar-sales-update-w2pb-icbu with SQL in under 60 seconds.
Query Your Local Engine
bash -c "$(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/nyc-citywide-annualized-calendar-sales-update-w2pb-icbu: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/nyc-citywide-annualized-calendar-sales-update-w2pb-icbuCheckout 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/nyc-citywide-annualized-calendar-sales-update-w2pb-icbu:latestThis will download all the objects for the latest tag of cityofnewyork-us/nyc-citywide-annualized-calendar-sales-update-w2pb-icbu 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/nyc-citywide-annualized-calendar-sales-update-w2pb-icbu: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/nyc-citywide-annualized-calendar-sales-update-w2pb-icbu: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/nyc-citywide-annualized-calendar-sales-update-w2pb-icbu is just another Postgres schema.