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 parcel_address table in this repository, by referencing it like:
"calgary-ca/parcel-address-9zvu-p8uz:latest"."parcel_address"or in a full query, like:
SELECT
":id", -- Socrata column ID
"latitude",
"longitude",
"house_number", -- All properties along a roadway are assigned numbers consecutively, usually starting at one end of the roadway and terminating at the opposite end, to represent an incremental distance along the roadway. In a house number on a numbered roadway, the last two digits are graduating numbers which increase as one progresses down a roadway. The leading numbers, 0-3 digits, represent the hundreds block. A house number on a named roadway may also be determined by the grid system or by an arbitrary starting point on that roadway.
"street_type", -- The following abbreviations are used for street type: AL Alley, AV Avenue, BA Bay, BV Boulevard, CA Cape, CE Centre, CI Circle, CL Close, CM Common, CO Court, CR Crescent, CV Cove, DR Drive, GA Gate, GD Gardens, GR Green, GV Grove, HE Heath, HI Highway, HL Hill, HT Heights, IS Island, LD Landing, LI Link, LN Lane, ME Mews, MR Manor, MT Mount, PA Park, PH Path, PL Place, PR Parade, PS Passage, PT Point, PY Parkway, PZ Plaza, RD Road, RI Rise, RO Row, SQ Square, ST Street, TC Terrace, TR Trail, VI Villas, VW View, WK Walk, WK Walkway, WY Way
"address", -- A description of the location of a person or organization, as written or printed on mail as directions for delivery or the location at which a particular organization or person may be found or reached.
"location_zip",
"street_quad", -- The city of Calgary is divided into four quadrants. The Bow River and the main north-south bridge (Centre Street Bridge) are the central axis with Centre Street dividing east from west and the Bow River dividing north from south, resulting in four quadrants (SW, SE, NE, NW). With expansion of Calgary, the quadrant definitions have changed to accommodate natural physical features (Bow River) and manmade facilities (Macleod Trail).
"address_type", -- Parcel. A parcel address assigned by the City of Calgary that identifies an area of land as described on a "certificate of title" . "Certificate of title" means the record of the title to land that is maintained by the Registrar at the Land Titles office.
"street_name", -- Most public roadway segments are either numbered or named. The Calgary Planning Commission and City Council approve the Street Names.
"point",
"house_alpha", -- An alphabetic extension added to an address. (1"A" Street SW)
"location",
"location_state",
"location_city",
"location_address",
":@computed_region_p8tp_5dkv",
":@computed_region_hq2j_w7j9",
":@computed_region_kxmf_bzkv",
":@computed_region_4b54_tmc4",
":@computed_region_4a3i_ccfj"
FROM
"calgary-ca/parcel-address-9zvu-p8uz:latest"."parcel_address"
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 calgary-ca/parcel-address-9zvu-p8uz 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 calgary-ca/parcel-address-9zvu-p8uz: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 calgary-ca/parcel-address-9zvu-p8uzCheckout 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 calgary-ca/parcel-address-9zvu-p8uz:latestThis will download all the objects for the latest tag of calgary-ca/parcel-address-9zvu-p8uz 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 calgary-ca/parcel-address-9zvu-p8uz: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 calgary-ca/parcel-address-9zvu-p8uz: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, calgary-ca/parcel-address-9zvu-p8uz is just another Postgres schema.