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 development_log_historical_projects_1997_2022 table in this repository, by referencing it like:
"cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjv:latest"."development_log_historical_projects_1997_2022"or in a full query, like:
SELECT
":id", -- Socrata column ID
"total_number_of_units", -- Number of permitted residential units included in project including new construction and those in rehabbed structures. Blank value indicates nonresidential project.
"use_type", -- Largest proportion of GFA by land use is primary use. For more detail see the associated Project Use Data table.
"far", -- Floor-to-Area (FAR) ratio, which is ratio of Total Gross Floor Area (GFA) to Lot Area. Other GFA not included in the project may exist on the parcel either in existing or prospective buildings that affects the FAR. See Note field for additional information about FAR in some cases.
"lot_area", -- Includes land area of all parcels or property included in project.
"building_permit", -- Only projects with a status of Building Permit Granted or Complete list building permit numbers. In cases of multiple building permits issued for a project either first or primary number listed.
"pb_special_permit", -- Permit number from Planning Board proceedings, if applicable. Not all projects require Planning Board approval.
"zoning", -- Primary zoning category under which the project received permits.
"developer_name", -- Initially the applicant, the developer may change if ownership of the property changes.
"yrcomplete", -- Refers to the year in which a Certificate of Occupancy is granted.
"street_name",
"street_number",
"prior_site_name", -- Name by which site was formerly know, if applicable.
"address", -- Primary street address of project. The street address of a project may change once a land subdivision takes place or an official address is assigned by the City of Cambridge.
"projectid",
"total_gfa", -- Total gross floor area (GFA) for all uses included in project under development as defined by the zoning ordinance. Other gross floor area may exist on the parcel either in existing or prospective buildings that affects the floor-to-area ratio (FAR).
"status", -- Refers to the project stage. Options are Permitting, Permit Granted or As of Right, Building Permit Granted, and Complete. See metadata for further details.
"note", -- Explanatory notes about parking arrangements, computation of FAR, project phasing, and other pertinent topics.
"neighborhood", -- Cambridge is divided into thirteen neighborhoods. For more information see http://www.cambridgema.gov/CDD/planud/neighplan.aspx.
"project_name", -- Refers to a name generally used to refer to the project. Not all projects have names.
"hotel_rooms" -- Blank value indicates project without hotel use.
FROM
"cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjv:latest"."development_log_historical_projects_1997_2022"
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 cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjv 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 cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjv: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 cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjvCheckout 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 cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjv:latestThis will download all the objects for the latest tag of cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjv 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 cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjv: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 cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjv: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, cambridgema-gov/development-log-historical-projects-1997-2022-a5ud-8kjv is just another Postgres schema.