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 zoning_application_portal_zap_project_data table in this repository, by referencing it like:
"cityofnewyork-us/zoning-application-portal-zap-project-data-hgx4-8ukb:latest"."zoning_application_portal_zap_project_data"or in a full query, like:
SELECT
":id", -- Socrata column ID
"mih_flag", -- Flag that indicates if Mandatory Inclusionary Housing (MIH) is proposed to be mapped through an amendment to the Zoning Resolution.
"project_status", -- This indicates whether the application is actively being worked on or not.
"public_status", -- The public status of the application.
"dcp_visibility",
"actions", -- The type of action(s) included in the application. There may be multiple land use actions attached to an application to facilitate a single development. Many action types on historical applications are retired.
"mih_mapped_no_res", -- Flag that indicates Mandatory Inclusionary Housing (MIH) is proposed to be mapped, but no residential units are proposed
"ulurp_non", -- Flag that indicates if a project is subject to ULURP or not. Applications can either follow the Uniform Land Use Review Procedure (ULURP) or are designated as Non-ULURP, and are therefore not restricted to ULURP rules and timing.
"mih_workforce", -- Flag that indicates the MIH Workforce option is proposed to be mapped (30% Units/115% AMI)
"completed_date", -- The date the application processing was completed.
"approval_date", -- The date an application was approved.
"ulurp_numbers", -- The ULURP number is a unique identifier for each application's action. The first 2-characters (number) are the fiscal year the application was filed, followed by 4-character unique number, if an application was modified it will be followed by a 1-character (letter), followed by 2-character (letter) action code, followed by a 1-character (letter) borough code.
"ceqr_type", -- Indicates the type of environmental review
"ceqr_number", -- Unique environmental review identifier
"eas_eis", -- Flag that indicates the environmental review document issued. Environmental Assessment Statement (EAS), Environmental Impact Statement (EIS), Technical Memorandum (Tech Memo)
"current_milestone_date", -- The start date of the current milestone related to the review of a land use application
"ceqr_leadagency", -- The agency responsible for determining if an environmental review is required.
"primary_applicant", -- Name of the project's primary applicant.
"current_milestone", -- The current milestone related to the review of a land use application
"mih_option2", -- Flag that indicates MIH Option 2 is proposed to be mapped (30% Units/80% AMI)
"flood_zone_a", -- Flag that indicates if project is in the 1% annual chance floodplain. Areas subject to the 1% annual chance flood (100 year flood) and are considered high-risk.
"community_district", -- Community District(s) associated to the project
"cc_district", -- City Council District(s) associated to the project
"mih_deepaffordability", -- Flag that indicates the MIH Deep Affordability option is proposed to be mapped (20% Units/40% AMI)
"applicant_type", -- Indicates if the applicant is a private or public entity.
"flood_zone_shadedx", -- Flag that indicates if project is in the 0.2% annual chance floodplain. Areas subject to the 0.2% annual chance flood (500 year flood) and are considered moderate-risk.
"certified_referred", -- The date an application was certified or referred. This is also the official start of the ULURP process.
"borough", -- Borough that is affected by the land use application.
"project_brief", -- Description of the application and the development it will facilitate.
"mih_option1", -- Flag that indicates MIH Option 1 is proposed to be mapped (25% Units/60% AMI)
"project_name", -- Name of application/project provided by the applicant.
"noticed_date", -- The date notice was given that an application will certify no sooner than 30 days per the City Charter requirement. This only applies to ULURP projects.
"project_id", -- Unique internal application identifier.
"current_envmilestone", -- The current milestone related to the CEQR/environmental review of an application.
"app_filed_date", -- The date an application(s) was filed with the Department of City Planning (DCP)
"current_envmilestone_date" -- The start date of the current milestone related to the CEQR/environmental review of an application.
FROM
"cityofnewyork-us/zoning-application-portal-zap-project-data-hgx4-8ukb:latest"."zoning_application_portal_zap_project_data"
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/zoning-application-portal-zap-project-data-hgx4-8ukb 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/zoning-application-portal-zap-project-data-hgx4-8ukb: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/zoning-application-portal-zap-project-data-hgx4-8ukbCheckout 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/zoning-application-portal-zap-project-data-hgx4-8ukb:latestThis will download all the objects for the latest tag of cityofnewyork-us/zoning-application-portal-zap-project-data-hgx4-8ukb 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/zoning-application-portal-zap-project-data-hgx4-8ukb: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/zoning-application-portal-zap-project-data-hgx4-8ukb: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/zoning-application-portal-zap-project-data-hgx4-8ukb is just another Postgres schema.