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 financial_incentive_projects_property_assessed table in this repository, by referencing it like:
"cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxx:latest"."financial_incentive_projects_property_assessed"or in a full query, like:
SELECT
":id", -- Socrata column ID
"wbe_participation", -- The total dollar amount of project funding paid to certified Women Business Enterprise (WBE) contractors.
"wbe_requirement_met", -- Confirmation of whether or not the project met Women Business Enterprise (WBE) contract requirements, established in the redevelopment agreement.
"jobs_created_aspirational", -- The number of full-time equivalent (FTE) jobs created by the project that are not specifically required as terms of a Redevelopment Agreement.
"jobs_retained_aspirational", -- The number of full-time equivalent (FTE) jobs retained by the project that are not specifically required as terms of a Redevelopment Agreement.
"mbe_participation", -- The total dollar amount of project funding paid to certified Minority Business Enterprise (MBE) contractors.
":@computed_region_rpca_8um6",
":@computed_region_vrxf_vc4k",
":@computed_region_6mkv_f3dw",
":@computed_region_bdys_3d7i",
":@computed_region_43wa_7qmu",
"project_name", -- The name of the development project receiving the incentive.
"applicant_name", -- The individual, company or organization requesting the incentive.
"address_number_high", -- Address Number (High). For projects with a single address this field will be blank.
"community_area", -- The Community Area, as defined by the City of Chicago, in which the project is located.
"total_eligible_project_costs", -- The total amount of project costs that are eligible for the PACE program.
"mbe_requirement_met", -- Confirmation of whether or not the project met Minority Business Enterprise (MBE) contract requirements, established in the redevelopment agreement.
"square_footage", -- The total square footage of the property.
"street_type", -- The type of street in the project address.
"residential_units", -- The number of residential units in the project.
"location", -- The location of the address columns, geocoded to a format that allows for mapping and other geographic analysis.
"street_direction", -- The cardinal direction of the project street address.
"street_name", -- The name of the street in the project address.
"ward", -- The Aldermanic Ward in which the project is located.
"approval_date", -- The closing date of the project loan.
"property_type", -- The land use of the subject property.
"incentive_amount", -- The amount of the PACE loan the project received.
"bonding_agency", -- The public agency providing the loan for the project.
"project_description", -- A brief textual description of the project.
"affordable_residential_units", -- The number of affordable residential units in the project.
"address_number" -- The individual, company or organization requesting the incentive.
FROM
"cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxx:latest"."financial_incentive_projects_property_assessed"
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 cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxx 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 cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxx: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 cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxxCheckout 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 cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxx:latestThis will download all the objects for the latest tag of cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxx 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 cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxx: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 cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxx: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, cityofchicago/financial-incentive-projects-property-assessed-cnna-nmxx is just another Postgres schema.