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 tax_increment_financing_tif_investment_committee table in this repository, by referencing it like:
"cityofchicago/tax-increment-financing-tif-investment-committee-nm3d-wkdd:latest"."tax_increment_financing_tif_investment_committee"or in a full query, like:
SELECT
":id", -- Socrata column ID
"tif_request", -- The amount of TIF funding that the project is requesting.
":@computed_region_rpca_8um6",
":@computed_region_vrxf_vc4k",
"improvement_type", -- The category of development seeking TIF funds.
"tic_meeting_date", -- The date of the TIF Investment Committee meeting at which the project was discussed.
":@computed_region_6mkv_f3dw",
"location", -- The location of the ADDRESS column, geocoded to a format that allows for mapping and other geographic analysis.
":@computed_region_bdys_3d7i",
"total_project_cost", -- The total project cost of the project requesting TIF funding.
"tic_decision", -- The decision by the TIF Investment Committee members on whether to approve, deny or hold for further review TIF funding for the project.
"location_tif_number", -- The TIF district(s) identifier number in which the project is located.
"department", -- The Department, Company or Organization requesting the TIF Funding.
"project", -- The name of the project that sought TIF funding.
"funding_tif", -- The TIF district(s) from which the project is receiving TIF funds.
":@computed_region_43wa_7qmu",
"funding_tif_number", -- The TIF district(s) identifier number from which the project is receiving TIF funds.
"project_summary", -- A brief summary of the proposed project that is requesting TIF funding.
"address", -- The address of the project location.
"location_tif", -- The TIF district(s) in which the project is located.
"percentage_of_tif" -- The share of the total project costs being covered by the requested TIF funding.
FROM
"cityofchicago/tax-increment-financing-tif-investment-committee-nm3d-wkdd:latest"."tax_increment_financing_tif_investment_committee"
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/tax-increment-financing-tif-investment-committee-nm3d-wkdd 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/tax-increment-financing-tif-investment-committee-nm3d-wkdd: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/tax-increment-financing-tif-investment-committee-nm3d-wkddCheckout 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/tax-increment-financing-tif-investment-committee-nm3d-wkdd:latestThis will download all the objects for the latest tag of cityofchicago/tax-increment-financing-tif-investment-committee-nm3d-wkdd 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/tax-increment-financing-tif-investment-committee-nm3d-wkdd: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/tax-increment-financing-tif-investment-committee-nm3d-wkdd: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/tax-increment-financing-tif-investment-committee-nm3d-wkdd is just another Postgres schema.