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 governors_executive_budget_program_measures_sfy table in this repository, by referencing it like:
"pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhah:latest"."governors_executive_budget_program_measures_sfy"or in a full query, like:
SELECT
":id", -- Socrata column ID
"budget_book_budget_year", -- This is the State Fiscal Year when the program measure numbers in this row were submitted for the Governor's Executive Budget Book.
"grants_provided_to_non_profit", -- Cultural and Historical Support Grants awarded to qualifying museums and historical organizations.for general operating support This program excludes art museums which are funded by the Pennsylvania Council for the Arts.
"records_or_information", -- Individuals, institutions and governments incorporating the statewide historic preservation plan into their preservation and community development plans.
"number_of_historic_resources", -- Documented historical and cultural places as well as recorded archaeological sites placed in the PA-SHARE database for online accessibility.
"images_added_to_pa_power", -- Images representing digitized records in the Pennsylvania State Archives placed online to make the holdings more accessible.
"records_added_online_to", -- Records documenting specific items/artifacts in PHMC's museum collections placed online to make them more accessible
"fiscal_year", -- Fiscal year for which the program measure values in this row are applicable. Fiscal Years 2020-21 and 2021-22 are estimated amounts based on agency projections.
"promote_the_use_of_statewide", -- Older paper records stored in the State Records Center on behalf of state agencies as per their retention schedule requested for retrieval by those agencies.
"environmental_reviews", -- Represents the number of projects submitted by federal and state agencies reviewed by the Pennsylvania State Historic Preservation Office (PA SHPO) reviews to determine if they will impact significant cultural and historical resources and, if so, how to address and resolve those effects, as required by the National Historic Preservation Act of 1966.
"trained_practitioners_and", -- Individuals who have received PHMC-sponsored training on preservation practices, record maintenance and community preservation.
"planning_and_construction", -- Dollars awarded/spent for preservation planning and construction projects.
"onsite_paid_visitation_at_phmc" -- Visitors paying to visit PHMC sites and museums - discounted admission included. PHMC welcome many visitors free of charge for special programs, free days and recreational use but the paid visitation number is tracked through our ticketing system and is more consistent than unpaid or recreational visitors which are sometimes estimated and open to greater chance of error.
FROM
"pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhah:latest"."governors_executive_budget_program_measures_sfy"
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 pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhah 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 pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhah: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 pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhahCheckout 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 pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhah:latestThis will download all the objects for the latest tag of pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhah 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 pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhah: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 pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhah: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, pa-gov/governors-executive-budget-program-measures-sfy-knxi-vhah is just another Postgres schema.