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-ikzn-avuz:latest"."governors_executive_budget_program_measures_sfy"or in a full query, like:
SELECT
":id", -- Socrata column ID
"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.
"percentage_of_youth", -- PCCD funds a set list of evidence-based prevention programs; these programs are – Aggression Replacement Therapy; Big Brothers Big Sisters; Cognitive Behavioral Intervention for Trauma in Schools; Familias Fuertes; Functional Family Therapy; LifeSkills Training (Middle School Version); Olweus Bulling Prevention Program; Multisystemic Therapy; Promoting Alternative Thinking Skills (PATHS); Positive Action; Project Toward No Drug Abuse; Strengthening Families 10-14; Strong African American Families; The BLUES Program; The Incredible Years (Parent, Small Group, and Classroom); Trauma-Focused Cognitive Behavioral Therapy; and Triple P (the Positive Parenting Program). Program outcomes are based on participant pre/post surveys specific to each program. One outcome is selected from each program's pre/post survey to serve as the “targeted outcome” that should be positively affected for participants. These selected outcomes are collected quarterly and reported yearly as percentage of participants who reported anticipated beneficial change.
"number_of_victims_served", -- Total number of individuals that were reported to have received service from a PCCD funded victim service provider. The provision of the reported service is a result of the funding provided by PCCD.
"number_of_individuals_diverted", -- This equals the total number of offenders sentenced annually to County Intermediate Punishment Program as reported by counties who receive Intermediate Punishment Program funding.
"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.
FROM
"pa-gov/governors-executive-budget-program-measures-sfy-ikzn-avuz: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-ikzn-avuz 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-ikzn-avuz: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-ikzn-avuzCheckout 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-ikzn-avuz:latestThis will download all the objects for the latest tag of pa-gov/governors-executive-budget-program-measures-sfy-ikzn-avuz 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-ikzn-avuz: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-ikzn-avuz: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-ikzn-avuz is just another Postgres schema.