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 wsac_college_bound_scholarship_signup_rates table in this repository, by referencing it like:
"wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyz:latest"."wsac_college_bound_scholarship_signup_rates"or in a full query, like:
SELECT
":id", -- Socrata column ID
"cbs_rate_suppressed", -- The number of CBS applications divided by the number of eligible students. Entities with fewer than ten eligible students have rates are been rounded to the nearest 10%, and for other entities, rates less than 5% are coded to 5% and greater than 95% are coded to 95%.
"cbs_applications_suppressed", -- The number of students with complete applications attending that specific school at the end of their 8th grade year.
"cbs_eligible_suppressed", -- Number of students enrolled at that specific school at the end of their 8th grade year who became eligible for Free and Reduced Price Lunch anytime during 7th or 8th grade. This is based on data schools submit to OSPI. Eligible Student counts of less than 10 have been labeled <10.
"esdcode_ospi", -- Text string: OSPI generated code for Educational Service Districts
"prime_name", -- Name of entity
"aggregation", -- Level of geography and aggregation
"districtcode_ospi", -- Text string: OSPI generated code for school district or LEA
"primeid", -- Unique ID based on Cohort, Aggregation, ESD name, district, and/or school codes
"county", -- County of entity, where applicable
"esd_number", -- Educational Service District (and similar) number, e.g. 113
"schoolname_ospi", -- Text string: OSPI generated code of school
"esd_name", -- Full name of Educational Service District, e.g. Capital Region ESD 113
"schoolyear_ospi", -- Academic year of students
"districtname_ospi", -- Text string: OSPI provided school district or LEA name
"flag_exclude", -- Indicates entities that are excluded from Gold Star calculations due to unique coding from OSPI (typically high schools)
"cbs_cohort", -- Cohort based on expected high school graduation year at the time of College Bound Scholarship application
"district_code_num", -- OSPI District Code as numeric string
"schoolcode_ospi", -- Text string: OSPI generated code for school
"esd_name_short", -- Short name of Educational Service District, e.g. ESD 113
"flag_supressed" -- Indicates if data is suppressed due to fewer than 10 eligible students
FROM
"wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyz:latest"."wsac_college_bound_scholarship_signup_rates"
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 wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyz 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 wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyz: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 wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyzCheckout 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 wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyz:latestThis will download all the objects for the latest tag of wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyz 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 wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyz: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 wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyz: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, wa-gov/wsac-college-bound-scholarship-signup-rates-asjc-htyz is just another Postgres schema.