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 recreation_facilities_courses table in this repository, by referencing it like:
"edmonton-ca/recreation-facilities-courses-nr35-h9xv:latest"."recreation_facilities_courses"or in a full query, like:
SELECT
":id", -- Socrata column ID
"activitydesc", -- Description of the course type - if no description stated then the field is given the Title of the course type
"activityid", -- Unique ID for the course type associated to this course - higher level grouping
"activitytitle", -- The title of the Course Type
"coursedesc", -- A descrption of the course offering, if no description is stated then the title of the course instance is used
"courseid", -- Unique ID for the course offering
"coursetitle", -- The title of the course being offered
"startdatetime",
"startdate", -- The first date of the first session of the course
"starttime", -- The time the course starts
"enddatetime",
"enddate", -- The last date of the last session of the course
"endtime", -- The time the course ends
"age", -- The age range for the course offering, indicates what age qualifies a participant to attend
"barcode", -- The unique barcode for the course - listed on the registration website
"brochure_section_id", -- The unique ID for the brochure section classification
"brochure_subsection_id", -- The unique ID for the brochure sub section classification
"brochure_subsection_title", -- The title of the brochure sub section category (i.e. Adult, Child, Youth, Senior etc)
"brochure_title", -- The title of the brochure section category (i.e Aquatics & swimming, fitness, arts, crafts &cooking etc)
"confirmationtext", -- Any additional information about the course
"course_fee_id", -- Unique ID for the course fee
"dayofweek", -- Day of the week of the class instance within the course (will display multiple records for the same course if it occurs more than 1 day per week)
"facility", -- The location where the course is taking place
"facilityid", -- Unique ID of the facility
"fee", -- The dollar amount of the course (default price)
"feetitle", -- Name of the default fee set for the course
"internetdisplay", -- Date the course is available for registration or the link to the course if the registration is now open
"max_reg", -- Maximum number of participants allowed to register
"min_reg", -- Minimum number of registrants allowed for the course to occur
"num_reg", -- Current number of active registrants
"num_waitl", -- Current number of actively waitlisted partcipants when the course is full
"registration_date", -- Date the registration is open for the course
"season" -- The season in which the course occurs
FROM
"edmonton-ca/recreation-facilities-courses-nr35-h9xv:latest"."recreation_facilities_courses"
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 edmonton-ca/recreation-facilities-courses-nr35-h9xv 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 edmonton-ca/recreation-facilities-courses-nr35-h9xv: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 edmonton-ca/recreation-facilities-courses-nr35-h9xvCheckout 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 edmonton-ca/recreation-facilities-courses-nr35-h9xv:latestThis will download all the objects for the latest tag of edmonton-ca/recreation-facilities-courses-nr35-h9xv 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 edmonton-ca/recreation-facilities-courses-nr35-h9xv: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 edmonton-ca/recreation-facilities-courses-nr35-h9xv: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, edmonton-ca/recreation-facilities-courses-nr35-h9xv is just another Postgres schema.