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 child_and_adult_care_food_programs_cacfp_day_care table in this repository, by referencing it like:
"texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62:latest"."child_and_adult_care_food_programs_cacfp_day_care"or in a full query, like:
SELECT
":id", -- Socrata column ID
"tieriihighpmsnack", -- Number of Tier II High afternoon snacks served at site in claim month
"tierilunch", -- Number of Tier I lunches served at site in claim month
"tieriilowamsnack", -- Number of Tier II Low morning snacks served at site in claim month
"daysservedtieriihigh", -- Number of days meals were served at the Tier II High reimbursement category in claim month
"daysservedtieri", -- Number of days meals were served at the Tier I reimbursement category in claim month
"ntsnackreimbursement", -- Total evening snack reimbursement for site for claim month
"supperreimbursement", -- Total supper reimbursement for site for claim month
"lunchreimbursement", -- Total lunch reimbursement for site for claim month
"totalmealssnacks", -- Sum of BreakfastTotal, LunchTotal, SupperTotal, and TotalSnacks for site claim (row)
"tierintsnack", -- Number of Tier I evening snacks served at site in claim month
"suppertotal", -- Total number of suppers served at site in claim month
"tierisupper", -- Number of Tier I suppers served at site in claim month
"pmsnacktotal", -- Total number of afternoon snacks served at site in claim month
"tieriihighlunch", -- Number of Tier II High lunches served at site in claim month
"tieriilowbreakfast", -- Number of Tier II Low breakfasts served at site in claim month
"tieribreakfast", -- Number of Tier I breakfasts served at site in claim month
"daysservedtieriilow", -- Number of days meals were served at the Tier II Low reimbursement category in claim month
"sitelicensenumber", -- Provider's license or registration number.
"cename", -- Contracting Entity (CE) name
"pmsnackreimbursement", -- Total afternoon snack reimbursement for site for claim month
"tdaregion", -- Texas Department of Agriculture (TDA) service region
"cesiteid", -- Unique site identifier for program year. Data format : [CE ID #]-[Site ID #]
"tieripmsnack", -- Number of Tier I afternoon snacks served at site in claim month
"siteid", -- Number assigned to identify site within Contracting Entity (CE)
"tieriilowsupper", -- Number of Tier II Low suppers served at site in claim month
"tieriilowpmsnack", -- Number of Tier II Low afternoon snacks served at site in claim month
"lunchtotal", -- Total number of lunches served at site in claim month
"claimdate", -- Month and year for which meals were reported by the site for reimbursement
"cecounty", -- County in which the Contracting Entity (CE) is located
"sitename", -- Site name/provider name
"tieriilowntsnack", -- Number of Tier II Low evening snacks served at site in claim month
"ceid", -- Unique number assigned to Contracting Entity (CE) to identify organization as a CACFP sponsor
"amsnackreimbursement", -- Total morning snack reimbursement for site for claim month
"breakfastreimbursement", -- Total breakfast reimbursement for site for claim month
"totalsnacks", -- Sum of AMSnackTotal, PMSnackTotal, NTSnackTotal for site claim (row)
"tieriihighsupper", -- Number of Tier II High suppers served at site in claim month
"tieriilowlunch", -- Number of Tier II Low lunches served at site in claim month
"amsnacktotal", -- Total number of morning snacks served at site in claim month
"tieriihighamsnack", -- Number of Tier II High morning snacks served at site in claim month
"breakfasttotal", -- Total number of breakfasts served at site in claim month
"tieriihighbreakfast", -- Number of Tier II High breakfasts served at site in claim month
"ntsnacktotal", -- Total number of evening snacks served at site in claim month
"tieriamsnack", -- Number of Tier I morning snacks served at site in claim month
"sitecounty", -- County in which the site is located
"esc", -- Educational Service Center (ESC) region
"typeofagency", -- Type of agency the Contracting Entity (CE) operates as. Data displayed as: Educational Institution/For Profit Organization/Government Agency/Indian Tribe/Military Installation/Private Non Profit Organization
"tieriihighntsnack", -- Number of Tier II High evening snacks served at site in claim month
"programyear", -- A program year for Child and Adult Care Food Programs (CACFP) is defined as October 1 of one year through September 30 of the following year.
"program" -- Type of information being reported in the dataset
FROM
"texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62:latest"."child_and_adult_care_food_programs_cacfp_day_care"
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 texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62 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 texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62: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 texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62Checkout 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 texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62:latestThis will download all the objects for the latest tag of texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62 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 texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62: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 texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62: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, texas-gov/child-and-adult-care-food-programs-cacfp-day-care-vc4s-rb62 is just another Postgres schema.