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 20212022_school_meal_count_tda_fn_dashboard table in this repository, by referencing it like:
"texas-gov/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deu:latest"."20212022_school_meal_count_tda_fn_dashboard"or in a full query, like:
SELECT
":id", -- Socrata column ID
"supperdays", -- Number of days supper meals were served at site for claim month
"program", -- Program meals have been reported under.
"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/Other
"supperadp", -- Average Daily Participation (ADP) for lunch. Calculated as the number of lunch meals served at the site in claim month divided by the number of supper service days at the site in claim month.
"lunchadp", -- Average Daily Participation (ADP) for lunch. Calculated as the number of lunch meals served at the site in claim month divided by the number of lunch service days at the site in claim month.
"pmsnackadp", -- Average Daily Participation (ADP) for lunch. Calculated as the number of lunch meals served at the site in claim month divided by the number of PM Snack service days at the site in claim month.
"tdaregion", -- Texas Department of Agriculture (TDA) service region
"typeoforg", -- Type of organization the Contracting Entity (CE) operates as within a specific nutrition program. Data for School Nutrition Programs and SSO displayed as: Charter/Private/Public/RCCI (Residential Child Care Institution).
"totalmeals_snacks", -- Total number of breakfasts, lunches, suppers and snacks served by site for claim month.
"breakfastdays", -- Number of days breakfast meals were served at site for claim month
"totalsnacks", -- Total number of snacks served by site for claim month.
"suppertotal", -- Total suppers served by site for claim month
"breakfasttotal", -- Total breakfasts served by site for claim month
"sitecounty", -- County in which the site is located
"cename", -- Contracting Entity (CE) name; district name
"pmsnackdays", -- Number of days PM Snacks were served at site for claim month
"countydistrictcode", -- County District Code for Contracting Entity (CE)
"cesiteid", -- Unique site identifier. Combination of CEID and SiteID.
"siteid", -- Identification number assigned to site under CE sponsorship
"sitename", -- Site name; school name
"pmsnacktotal", -- Total PM Snacks served by site for claim month
"lunchtotal", -- Total lunches served by site for claim month
"lunchdays", -- Number of days lunch meals were served at site for claim month
"amsnackadp", -- Average Daily Participation (ADP) for lunch. Calculated as the number of lunch meals served at the site in claim month divided by the number of AM Snack service days at the site in claim month.
"amsnacktotal", -- Total AM Snacks served by site for claim month
"amsnackdays", -- Number of days AM Snacks were served at site for claim month
"breakfastadp", -- Average Daily Participation (ADP) for breakfast. Calculated as the number of breakfast meals served at the site in claim month divided by the number of breakfast service days at the site in claim month.
"claimdate", -- Month and year being reported for reimbursement of meals served
"cecounty", -- County in which the CE is located
"covidmealsite", -- COVID-19 Meal Site indicator. Indicates noncongregate meal service in response to the COVID-19 pandemic and is based on presence of "CV" in Site Name. Data displayed as: Yes/No.
"esc", -- Educational Service Center (ESC) region
"ceid", -- Unique number assigned by TDA to Contracting Entity (CE) to identify organization as program sponsor
"programyear", -- A program year for School Nutrition Programs is defined as July 1 of one year through June 30 of the following year. The school year for Seamless Summer Option is defined as September through May.
"totalbl_snacks" -- Total number of breakfasts, lunches and snacks served by site for claim month.
FROM
"texas-gov/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deu:latest"."20212022_school_meal_count_tda_fn_dashboard"
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/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deu 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/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deu: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/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deuCheckout 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/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deu:latestThis will download all the objects for the latest tag of texas-gov/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deu 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/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deu: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/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deu: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/20212022-school-meal-count-tda-fn-dashboard-kvd9-9deu is just another Postgres schema.