texas-gov/20212022-school-nutrition-program-meal-count-tda-c4yx-ez7e
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Query the Data Delivery Network

Query the DDN

The 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_nutrition_program_meal_count_tda table in this repository, by referencing it like:

"texas-gov/20212022-school-nutrition-program-meal-count-tda-c4yx-ez7e:latest"."20212022_school_nutrition_program_meal_count_tda"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "totalmeals_snacks", -- Total number of breakfasts, lunches,and snacks served by site for claim month.
    "lunchdays", -- Number of days lunch meals were served at site for claim month
    "breakfasttotal", -- Total breakfasts served by site for claim month
    "claimdate", -- Month and year being reported for reimbursement of meals served
    "sitecounty", -- County in which the site is located
    "cecounty", -- County in which the CE is located
    "countydistrictcode", -- County District Code for Contracting Entity (CE)
    "sitename", -- Site name; school name
    "esc", -- Educational Service Center (ESC) region
    "ceid", -- Unique number assigned by TDA to Contracting Entity (CE) to identify organization as program sponsor
    "snackdays", -- Number of days snacks were served at site for 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.
    "snacktotal", -- Total snacks served by site for claim month
    "snackadp", -- Average Daily Participation (ADP) for snacks. Calculated as the number of snacks served at the site in claim month divided by the number of snack service days at the site in claim month.
    "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
    "cename", -- Contracting Entity (CE) name; district name
    "cesiteid", -- Unique site identifier. Combination of CEID and SiteID.
    "lunchtotal", -- Total lunches served by 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.
    "breakfastdays", -- Number of days breakfast meals were served at site for claim month
    "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.
    "siteid", -- Identification number assigned to site under CE sponsorship
    "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). 
    "program", -- Program meals have been reported under.
    "programyear" -- A program year for School Nutrition Programs is defined as July 1 of one year through June 30 of the following year. 
FROM
    "texas-gov/20212022-school-nutrition-program-meal-count-tda-c4yx-ez7e:latest"."20212022_school_nutrition_program_meal_count_tda"
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-nutrition-program-meal-count-tda-c4yx-ez7e with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.texas.gov. When you querytexas-gov/20212022-school-nutrition-program-meal-count-tda-c4yx-ez7e:latest on the DDN, we "mount" the repository using the socrata mount handler. The mount handler proxies your SQL query to the upstream data source, translating it from SQL to the relevant language (in this case SoQL).

We also cache query responses on the DDN, but we run the DDN on multiple nodes so a CACHE_HIT is only guaranteed for subsequent queries that land on the same node.

Query Your Local Engine

Install Splitgraph Locally
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 (like this repository), 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, where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.

Mounting Data

This repository is an external repository. It's not hosted by Splitgraph. It is hosted by data.texas.gov, and Splitgraph indexes it. This means it is not an actual Splitgraph image, so you cannot use sgr clone to get the data. Instead, you can use the socrata adapter with the sgr mount command. Then, if you want, you can import the data and turn it into a Splitgraph image that others can clone.

First, install Splitgraph if you haven't already.

Mount the table with sgr mount

sgr mount socrata \
  "texas-gov/20212022-school-nutrition-program-meal-count-tda-c4yx-ez7e" \
  --handler-options '{
    "domain": "data.texas.gov",
    "tables": {
        "20212022_school_nutrition_program_meal_count_tda": "c4yx-ez7e"
    }
}'

That's it! Now you can query the data in the mounted table like any other Postgres table.

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-nutrition-program-meal-count-tda-c4yx-ez7e is just another Postgres schema.