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 summer_meal_programs_meal_count_measure_dataset table in this repository, by referencing it like:
"texas-gov/summer-meal-programs-meal-count-measure-dataset-5gm9-7rqm:latest"."summer_meal_programs_meal_count_measure_dataset"or in a full query, like:
SELECT
":id", -- Socrata column ID
"sitestreetaddresszipcode", -- Site street address, zip code
"sitestreetaddresscity", -- Site street address, city
"sitestreetaddressline2", -- Site street address, line 2 (if applicable)
"total_meals_snacks", -- Total breakfast, lunch, snack and supper meals served by site for claim month
"supperdays", -- Number of days supper meals served at site for claim month
"pmsnackdays", -- Number of days afternoon snacks were served at 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
"amsnacktotal", -- Total number of morning snacks served at site for claim month
"amsnackdays", -- Number of days morning snacks were served at site for claim month
"breakfastdays", -- Number of days breakfast meals were served at site for 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
"ceid", -- Unique number assigned by TDA to Contracting Entity (CE) to identify organization as program sponsor
"sitestreetaddressline1", -- Site street address, line 1
"suppertotal", -- Total suppers 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 Contracting Entity (CE) is located
"countydistrictcode", -- County District Code for county in which Contracting Entity (CE) in located
"siteid", -- Identification number assigned to site under CE sponsorship
"esc", -- Educational Service Center (ESC) region
"cename", -- Contracting Entity (CE) name; sponsor or district name
"geoloc_data", -- Geolocation data based on site address.
"sitestreetaddressstate", -- Site street address, state
"pmsnacktotal", -- Total number of afternoon snacks served at site for claim month
"breakfasttotal", -- Total breakfasts served by site for claim month
"covidmealsite", -- COVID-19 Meal Site indicator, Indicates whether site is operating under USDA flexibilities offered in response to the COVID-19 pandemic. Data displayed as: Yes/No.
"sitename", -- Site name
"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 SFSP displayed as: Nonresidential Summer Camp/Private Non Profit/Residential Camp/School Food Authority/Unit of Government. Data for School Nutrition Programs/SSO displayed as: Charter/Private/Public/RCCI (Residential Child Care Institution).
"reporttype", -- Type of information being reported in the dataset
":@computed_region_czj8_xg26", -- This column was automatically created in order to record in what polygon from the dataset 'Texas U.S. Congressional Districts Plan C235 (Effective Jan 2013)' (czj8-xg26) the point in column 'geoloc_data' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_45pq_umjc", -- This column was automatically created in order to record in what polygon from the dataset 'Texas State House Districts Plan H414 (Effective Jan 2021)' (45pq-umjc) the point in column 'geoloc_data' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_5xir_5pdr", -- This column was automatically created in order to record in what polygon from the dataset 'Texas Senate Districts Plan S172 (Effective Jan 2013)' (5xir-5pdr) the point in column 'geoloc_data' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_de3d_j5mj", -- This column was automatically created in order to record in what polygon from the dataset 'US States Cartographic Boundary Map' (de3d-j5mj) the point in column 'geoloc_data' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_59h5_km5p", -- This column was automatically created in order to record in what polygon from the dataset 'Texas Counties Cartographic Boundary Map' (59h5-km5p) the point in column 'geoloc_data' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"programyear" -- A program period for summer meal programs (SFSP and SSO) is defined as mid-May through the end of August for the same calendar year. USDA policy flexibility due to the pandemic has extended summer meal program period from October to September.
FROM
"texas-gov/summer-meal-programs-meal-count-measure-dataset-5gm9-7rqm:latest"."summer_meal_programs_meal_count_measure_dataset"
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/summer-meal-programs-meal-count-measure-dataset-5gm9-7rqm 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/summer-meal-programs-meal-count-measure-dataset-5gm9-7rqm: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
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/summer-meal-programs-meal-count-measure-dataset-5gm9-7rqm" \
--handler-options '{
"domain": "data.texas.gov",
"tables": {
"summer_meal_programs_meal_count_measure_dataset": "5gm9-7rqm"
}
}'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/summer-meal-programs-meal-count-measure-dataset-5gm9-7rqm is just another Postgres schema.