Query the Data Delivery Network

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 supplemental_nutrition_assistance_program table in this repository, by referencing it like:

"pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y:latest"."supplemental_nutrition_assistance_program"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "month_name", -- Calendar Month Name
    "year", -- Calendar Year Number
    "county_cd", -- There are 67 counties in Pennsylvania. They're numbered 01 thru 67, and 00 identifies the statewide total.
    "county_name", -- The name of the county in Pennsylvania or "Statewide" for all of Pennsylvania.
    "geocoded_column_1", -- Georeferenced column as a point used for creating visuals such as maps. A generic point for each county is supplied so a map can be created.
    "longitude", -- Longitude generic point for each county.
    "snap_individuals", -- A SNAP person is an individual who is applying for SNAP benefits and have been deemed eligible for SNAP benefits.  These numbers include adults & children. An EBT (Electronic Benefits Transfer) card is issued to the client to buy their food. They can only spend the amount that's on the card. In July 2014, duplication of persons moving from county to county was eliminated. 
    "county_fips", -- The Federal Information Processing Standard (FIPS) code, used by the United States government to uniquely identify counties, is provided with each entry. FIPS codes are five-digit numbers; for Pennsylvania the codes start with 42 and are completed with the three-digit county code. The County FIPS is the last three digits of the five digit FIPS and the code 000 is for statewide.
    "date", -- Combination of calendar month and year, formatted as MM/YYYY.
    "latitude", -- Latitude generic point for each county.
    "snap_dollars", -- Benefits issued for SNAP for a given month. These benefits are used to buy food to help low-income households. 
    "fiscal_year", -- State Fiscal Year that corresponds with the Month of the data being reported. 
    "state_code", -- The Federal Information Processing Standard (FIPS) code, used by the United States government to uniquely identify states and counties. FIPS codes are five-digit numbers; for Pennsylvania the codes start with 42 and are completed with the three-digit county code.  The state code is the first two digits of the five digit FIPS code.
    "month", -- Calendar Month Number
    "state_name", -- PA is the Pennsylvania abbreviation and the indicator for the State
    ":@computed_region_rayf_jjgk",
    ":@computed_region_r6rf_p9et",
    ":@computed_region_amqz_jbr4",
    ":@computed_region_d3gw_znnf",
    ":@computed_region_nmsq_hqvv"
FROM
    "pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y:latest"."supplemental_nutrition_assistance_program"
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 pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.pa.gov. When you querypa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y: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)"

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.pa.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 \
  "pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y" \
  --handler-options '{
    "domain": "data.pa.gov",
    "tables": {
        "supplemental_nutrition_assistance_program": "kd9x-cq7y"
    }
}'

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, pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y is just another Postgres schema.