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 iowa_aging_services_consumer_counts_by_fiscal_year table in this repository, by referencing it like:

"mydata-iowa-gov/iowa-aging-services-consumer-counts-by-fiscal-year-3qxc-gxc2:latest"."iowa_aging_services_consumer_counts_by_fiscal_year"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "hawaiian_pacific_islander_consumers", -- Total number of individuals who self-reported race status as Native Hawaiian/Other Pacific Islander
    "asian_consumers", -- Total number of individuals who self-reported race status as Asian
    "native_american_consumers", -- Total number of individuals who self-reported race status as American Indian/Native Alaskan
    "white_not_hispanic_consumers", -- Total number of individuals who self-reported race status as White (not Hispanic).
    "non_hispanic_consumers", -- Total number of individuals who did not self-report ethnicity as Hispanic.
    "hispanic_consumers", -- Total number of individuals who self-reported ethnicity as Hispanic.
    "consumers_in_poverty", -- Total number of individuals whose self-reported household size and income indicated a poverty status..
    "conumsers_living_alone", -- Total number of individuals who self-reported gender as living alone.
    "consumers_in_rural_areas", -- Total number of individuals whose self-reported zip code is considered rural. Rural definition up to 2018 was the U.S. Census Bureau definition. In 2019, the rural definition was changed to match rural designations according to The rural-urban commuting area (RUCA) codes classify U.S. census tracts using measures of population density, urbanization, and daily commuting developed an published by U.S. Dept of Agriculture Economic Research Sevice.
    "male_consumers", -- Total number of individuals who self-reported gender as male.
    "consumers", -- Total number of individuals who received at least 1 unit of the service.
    "service", -- Services provided in accordance with Older Americans Act authorization.
    "consumers_other_race", -- Total number of individuals who self-reported race status as Other
    "african_american_consumers", -- Total number of individuals who self-reported race status as African American 
    "year", -- The state fiscal year for which the services were provided.  The State Fiscal Year runs from July 1 - June 30 and is numbered for the year in which it ends.
    "consumers_two_or_more_races", -- Total number of individuals who self-reported race status as two or more races
    "white_hispanic_consumers", -- Total number of individuals who self-reported race status as White (Hispanic).
    "female_consumers", -- Total number of individuals who self-reported gender as female.
    "age_group" -- Age group as determined by date of birth and age at the end of the previous federal fiscal year.
FROM
    "mydata-iowa-gov/iowa-aging-services-consumer-counts-by-fiscal-year-3qxc-gxc2:latest"."iowa_aging_services_consumer_counts_by_fiscal_year"
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 mydata-iowa-gov/iowa-aging-services-consumer-counts-by-fiscal-year-3qxc-gxc2 with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at mydata.iowa.gov. When you querymydata-iowa-gov/iowa-aging-services-consumer-counts-by-fiscal-year-3qxc-gxc2: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 mydata.iowa.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 \
  "mydata-iowa-gov/iowa-aging-services-consumer-counts-by-fiscal-year-3qxc-gxc2" \
  --handler-options '{
    "domain": "mydata.iowa.gov",
    "tables": {
        "iowa_aging_services_consumer_counts_by_fiscal_year": "3qxc-gxc2"
    }
}'

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, mydata-iowa-gov/iowa-aging-services-consumer-counts-by-fiscal-year-3qxc-gxc2 is just another Postgres schema.