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 metro_energy_use_index_benchmarking_2021 table in this repository, by referencing it like:

"nashville-gov/metro-energy-use-index-benchmarking-2021-kry7-n8d5:latest"."metro_energy_use_index_benchmarking_2021"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "district_chilled_water_use", -- Total amount of district chilled water consumed for a property in a given year (expressed in ton-hours)
    "district_steam_use_lbs", -- Total amount of district steam consumed for a property in a given year (expressed in lbs)
    "eci", -- Energy Cost Index - measure of all energy costs per square foot in a calendar year
    "facility", -- Name of the facility, building, or site
    "property_type", -- Property type that best matches the intended use of the property, based on terms defined by EnergyStar, US Department of Energy
    "department", -- Metro department the facility belongs to
    "address", -- Street address of the property
    "electricity_use_kwh", -- Total amount of electricity consumed for a property in a given year (expressed in kWh)
    "property_category", -- Broad category of the property type that highlights the intended use of the property, based on terms defined by EnergyStar, US Department of Energy
    "cbecs_2018", -- US Department of Energy national EUI benchmarks for specific property types and categories
    "eui", -- Energy Use Index - measure of energy use (expressed in kBTU units) per square foot in a calendar year
    "electricity_costs", -- Total amount of electricity costs for a property in a given year
    "district_chilled_water_costs", -- Total amount of district chilled water costs for a property in a given year
    "district_steam_costs", -- Total amount of district steam costs for a property in a given year
    "natural_gas_costs", -- Total amount of natural gas costs for a property in a given year
    "total_energy_use_kbtu", -- Total amount of energy consumed from all energy sources for a property in a given year (expressed in kBTU)
    "natural_gas_use_therms", -- Total amount of natural gas consumed for a property in a given year (expressed in therms)
    "total_energy_costs", -- Total amount of energy consumption costs from all energy sources for a property in a given year
    "building_sq_ft" -- Reported size of the property
FROM
    "nashville-gov/metro-energy-use-index-benchmarking-2021-kry7-n8d5:latest"."metro_energy_use_index_benchmarking_2021"
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 nashville-gov/metro-energy-use-index-benchmarking-2021-kry7-n8d5 with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.nashville.gov. When you querynashville-gov/metro-energy-use-index-benchmarking-2021-kry7-n8d5: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.nashville.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 \
  "nashville-gov/metro-energy-use-index-benchmarking-2021-kry7-n8d5" \
  --handler-options '{
    "domain": "data.nashville.gov",
    "tables": {
        "metro_energy_use_index_benchmarking_2021": "kry7-n8d5"
    }
}'

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, nashville-gov/metro-energy-use-index-benchmarking-2021-kry7-n8d5 is just another Postgres schema.