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 cambridge_community_wide_greenhouse_gas_inventory table in this repository, by referencing it like:

"cambridgema-gov/cambridge-community-wide-greenhouse-gas-inventory-eiuf-6ksy:latest"."cambridge_community_wide_greenhouse_gas_inventory"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "nitrous_oxide", -- Emissions of the greenhouse gas nitrous oxide (N2O). Units are megatonnes, or one million metric tons. 
    "carbon_dioxide", -- Emissions of the greenhouse gas carbon dioxide (CO2). Units are megatonnes, or one million metric tons. 
    "methane_emissions", -- Emissions of the greenhouse gas methane (CH4). Units are megatonnes, or one million metric tons. 
    "subsector", -- Narrower, more specific economic activities that lead to greenhouse gas emissions. 
    "carbon_dioxide_eq", -- Each greenhouse gas contributes differently to global warming. In order to to compare different sources and sectors, greenhouse gas accounting protocols tend to convert greenhouse gases into carbon dioxide equivalent emissions. For example, the most recent Intergovernmental Panel on Climate Change found one metric ton of methane creates 28 times more atmospheric warming than an equal amount of carbon dioxide over a 100 year period. This is known as methane's "global warming potential" (GWP). To convert from methane to CO2e, we multiple a given mass of methane by its GWP of 28. Nitrous oxide has a GWP of 265.
    "sector", -- The broad economic activities that lead to greenhouse gas emissions. 
    "source", -- The fuel or industrial process that leads to greenhouse gas emissions. 
    "scope" -- Greenhouse gas accounting protocols tend to assign a "scope" of 1, 2, or 3 to greenhouse gas emissions. The scope indicates whether the emissions derive from a source that is directly or indirectly controlled by Cambridge. Scope 1: All direct GHG emissions. Scope 2: Indirect GHG emissions from consumption of purchased electricity, heat or steam. Scope 3: Other indirect emissions, such as the extraction and production of purchased materials and fuels, transport-related activities in vehicles not owned or controlled by the reporting entity, electricity-related activities (e.g. T&D losses) not covered in Scope 2, outsourced activities, waste disposal, etc.
FROM
    "cambridgema-gov/cambridge-community-wide-greenhouse-gas-inventory-eiuf-6ksy:latest"."cambridge_community_wide_greenhouse_gas_inventory"
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 cambridgema-gov/cambridge-community-wide-greenhouse-gas-inventory-eiuf-6ksy with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.cambridgema.gov. When you querycambridgema-gov/cambridge-community-wide-greenhouse-gas-inventory-eiuf-6ksy: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.cambridgema.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 \
  "cambridgema-gov/cambridge-community-wide-greenhouse-gas-inventory-eiuf-6ksy" \
  --handler-options '{
    "domain": "data.cambridgema.gov",
    "tables": {
        "cambridge_community_wide_greenhouse_gas_inventory": "eiuf-6ksy"
    }
}'

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, cambridgema-gov/cambridge-community-wide-greenhouse-gas-inventory-eiuf-6ksy is just another Postgres schema.