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 cambridge_municipal_greenhouse_gas_inventory_2008 table in this repository, by referencing it like:
"cambridgema-gov/cambridge-municipal-greenhouse-gas-inventory-2008-m5zs-2fuf:latest"."cambridge_municipal_greenhouse_gas_inventory_2008"or in a full query, like:
SELECT
":id", -- Socrata column ID
"use_mmbtu", -- One MMBtu is equivalent to one million Btu. Calculated value based on energy use in native units, converted to MMBtu using standard conversion factors.
"source", -- The process that generated greenhouse gas emissions.
"total_co2e_metric_tons", -- Metric tons of carbon dioxide equivalent (CO2e). Calculated value based on energy use data tracked by the City in MassEnergyInsight, and emission factors and Global Warming Potential (GWP) factors approved by the The Climate Registry. The GWP was developed to allow comparisons of the global warming impacts of different gases. Specifically, it is a measure of how much energy the emissions of one ton of a gas will absorb over a given period of time, relative to the emissions of one ton of carbon dioxide.
"scope", -- Scope 1, or direct emissions are GHG emissions from fuels combusted within the city boundary. Scope 2, or indirect emissions, are GHG emissions occurring outside the City boundary, but as a consequence of the purchase and use of grid-supplied electricity, heat, steam and/or cooling within the city boundary
"n2o_metric_tons", -- Metric tons of nitrous oxide (N20) emissions. One metric ton is equivalent to 1,000 kg. Calculated values based on kg of N2O, converted to metric tons using a standard conversion factor
"co2e_from_n2o_metric_tons", -- Calculated value based on NO2 emissions in metric tons and Global Warming Potential (GWP) factor for NO2 . GWP was developed to allow comparisons of the global warming impacts of different gases. Specifically, it is a measure of how much energy the emissions of one ton of a gas will absorb over a given period of time, relative to the emissions of one ton of carbon dioxide.
"ch4_metric_tons", -- Metric tons of methane (CH4) emissions. One metric ton is equivalent to 1,000 kg. Calculated values based on kg of CH4, converted to metric tons using a standard conversion factor
"year", -- The year during which emissions took place.
"co2e_from_ch4_metric_tons", -- Calculated value based on CH4 emissions in metric tons and global warming potential (GWP) factor for CH4. The Global Warming Potential (GWP) was developed to allow comparisons of the global warming impacts of different gases. Specifically, it is a measure of how much energy the emissions of one ton of a gas will absorb over a given period of time, relative to the emissions of one ton of carbon dioxide.
"n2o_kg", -- Kilograms of nitrous oxide (N20) emissions. Calculate value based on energy use data and fuel specific N20 emissions factors.
"uniqueid", -- Row ID provided for ease of analysis. A concatenation of scope, year, fuel, and source.
"co2_kg", -- Kilograms of carbon dioxide (CO2). Calculated value based on energy use data and fuel specific CO2 emissions factors.
"co2_metric_tons", -- Metric tons of carbon dioxide (CO2). One metric ton is equivalent to 1,000 kg. Calculated values based on kg of CO2, converted to metric tons using a standard conversion factor
"ch4_kg", -- Kilograms of methane (CH4) emissions. Calculated value based on energy use data and fuel specific CH4 emissions factors
"use_kwh", -- Kilowatt hours. Energy use data in native units based on monthly electricity bills
"type", -- The fuel that generated greenhouse gas emissions.
"use_therms", -- A unit of heat equivalent to 100,000 British Thermal Units (Btu) or 1.055 × 108 joules. Energy use data in native units based on monthly natural gas bills.
"use_gallons" -- Energy use data in native units based on periodic fuel delivery bills
FROM
"cambridgema-gov/cambridge-municipal-greenhouse-gas-inventory-2008-m5zs-2fuf:latest"."cambridge_municipal_greenhouse_gas_inventory_2008"
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-municipal-greenhouse-gas-inventory-2008-m5zs-2fuf 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-municipal-greenhouse-gas-inventory-2008-m5zs-2fuf: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.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-municipal-greenhouse-gas-inventory-2008-m5zs-2fuf" \
--handler-options '{
"domain": "data.cambridgema.gov",
"tables": {
"cambridge_municipal_greenhouse_gas_inventory_2008": "m5zs-2fuf"
}
}'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-municipal-greenhouse-gas-inventory-2008-m5zs-2fuf is just another Postgres schema.