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 residential_existing_homes_onetofour_units_energy table in this repository, by referencing it like:
"ny-gov/residential-existing-homes-onetofour-units-energy-4a2x-yp8g:latest"."residential_existing_homes_onetofour_units_energy"or in a full query, like:
SELECT
":id", -- Socrata column ID
"first_year_modeled_project_energy_savings_estimate", -- Estimated post-retrofit first year dollar savings (USD). Negative numbers represent projects with estimated post-retrofit first year dollar expenses, typically occurring when non-energy work was completed such as health and safety improvements, or when work was done in conjunction with another, net positive energy savings project. Projects with zero energy savings dollars represent projects with only health and safety measures, and customer efficiency education
"location_1_state",
":@computed_region_yamh_8v7k",
":@computed_region_wbg7_3whc",
":@computed_region_kjdx_g34t",
"type_of_dwelling", -- General home category describing the dwelling as Single Family, 2-4 Family, Multi Family, or Manufactured/Mobile Home
"location_1_address",
"project_city", -- Name of city for project location
"size_of_home", -- Square footage of home. Blank cells indicate data not reported by the contractor
"location_1", -- Open Data/Socrata-generated geocoding information
"project_id", -- Unique identifier for project
"job_type", -- Indicates whether the project includes only electric reduction measures (Electric Reduction) or is a comprehensive (Home Performance) project including both electric and heating efficiency improvements
"reporting_period", -- The time period covered by the dataset
"project_county", -- Name of county for project location
"project_zip", -- ZIP code for project location
"gas_utility", -- Name of gas utility for project location. If blank, then utility was not reported, or project location is not served by a gas utility
"electric_utility", -- Name of electric utility for project location
"project_completion_date", -- Date final project completion paperwork was reviewed and approved by Program
"total_project_cost", -- Cost of project (USD). NYSERDA incentive currently at 100% of the total project cost. Total Project Costs less than $100 often reflects mileage-only billing for projects with minor work scopes
"pre_retrofit_home_heating_fuel_type", -- Indicates the pre-retrofit primary heating fuel type. Either coal, electricity, kerosene, natural gas, oil, other, pellets, propane, or wood
"year_home_built", -- Home construction date. Blank cells indicate data not reported by the contractor
"number_of_units", -- Number of units served by the Program. Data may include exceptions to the One-to-Four units, which were approved by NYSERDA on a case-by-case basis
"measure_type", -- Measure classification describing primary project improvement defined as Combination-Home Performance, Combination-Electric Reduction, Heating Repair/Replacement, Refrigerator/Freezer Replacement, CFL/LED Lighting, Shell, Shower Head Replacement, or Other
"estimated_annual_kwh_savings", -- Annual post-retrofit modeled electric savings estimate in kWh. Negative numbers represent projects with post-retrofit increase in electric consumption, typically from fuel conversions or ancillary savings. Projects with zero kWh represent projects with only health and safety measures, and customer efficiency education
"estimated_annual_mmbtu_savings", -- Annual post-retrofit modeled MMBtu savings based on primary fuel type. Negative numbers represent projects with post-retrofit increase in MMBtu consumption, typically from fuel conversions or ancillary savings. Projects with zero MMBtu represent projects with only health and safety measures, and customer efficiency education
"location_1_city",
"location_1_zip"
FROM
"ny-gov/residential-existing-homes-onetofour-units-energy-4a2x-yp8g:latest"."residential_existing_homes_onetofour_units_energy"
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 ny-gov/residential-existing-homes-onetofour-units-energy-4a2x-yp8g with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.ny.gov. When you queryny-gov/residential-existing-homes-onetofour-units-energy-4a2x-yp8g: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.ny.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 \
"ny-gov/residential-existing-homes-onetofour-units-energy-4a2x-yp8g" \
--handler-options '{
"domain": "data.ny.gov",
"tables": {
"residential_existing_homes_onetofour_units_energy": "4a2x-yp8g"
}
}'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, ny-gov/residential-existing-homes-onetofour-units-energy-4a2x-yp8g is just another Postgres schema.