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 solar_installation_permits table in this repository, by referencing it like:

"cambridgema-gov/solar-installation-permits-whpw-w55x:latest"."solar_installation_permits"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "watt_capacity", -- Watt Capacity of Each Panel
    ":@computed_region_rffn_qbt6",
    ":@computed_region_v7jj_366k",
    "panel_dimensions", -- Thermal Panel Dimensions
    "mount_type", -- Mount Type
    "geocoded_column_zip",
    "building_construction_type",
    "building_use",
    "solar_system_size", -- Solar System Size (kW DC)
    "application_status", -- Status
    "stories_above_grade", -- Number of Stories (Above Grade)
    "firm_name", -- Name of firm permitted to install solar equipment
    "demolition_description",
    "temporary_dumpster_count", -- Number of Temporary Dumpsters
    "photovoltaic_panel_count", -- Quantity of Photovoltaics Panels
    "collector_panels", -- Make and Model of Collector Panels
    "id", -- Permit ID
    "address",
    "work_description",
    "geocoded_column_city",
    "backup_power", -- Source of Backup Power for Water Tank
    "solar_energy_type", -- Solar Energy System Type
    "geocoded_column", -- Geocoded address for creating maps on the open data portal
    "plumbing_cost", -- Plumbing Cost of Construction
    "submit_date", -- Date application for permit was submitted
    "number_of_dwelling_units", -- Number of Dwelling Units
    "heat_exchanger", -- Solar Pa: Heat Exchanger Type
    "total_cost", -- Total Cost of Construction
    "geocoded_column_address",
    "latitude",
    "solar_water_tank", -- Capacity of Solar Water Storage Tank (gallons)
    "longitude",
    "demolition_type", -- Type of Demolition
    "solar_collector_type", -- Type of Thermal Solar Collector
    "electrical_cost", -- Electrical Cost of Construction
    "issue_date", -- Date permit was issued
    "owner_occupied", -- Is the property owner-occupied?
    "height", -- Building: Building Height (feet)
    "debris_removal_date", -- Construction Debris Removal Completion Date
    ":@computed_region_guic_hr4a",
    "debris_removal_location", -- Construction debris will be disposed at/by
    "inverter_count", -- Number of Inverters
    "inverter_make_and_model", -- Make and Model of Inverters
    "building_cost", -- Building cost of construction
    "insurance_company", -- Workers: Insurance Company Name
    ":@computed_region_swkg_bavi",
    ":@computed_region_e4yd_rwk4",
    "geocoded_column_state",
    "method_of_removal", -- Method of Removal for Construction Debris
    "inverter_type", -- Inverter Type
    "solar_water_tank_make_and", -- Make and Model of Solar Water Storage Tank
    "integrative_solar_tank", -- Will the storage tank be integrative to the solar collector(s)?
    "thermal_panel_count", -- Quantity of Thermal Panels
    "condo_association" -- Is the property part of a condo association?
FROM
    "cambridgema-gov/solar-installation-permits-whpw-w55x:latest"."solar_installation_permits"
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/solar-installation-permits-whpw-w55x 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/solar-installation-permits-whpw-w55x: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/solar-installation-permits-whpw-w55x" \
  --handler-options '{
    "domain": "data.cambridgema.gov",
    "tables": {
        "solar_installation_permits": "whpw-w55x"
    }
}'

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/solar-installation-permits-whpw-w55x is just another Postgres schema.