cambridgema-gov/article-22-green-building-review-projects-ay64-ymwq
Icon for Socrata external plugin

Query the Data Delivery Network

Query the DDN

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 article_22_green_building_review_projects table in this repository, by referencing it like:

"cambridgema-gov/article-22-green-building-review-projects-ay64-ymwq:latest"."article_22_green_building_review_projects"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "master_project", -- Larger development/master plan incorporating the project, if applicable
    "primary_address", -- Primary address of the project.
    "gb_id", -- Unique ID used to track Article 22 projects
    ":@computed_region_guic_hr4a",
    "project_name", -- Name by which project is known, if applicable
    "location_address",
    "former_site_name", -- Site name prior to initiation of project.
    "location_city",
    "neighborhood", -- Cambridge neighborhood where project located
    "location_state",
    "devlog_id", -- Project ID number in the Cambridge Development Log publication, if applicable
    "location_zip",
    "pro_type", -- “New Construction” projects are new buildings.. “Substantial Rehabilitation” projects include major renovation to existing buildings.. 
    "pro_use", -- Primary use of the project
    "pro_stg", -- “Permitting” projects are under review. “Permitted” projects have received development approvals. “Under Construction” projects have received a Building Permit. “Completed” projects have received a Certificate of Occupancy (CO) or a Temporary CO.
    "year_complete", -- Year final Certificate of Occupancy for the project issued.
    "approval_type", -- Type of development review to which project was subject
    "gfa", -- Gross floor area of a project as reviewed
    "mr_ach", -- LEED points achieved in Materials & Resources
    "latitude",
    ":@computed_region_rffn_qbt6",
    ":@computed_region_swkg_bavi",
    ":@computed_region_v7jj_366k",
    ":@computed_region_rcj3_ccgu",
    "ae_ach", -- LEED points achieved in Awareness & Education
    "ae_all", -- LEED points possible in Awareness & Education
    "certified", -- Certification status of the project
    "ea_ach", -- LEED points achieved in Energy & Atmosphere
    "ea_all", -- LEED points possible in Energy & Atmosphere
    "id_ach", -- LEED points achieved in Innovation & Design Process
    "id_all", -- LEED points possible in Innovation & Design Process
    "ieq_ach", -- LEED points achieved in Indoor Environmental Quality
    "ieq_all", -- LEED points possible in Indoor Environmental Quality
    "ip_ach", -- LEED points achieved in Integrative Process
    "ip_all", -- LEED points possible in Integrative Process
    "ll_ach", -- LEED points achieved in Location & Transportation/Linkages
    "ll_all", -- LEED points possible in Location & Transportation/Linkages
    "location", -- Latitude and longitude of project
    "longitude",
    "mr_all", -- LEED points possible in Materials & Resources
    "pb", -- Planning Board special permit number, if applcaible
    "pts_ach", -- Total points that the project has been designed to achieve
    "pts_all", -- Total points that possible based on the rating system
    "rating_level", -- Rating a project is designed to achieve
    "rating_system_version", -- Year or iteration (version) of the set of standards established within an authorized rating program for a project or building type.
    "rp_ach", -- LEED points achieved in Regional Priority
    "rp_all", -- LEED points possible in Regional Priority
    "ss_ach", -- LEED points achieved in Sustainable Sites
    "ss_all", -- LEED points possible in Sustainable Sites
    "we_ach", -- LEED points achieved in Water Efficiency
    "we_all", -- LEED points possible in Water Efficiency
    "residential_units", -- Number of residential units in project, if applicable
    "solar_capacity", -- Indicates potential solar capacity of project in kilowatt hours.
    "solar_ready", -- Indicates if project is ready for installation of solar energy system
    "developer_name" -- Project developer or owner
FROM
    "cambridgema-gov/article-22-green-building-review-projects-ay64-ymwq:latest"."article_22_green_building_review_projects"
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/article-22-green-building-review-projects-ay64-ymwq 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/article-22-green-building-review-projects-ay64-ymwq: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

Install Splitgraph Locally
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/article-22-green-building-review-projects-ay64-ymwq" \
  --handler-options '{
    "domain": "data.cambridgema.gov",
    "tables": {
        "article_22_green_building_review_projects": "ay64-ymwq"
    }
}'

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/article-22-green-building-review-projects-ay64-ymwq is just another Postgres schema.

Related Documentation: