cambridgema-gov/roof-building-permit-79ih-g44d
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 roof_building_permit table in this repository, by referencing it like:

"cambridgema-gov/roof-building-permit-79ih-g44d:latest"."roof_building_permit"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "method_of_removal", -- Method of Removal (Demolition)
    "roof_covering_classification", -- Provide the minimum roof covering classification that will be provided
    "temporary_dumpster_permit", -- Would you like to apply for a temporary dumpster permit as part of this building permit application?
    "building_use", -- Type of building (home, commercial, etc.)
    ":@computed_region_guic_hr4a", -- This column was automatically created in order to record in what polygon from the dataset 'Police Neighborhood Regions' (guic-hr4a) the point in column 'geocoded_column' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    ":@computed_region_v7jj_366k", -- This column was automatically created in order to record in what polygon from the dataset 'Police Response Districts' (v7jj-366k) the point in column 'geocoded_column' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    ":@computed_region_rffn_qbt6", -- This column was automatically created in order to record in what polygon from the dataset 'cambridge_neighborhoods' (rffn-qbt6) the point in column 'geocoded_column' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    ":@computed_region_swkg_bavi", -- This column was automatically created in order to record in what polygon from the dataset 'cambridge_cdd_zoning' (swkg-bavi) the point in column 'geocoded_column' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    ":@computed_region_e4yd_rwk4", -- This column was automatically created in order to record in what polygon from the dataset 'Census Blocks 2010' (e4yd-rwk4) the point in column 'geocoded_column' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    "debris_removal_location", -- Construction debris will be disposed at/by
    "licensed_class", -- Licensed: Class
    "longitude",
    "id", -- Permit ID
    "geocoded_column_address",
    "deck_insulation_tapered", -- Is the above deck insulation tapered?
    "geocoded_column_city",
    "temporary_dumpster_count", -- How many temporary dumpsters would you like to apply for?
    "above_deck_insulation", -- Replacement of above deck insulation is required. Provide the R-value of new insulation to be installed
    "dumpster_license_number", -- Cambridge Dumpster License Number
    "demolition_description",
    "debris_removal_date", -- Construction debris removal will be completed by
    "license_expiration_date", -- License Expiration Date
    "license_number", -- License Number
    "description_other", -- Description: Other / Mixed
    "status", -- Status of roof construction
    "layers_of_roof_covering", -- How many existing layers of roof covering will remain underneath the new roof covering?
    "roofing_material", -- Select the roofing material that will be installed
    "submit_date", -- Applicant Submit Date
    "latitude",
    "address", -- Address where roof work is being done
    "proposed_work_description", -- Select the option that best describes the proposed work
    "dwelling_units", -- Number of Dwelling Units in the building
    "building_cost", -- Building cost of construction
    "geocoded_column", -- Use this column to create maps with the open data portal's mapping tools. 
    "roof_work_description", -- Detailed Description of Work, including attachment methods, use of underlayment, and description of fasteners to be use
    "firm_name", -- Name of firm working on roof construction
    "construction_type",
    "roof_deck_insulation_removal", -- Does the work include removal of existing insulation entirely above a roof deck?
    "photovoltaic_products", -- Will building-integrated photovoltaic products be used as the roof covering?
    "issue_date", -- Date when permit was issued
    "condo_association", -- Is the property part of a condo association?
    "geocoded_column_state",
    "roof_structure_slope", -- Is the roof structure sloped less than 3:12 OR is there rigid insulation that is tapered?
    "type_of_demolition",
    "owner_occupied", -- Is the property owner-occupied?
    "geocoded_column_zip",
    "flashing_installation" -- Will new flashing or fascia be required and installed because of this permit?
FROM
    "cambridgema-gov/roof-building-permit-79ih-g44d:latest"."roof_building_permit"
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/roof-building-permit-79ih-g44d 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/roof-building-permit-79ih-g44d: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)"
 

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/roof-building-permit-79ih-g44d" \
  --handler-options '{
    "domain": "data.cambridgema.gov",
    "tables": {
        "roof_building_permit": "79ih-g44d"
    }
}'

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/roof-building-permit-79ih-g44d is just another Postgres schema.