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 local_law_18_pay_and_demographics_report_agency table in this repository, by referencing it like:

"cityofnewyork-us/local-law-18-pay-and-demographics-report-agency-423i-ukqr:latest"."local_law_18_pay_and_demographics_report_agency"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "gender", -- Gender category self-identified by the employee.
    "race", -- Race category self-identified by the employee.
    "upper_pay_band_bound", -- The upper bound of the pay band that an employee's pay falls in.
    "pay_band", -- A pay band represents the minimum and maximum pay range of a specified width that an employee’s pay falls in.
    "eeo_4_job_category", -- EEO-4 Job Category is used by the U.S. Equal Employment Opportunity Commission (EEOC) to classify a group of employees with comparable job responsibilities at comparable levels within an organization. DCAS classifies and maps each civil service title to one of the eight EEO-4 Job Categories as part of its legal mandate to submit EEO-4 reports every two years.
    "lower_pay_band_bound", -- The lower bound of the pay band that employee's pay falls in.
    "agency_name", -- Name of the agency the employee works for. Includes Local Law 18 covered agencies only.
    "number_of_employees", -- Total number of employees in this group.
    "ethnicity", -- Whether the employee is Hispanic or Latino, which is self-identified by the employee.
    "employee_status", -- Whether an employee is a full-time, part-time, or seasonal. Full-time employees work a standard work week in a full-time title with a regular annual work schedule whereas part-time employees work fewer than 35 hours per week or are in titles having no standard hours per week or days per year. Seasonal employees such as lifeguards and many parks workers may work in either a part-time or full-time capacity.
    "data_year" -- The year corresponding to the data. E.g. 2020 reflects pay and demographic data as of 12/31/2020 for full-time employees and as of 6/30/2020 for employees in seasonal titles.
FROM
    "cityofnewyork-us/local-law-18-pay-and-demographics-report-agency-423i-ukqr:latest"."local_law_18_pay_and_demographics_report_agency"
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 cityofnewyork-us/local-law-18-pay-and-demographics-report-agency-423i-ukqr with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.cityofnewyork.us. When you querycityofnewyork-us/local-law-18-pay-and-demographics-report-agency-423i-ukqr: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.cityofnewyork.us, 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 \
  "cityofnewyork-us/local-law-18-pay-and-demographics-report-agency-423i-ukqr" \
  --handler-options '{
    "domain": "data.cityofnewyork.us",
    "tables": {
        "local_law_18_pay_and_demographics_report_agency": "423i-ukqr"
    }
}'

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, cityofnewyork-us/local-law-18-pay-and-demographics-report-agency-423i-ukqr is just another Postgres schema.