pa-gov/estimated-lost-lifetime-wages-due-to-premature-8rwb-e4pv
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 estimated_lost_lifetime_wages_due_to_premature table in this repository, by referencing it like:

"pa-gov/estimated-lost-lifetime-wages-due-to-premature-8rwb-e4pv:latest"."estimated_lost_lifetime_wages_due_to_premature"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "state_fips_code", -- First 2 digits of the 5-digit Federal Information Processing Standard (FIPS) code that designate the state association. Each state has its own 2-digit number and each county within the state has its own 3-digit number which are combined into a 5-digit number to uniquely identify every US county.
    "longitude",
    "county_code_number", -- Pennsylvania county code provided as a number (1-67 for counties, 0 for Commonwealth).
    "geocoded_column", -- Georeferenced column as a point used for creating visuals such as maps. A generic point for reach county is supplied so a map can be created.
    "time_period", -- Period of measurement (annual, federal fiscal year, or quarterly if available).
    "lost_tax_revenue_description", -- Description of estimated lost lifetime state income tax revenue.
    "latitude_longitude", -- Latitude and longitude coordinates in degrees for a centroid point for geographic area.
    "geographic_name", -- Name of geographic area.
    "age", -- Ages of individuals (0 to 64 years).
    "time_period_dates", -- Start and end dates of time period.
    "estimated_lost_lifetime_wages", -- Estimated lifetime wages lost due to premature opioid-related mortality. This value is the sum of the product of the number of years of life lost due to premature opioid-related mortality and the average quarterly wages for county of residence—as reported by the Bureau of Labor Statistics—adjusted for inflation and then discounted.
    "lost_tax_revenue", -- Estimated state income tax revenue associated with estimated lost lifetime wages; 3.07% of lost wages.
    "county_code_text", -- Pennsylvania county code provided as text (1-67 for counties sorted alphabetically, 0 for Commonwealth).
    "county_fips_code", -- Last 3 digits of the 5-digit Federal Information Processing Standard (FIPS) code that designate the county association. Each state has its own 2-digit number and each county within the state has its own 3-digit number which are combined into a 5-digit number to uniquely identify every US county.
    "gender", -- Gender of individuals.
    ":@computed_region_nmsq_hqvv",
    ":@computed_region_r6rf_p9et",
    ":@computed_region_rayf_jjgk",
    ":@computed_region_amqz_jbr4",
    ":@computed_region_d3gw_znnf",
    "geographic_area", -- Region measured, either total for Commonwealth or county.
    "latitude",
    "year", -- Calendar year of measurement (January 1–December 31).
    "estimated_lost_lifetime_wages_1" -- Description of estimated lost lifetime wages.
FROM
    "pa-gov/estimated-lost-lifetime-wages-due-to-premature-8rwb-e4pv:latest"."estimated_lost_lifetime_wages_due_to_premature"
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 pa-gov/estimated-lost-lifetime-wages-due-to-premature-8rwb-e4pv with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.pa.gov. When you querypa-gov/estimated-lost-lifetime-wages-due-to-premature-8rwb-e4pv: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.pa.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 \
  "pa-gov/estimated-lost-lifetime-wages-due-to-premature-8rwb-e4pv" \
  --handler-options '{
    "domain": "data.pa.gov",
    "tables": {
        "estimated_lost_lifetime_wages_due_to_premature": "8rwb-e4pv"
    }
}'

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, pa-gov/estimated-lost-lifetime-wages-due-to-premature-8rwb-e4pv is just another Postgres schema.

Related Documentation: