pa-gov/quarterly-census-of-employment-and-wages-qcew-342b-rkgt
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 quarterly_census_of_employment_and_wages_qcew table in this repository, by referencing it like:

"pa-gov/quarterly-census-of-employment-and-wages-qcew-342b-rkgt:latest"."quarterly_census_of_employment_and_wages_qcew"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    ":@computed_region_r6rf_p9et",
    "latitude", -- This is a generic latitude point for the county so that a map can be created.
    "county_code", -- There are 67 counties in Pennsylvania. They're numbered 01 thru 67, and 00 identifies the statewide total.
    "county_fips", -- FIPS code. The Federal Information Processing Standard (FIPS) code, used by the United States government to uniquely identify counties, is provided with each entry. FIPS codes are five-digit numbers; for Pennsylvania the codes start with 42 and are completed with the three-digit county code. The County FIPS is the last three digits of the five digit FIPS and the code 000 is for statewide.
    "geocoded_column", -- Georeferenced Latitude and Longitude column as generic points for each county that can be used for creating visuals such as maps.
    "area_name", -- The name for the area that the row of data supports. The state of Pennsylvania and all the county names.  
    "state_fips", -- The Federal Information Processing Standard (FIPS) code, used by the United States government to uniquely identify states and counties. FIPS codes are five-digit numbers; for Pennsylvania the codes start with 42 and are completed with the three-digit county code.  The state code is the first two digits of the five digit FIPS code.
    "naics", -- The North American Industry Classification System (NAICS) is the standard used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the U.S. business economy. The NAICS coding hierarchy shared among Canada, Mexico, and the United States ranges from aggregated 2-digit industry sectors to detailed 6-digit country-specific industries.  Industries at the 2-, 3-, 4-, and 5-digit NAICS level are comparable among all three countries.
    "naics_title", -- The North American Industry Classification System (NAICS) Title conveys in brief the industries represented by the NAICS code.
    "establishments", -- An employer establishment represents a single economic unit such as a mine, factory or store engaged in one, or predominantly one activity. An employer represents a business entity and may consist of one or more establishments.  Establishments represent the 12-month average of monthly counts.
    "employment", -- Employment data under the QCEW program represent the number of covered workers who worked during, or received pay for, the pay period including the 12th of the month. Excluded are members of the armed forces, the self-employed, proprietors, domestic workers, unpaid family workers, and railroad workers.  Employment data is presented as the 12-month average of the calendar year. When the field is blank it tells us the data is non-disclosed which has the following meaning:  The non-disclosure guidelines essentially exist for one or two reasons: 1)	Disclosure of the information would breach confidentiality. 2)	The data lacks the statistical rigor to be valid or reliable. 
    "weekly_wages", -- QCEW wages represent total compensation paid during the calendar year, regardless of when services were performed. Included in wages are pay for vacation and other paid leave, bonuses, stock options, tips, the cash value of meals and lodging. Weekly Wages are derived by dividing total wages reported by average employment and then dividing the quotient by 52 weeks per year. When the field is blank it tells us the data is non-disclosed which has the following meaning:  The non-disclosure guidelines essentially exist for one or two reasons: 1)	Disclosure of the information would breach confidentiality. 2)	The data lacks the statistical rigor to be valid or reliable.
    "longitude", -- This is a generic longitude point for the county so that a map can be created.
    "calendar_year", -- Represents the period inclusive of January 1st through December 31st.
    ":@computed_region_nmsq_hqvv",
    ":@computed_region_d3gw_znnf",
    ":@computed_region_amqz_jbr4",
    ":@computed_region_rayf_jjgk"
FROM
    "pa-gov/quarterly-census-of-employment-and-wages-qcew-342b-rkgt:latest"."quarterly_census_of_employment_and_wages_qcew"
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/quarterly-census-of-employment-and-wages-qcew-342b-rkgt 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/quarterly-census-of-employment-and-wages-qcew-342b-rkgt: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.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/quarterly-census-of-employment-and-wages-qcew-342b-rkgt" \
  --handler-options '{
    "domain": "data.pa.gov",
    "tables": {
        "quarterly_census_of_employment_and_wages_qcew": "342b-rkgt"
    }
}'

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/quarterly-census-of-employment-and-wages-qcew-342b-rkgt is just another Postgres schema.