pa-gov/count-and-rate-of-court-cases-and-drug-court-e4tx-vmn6
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 count_and_rate_of_court_cases_and_drug_court table in this repository, by referencing it like:

"pa-gov/count-and-rate-of-court-cases-and-drug-court-e4tx-vmn6:latest"."count_and_rate_of_court_cases_and_drug_court"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "latitude", -- Latitude coordinates in degrees for a centroid point for geographic area.
    "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.
    "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.
    "county_code_number", -- Pennsylvania county code provided as a number (1-67 for counties, 0 for Commonwealth).
    "percent_of_drug_court_cases_5", -- Describes percent of adult drug court participants self-reporting opioid use successfully graduating.
    "percent_of_drug_court_cases_4", -- Percent of adult drug court participants self-reporting opioids (heroin or opiates) as their drug of choice and graduated successfully from the program.
    "percent_of_drug_court_cases_2", -- Percent of adult drug court participants discharged and successfully graduated from the program.
    "percent_of_drug_court_cases", -- Percent of adult drug court participants discharged that self-reported opioids (heroin or opiates) as their drug of choice.
    "successfully_completed_opioid", -- Adult drug court participants self-reporting opioids (heroin or opiates) as their drug of choice and graduated successfully from the program.
    "opioid_drug_court_cases", -- Adult drug court participants discharged and self-reporting opioids (heroin or opiates) as their drug of choice.
    "successfully_completed_drug", -- Adult drug court participants discharged and successfully graduated from program.
    "percent_of_court_of_common_1", -- Describes percent of Court of Common Pleas cases with opioid use.
    "percent_of_court_of_common", -- Percent of Court of Common Pleas cases with opioid use for a given time period and group (sex, age).
    "type_of_rate", -- Describes the rate of Court of Common Pleas opioid cases.
    "rate_of_court_of_common_pleas", -- Rate of annual Court of Common Pleas cases specifying opioids per 1,000 cases in the state or the county.
    "court_of_common_pleas_cases", -- Total number of Court of Common Pleas criminal cases disposed; used to calculate the rate (total cases for the geographic area and time period) or the percentage (total opioid cases for the geographic area and time period).
    "court_of_common_pleas_opioid", -- Number of Court of Common Pleas cases with a specified opioid drug.
    "time_period_dates", -- Start and end dates of time period.
    "age", -- Age group of defendant (18 years and above).
    "geocoded_column", -- Georeferenced latitude and longitude point which can be used to create a map.
    "longitude", -- Longitude coordinates in degrees for a centroid point for geographic area.
    "percent_of_drug_court_cases_3", -- Describes percent of adult drug court participants successfully graduating.
    "drug_court_cases_description", -- Describes adult drug court participants. 
    "percent_of_drug_court_cases_1", -- Describes percent of adult drug court participants self-reporting opioid use.
    "time_period", -- Period of Court of Common Pleas disposition dates (annual or quarterly) or adult drug court discharge dates (annual only).
    "county_code_text", -- Pennsylvania county code provided as text (1-67 for counties sorted alphabetically, 0 for Commonwealth).
    "successfully_completed_drug_1", -- Describes adult drug court participants successfully graduating.
    "drug_court_cases", -- Number of discharged adult drug court participants exiting a problem-solving court.
    "geographic_name", -- Name of geographic area.
    "geographic_area", -- Region for measure, either total for Commonwealth or individual county.
    "court_of_common_pleas_cases_1", -- Describes Court of Common Pleas cases.
    "successfully_completed_opioid_1", -- Describes adult drug court participants self-reporting opioid use successfully graduating.
    "opioid_drug_court_cases_1", -- Describes adult drug participants self-reporting opioid use.
    "gender", -- Gender of defendant.
    "court_of_common_pleas_opioid_1", -- Describes Court of Common Pleas opioid cases.
    "year", -- Calendar year of Court of Common Pleas disposition date or adult drug court discharge date (January 1–December 31).
    ":@computed_region_rayf_jjgk",
    ":@computed_region_r6rf_p9et",
    ":@computed_region_amqz_jbr4",
    ":@computed_region_d3gw_znnf",
    ":@computed_region_nmsq_hqvv"
FROM
    "pa-gov/count-and-rate-of-court-cases-and-drug-court-e4tx-vmn6:latest"."count_and_rate_of_court_cases_and_drug_court"
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/count-and-rate-of-court-cases-and-drug-court-e4tx-vmn6 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/count-and-rate-of-court-cases-and-drug-court-e4tx-vmn6: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/count-and-rate-of-court-cases-and-drug-court-e4tx-vmn6" \
  --handler-options '{
    "domain": "data.pa.gov",
    "tables": {
        "count_and_rate_of_court_cases_and_drug_court": "e4tx-vmn6"
    }
}'

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/count-and-rate-of-court-cases-and-drug-court-e4tx-vmn6 is just another Postgres schema.