cdc-gov/covid19-case-surveillance-public-use-data-with-n8mc-b4w4
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 covid19_case_surveillance_public_use_data_with table in this repository, by referencing it like:

"cdc-gov/covid19-case-surveillance-public-use-data-with-n8mc-b4w4:latest"."covid19_case_surveillance_public_use_data_with"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "current_status", -- What is the current status of this person? [Laboratory-confirmed case, Probable case]
    "case_onset_interval", -- Weeks between earliest date and date of symptom onset.
    "case_positive_specimen", -- Weeks between earliest date and date of first positive specimen collection
    "res_county", -- County of residence
    "case_month", -- The earlier of month the Clinical Date (date related to the illness or specimen collection) or the Date Received by CDC
    "death_yn", -- Did the patient die as a result of this illness?  [Yes; No; Unknown; Missing; NA, if value suppressed for privacy protection.]
    "hosp_yn", -- Was the patient hospitalized? [Yes, No, Unknown, Missing]
    "process", -- Under what process was the case first identified? [Clinical evaluation; Routine surveillance; Contact tracing of case patient; Multiple; Other; Unknown; Missing]
    "ethnicity", -- Ethnicity [Hispanic; Non-Hispanic; Unknown; Missing; NA, if value suppressed for privacy protection.]
    "state_fips_code", -- State FIPS code
    "res_state", -- State of residence
    "exposure_yn", -- In the 14 days prior to illness onset, did the patient have any of the following known exposures: domestic travel, international travel, cruise ship or vessel travel as a passenger or crew member, workplace, airport/airplane, adult congregate living facility (nursing, assisted living, or long-term care facility), school/university/childcare center, correctional facility, community event/mass gathering, animal with confirmed or suspected COVID-19, other exposure, contact with a known COVID-19 case? [Yes, Unknown, Missing]
    "age_group", -- Age group [0 - 17 years; 18 - 49 years; 50 - 64 years; 65 + years; Unknown; Missing; NA, if value suppressed for privacy protection.]
    "county_fips_code", -- County FIPS code
    "icu_yn", -- Was the patient admitted to an intensive care unit (ICU)? [Yes, No, Unknown, Missing]
    "sex", -- Sex [Female; Male; Other; Unknown; Missing; NA, if value suppressed for privacy protection.]
    "race", -- Race [American Indian/Alaska Native; Asian; Black; Multiple/Other; Native Hawaiian/Other Pacific Islander; White; Unknown; Missing; NA, if value suppressed for privacy protection.]
    "symptom_status", -- What is the symptom status of this person? [Asymptomatic, Symptomatic, Unknown, Missing]
    "underlying_conditions_yn" -- Did the patient have one or more of the underlying medical conditions and risk behaviors: diabetes mellitus, hypertension, severe obesity (BMI>40), cardiovascular disease, chronic renal disease, chronic liver disease, chronic lung disease, other chronic diseases, immunosuppressive condition, autoimmune condition, current smoker, former smoker, substance abuse or misuse, disability, psychological/psychiatric, pregnancy, other. [Yes, No, blank]
FROM
    "cdc-gov/covid19-case-surveillance-public-use-data-with-n8mc-b4w4:latest"."covid19_case_surveillance_public_use_data_with"
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 cdc-gov/covid19-case-surveillance-public-use-data-with-n8mc-b4w4 with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.cdc.gov. When you querycdc-gov/covid19-case-surveillance-public-use-data-with-n8mc-b4w4: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.cdc.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 \
  "cdc-gov/covid19-case-surveillance-public-use-data-with-n8mc-b4w4" \
  --handler-options '{
    "domain": "data.cdc.gov",
    "tables": {
        "covid19_case_surveillance_public_use_data_with": "n8mc-b4w4"
    }
}'

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, cdc-gov/covid19-case-surveillance-public-use-data-with-n8mc-b4w4 is just another Postgres schema.