cdc-gov/vaccination-coverage-among-adolescents-1317-years-ee48-w5t6
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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 vaccination_coverage_among_adolescents_1317_years table in this repository, by referencing it like:

"cdc-gov/vaccination-coverage-among-adolescents-1317-years-ee48-w5t6:latest"."vaccination_coverage_among_adolescents_1317_years"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "coverage_estimate", -- The estimated vaccination coverage or percent of sample represented by each survey sociodemographic characteristic. Non-numeric data are present in this column, such as "NA." These data indicate if an estimate is not applicable. More information can be found on the "Data Sources" page at https://www.cdc.gov/vaccines/imz-managers/coverage/teenvaxview/data-sources.html.
    "dimension", -- The sociodemographic group for which estimates are calculated.
    "vaccine", -- The name of the vaccine or survey sample for which estimates are calculated.
    "population_sample_size", -- The size of the sample surveyed to create the estimate for each vaccine/survey sample, geography, dimension grouping.
    "_95_ci", -- The 95% confidence interval of the estimate of vaccination coverage/survey sociodemographic characteristics.
    "dimension_type", -- The classification of the sociodemographic category for which estimates are calculated. For vaccination coverage in a single survey year, the only dimension type is age. For the five-survey year estimates, estimates are calculated overall and by insurance coverage, urbanicity, race/ethnicity, and poverty.
    "geography", -- The name of the geography for which estimates are calculated.
    "dose", -- This is only applicable for vaccination coverage estimates. When populated, it shows dose of vaccine (≥1, ≥2, ≥3, ≥4) for which coverage is estimated.
    "geography_type", -- The classification (HHS Region/National, State/Local Area) of geographies available.
    "year_season" -- The survey year or survey years for which estimates are calculated.
FROM
    "cdc-gov/vaccination-coverage-among-adolescents-1317-years-ee48-w5t6:latest"."vaccination_coverage_among_adolescents_1317_years"
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/vaccination-coverage-among-adolescents-1317-years-ee48-w5t6 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/vaccination-coverage-among-adolescents-1317-years-ee48-w5t6: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.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/vaccination-coverage-among-adolescents-1317-years-ee48-w5t6" \
  --handler-options '{
    "domain": "data.cdc.gov",
    "tables": {
        "vaccination_coverage_among_adolescents_1317_years": "ee48-w5t6"
    }
}'

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/vaccination-coverage-among-adolescents-1317-years-ee48-w5t6 is just another Postgres schema.

Related Documentation: