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 substance_use_disorder_ambulatory_followup table in this repository, by referencing it like:

"ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm:latest"."substance_use_disorder_ambulatory_followup"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "year", -- 4 Digit year for which the measures is calculated.
    "quarter", -- 2 Digit Quarter for which the measures is calculated. 
    "metric_id_and_description",
    "rate", -- The rate of each measure as calculated by dividing the Denominator by the Numerator. 
    "numerator", -- Count of numerator for each measure at specific grouping level. For detailed descriptions of Numerator for each measure, see the “Data Dictionary" attachment. 
    "age_inpatient_type", -- Age group combined with inpatient type. 
    "region_or_coverage_category", -- Name of Provider Region or Medicaid Coverage Category. 
    "ytd_denominator", -- Count of YTD denominator for each measure at specific grouping level. For detailed descriptions of Denominator for each measure, see the “Data Dictionary" attachment.
    "row_created_date_time", -- Date and Time that the Extract File was generated
    "grouping_description", -- Grouping level description.
    "ytd_rate", -- The rate of each measure as calculated by dividing the YTD_Denominator by the YTD_Numerator. 
    "grouping_level", -- Indicator of corresponding aggregation level.
    "metric_description", -- Metric ID Description
    "denominator", -- Count of denominator for each measure at specific grouping level. For detailed descriptions of Denominator for each measure, see the “Data Dictionary" attachment.
    "metric_id", -- Metric ID that uniquely identifies the OMH/OASAS Medicaid Behavioral Health Measures.                                                09 -14-Day SUD Detox Follow-up,                                              10 -14-Day SUD IP Rehab Follow-up                                  
    "ytd_numerator" -- Count of YTD numerator for each measure at specific grouping level. For detailed descriptions of Numerator for each measure, see the “Data Dictionary" attachment. 
FROM
    "ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm:latest"."substance_use_disorder_ambulatory_followup"
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 ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm with SQL in under 60 seconds.

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, 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 (like this repository), where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.

Cloning Data

Because ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm:latest is a Splitgraph Image, you can clone the data from Spltgraph Cloud to your local engine, where you can query it like any other Postgres database, using any of your existing tools.

First, install Splitgraph if you haven't already.

Clone the metadata with sgr clone

This will be quick, and does not download the actual data.

sgr clone ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm

Checkout the data

Once you've cloned the data, you need to "checkout" the tag that you want. For example, to checkout the latest tag:

sgr checkout ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm:latest

This will download all the objects for the latest tag of ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm and load them into the Splitgraph Engine. Depending on your connection speed and the size of the data, you will need to wait for the checkout to complete. Once it's complete, you will be able to query the data like you would any other Postgres database.

Alternatively, use "layered checkout" to avoid downloading all the data

The data in ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm:latest is 0 bytes. If this is too big to download all at once, or perhaps you only need to query a subset of it, you can use a layered checkout.:

sgr checkout --layered ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm:latest

This will not download all the data, but it will create a schema comprised of foreign tables, that you can query as you would any other data. Splitgraph will lazily download the required objects as you query the data. In some cases, this might be faster or more efficient than a regular checkout.

Read the layered querying documentation to learn about when and why you might want to use layered queries.

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, ny-gov/substance-use-disorder-ambulatory-followup-u2sw-7hnm is just another Postgres schema.

Related Documentation:

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