Query the Data Delivery Network
Query the DDNThe 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 medicaid_enrolled_provider_listing table in this repository, by referencing it like:
"health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5t:latest"."medicaid_enrolled_provider_listing"or in a full query, like:
SELECT
":id", -- Socrata column ID
"medicaid_type", -- FFS (Fee for Service Medicaid): Provider is enrolled and participating in the Medicaid fee for service program. The provider may or may not be a participating provider in the Medicaid managed care program. MCO (Managed Care Only): Provider is enrolled but cannot bill the Medicaid fee for service program. The provider is a participating provider in the Medicaid managed care program. OPRA (Ordering, Prescribing, Referring, Attending): Provider is enrolled and participating in the Medicaid program as a non-billing provider.
"mmis_id", -- A unique number assigned to each provider enrolled to provide services to members of the Medicaid program. This number is the primary method of identifying a provider.
"longitude", -- Longitude related to the service address for the Medicaid provider ID. nnn.dddddddddddd (example: Zip Code 10029-4623 would reflect Longitude ¬-73.9444103)
"medically_fragile_children_directory_ind", -- Indicator to identify provider enrolled in the Medically Fragile Children Directory. Indicator will be Y for Yes and N for No
"provider_specialty", -- Identifies the medical specialty for which a provider is certified.
"npi", -- National Provider ID (NPI) is a standard unique identifier for health care providers. This NPI relates to the MMIS ID and is the most current NPI on file.
"state", -- State related to the service address for the MMIS ID.
"mmis_name", -- The name of a provider of Medicaid services as used on official State records.
"profession_or_service", -- Specifies the broad areas of service that a provider can render.
"zip_code", -- Zip Code related to the service address for the Medicaid provider ID.
"updated", -- Date the file was created at eMedNY. mm/dd/ccyy with leading zeros
"service_address", -- Address related to the service address for the Medicaid provider ID.
"provider_email", -- The provider email address related to the service address for the Medicaid provider ID. Email address will only be included for Provider Duty Nursing (PDN) providers. All other provider records will be blank.
"telephone", -- Telephone number related to the service address for the Medicaid provider ID.
"city", -- The City related to the service address for the Medicaid provider ID.
"county", -- County related to the service address for the MMIS ID.
"enrollment_begin_date", -- Most recent date the provider began participating in NYS FFS Medicaid/OPRA/ Managed Care Only. mm/dd/ccyy with leading zeros
"next_anticipated_revalidation_date", -- Estimated date by which the provider is required to revalidate. May be subject to change based on several factors.
"latitude" -- Latitude related to the service address for the Medicaid provider ID. –nn.dddddddddddd (example: Zip Code 10029-4623 would reflect Latitude 40.7920468)
FROM
"health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5t:latest"."medicaid_enrolled_provider_listing"
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 health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5t with SQL in under 60 seconds.
Query Your Local Engine
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 health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5t: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 health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5tCheckout 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 health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5t:latestThis will download all the objects for the latest tag of health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5t 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 health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5t: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 health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5t:latestThis 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, health-data-ny-gov/medicaid-enrolled-provider-listing-keti-qx5t is just another Postgres schema.