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 all_payer_opioidrelated_facility_visits_in_new table in this repository, by referencing it like:
"health-data-ny-gov/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54:latest"."all_payer_opioidrelated_facility_visits_in_new"or in a full query, like:
SELECT
":id", -- Socrata column ID
"as_visits", -- Total Ambulatory Surgery Visits
"as_opioid", -- Total Ambulatory Surgery Visits with Opioid Code
"er_ip_total_discharges", -- Total Emergency Room and Total Inpatient Discharges
"er_visits", -- Total Number of Emergency Room Visits
"er_ip_total_opioid", -- Total Emergency Room and Total Inpatient Discharges with Opioid Code
"ip_total_rateper1000", -- Total Inpatient Discharges with Opioid Code / Total Inpatient Discharges * 1000
"op_total_rate_per1000", -- (Ambulatory Surgery Opioid Visits + Outpatient Opioid Visits) / (Ambulatory Surgery Visits + Outpatient Visits ) * 1000
"overall_rateper1000", -- Grand Total Opioid Visits / Grand Total Discharges or Visits * 1000
"patient_county_name", -- Patient County Code Description
"ip_total_discharges", -- Total Inpatient Discharges (Sum of Through Emergency Room and Not Through Emergency Room)
"er_opioid", -- Number of Emergency Room Visits with Opioid Code
"op_total_opioid", -- Ambulatory Surgery Opioid Visits + Outpatient Opioid Visits
"ip_total_opioid", -- Total Inpatient Discharges with Opioid Code (Sum of Through Emergency Room and Not Through Emergency Room)
"ip_non_er_rateper1000", -- Number of Inpatient Discharges Not Admitted through Emergency Room with Opioid Code / Total Number of Inpatient Discharges Not Admitted through Emergency Room * 1000
"as_rateper1000", -- Total Ambulatory Surgery Visits with Opioid Code / Total Ambulatory Surgery Visits * 1000
"os_visits", -- Total All Other Outpatient
"os_rateper1000", -- All Other Outpatient with Opioid Code / Total All Other Outpatient * 1000
"ip_er_rateper1000", -- Number of Inpatient Discharges Admitted through Emergency Room with Opioid Code / Total Number of Inpatient Discharges Admitted through Emergency Room * 1000
"er_ip_total_rateper1000", -- Total Emergency Room and Total Inpatient Discharges with Opioid Code / Total Emergency Room and Total Inpatient Discharges * 1000
"year", -- Discharge or Visit Year
"overalldischarges_rates", -- Grand Total SPARCS Discharges or Visits
"payer", -- Classification of Payer Type: Medicaid, Medicare, Commercial, Other, or Unknown
"ip_non_er_discharges", -- Total Number of Inpatient Discharges Not Admitted through Emergency Room
"rural_urban", -- Classification of Urban or Rural County, with state total
"patient_county_code", -- SPARCS Patient County Code
"ip_non_er_opioid", -- Number of Inpatient Discharges Not Admitted through Emergency Room with Opioid Code
"ip_er_discharges", -- Total Number of Inpatient Discharges Admitted through Emergency Room
"os_opioid", -- All Other Outpatient with Opioid Code
"overall_opioid", -- Grand Total All Opioid Visits (Emergency Room + Inpatient + Ambulatory Surgery + Outpatient)
"ip_er_opioid", -- Number of Inpatient Discharges Admitted through Emergency Room with Opioid Code
"op_total_visits", -- Ambulatory Surgery Visits + Outpatient Visits
"er_rateper1000" -- Emergency Room Visits with Opioid Code / Total Number of Emergency Room Visits * 1000
FROM
"health-data-ny-gov/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54:latest"."all_payer_opioidrelated_facility_visits_in_new"
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/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54 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/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54: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/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54Checkout 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/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54:latestThis will download all the objects for the latest tag of health-data-ny-gov/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54 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/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54: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/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54: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/all-payer-opioidrelated-facility-visits-in-new-rxm6-fp54 is just another Postgres schema.