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 archive_covid19_ltc_program_vaccinations_and table in this repository, by referencing it like:
"cdc-gov/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7:latest"."archive_covid19_ltc_program_vaccinations_and"or in a full query, like:
SELECT
":id", -- Socrata column ID
"series_complete_fedltc_staff", -- Total number of staff who are fully vaccinated (have second dose of a two-dose vaccine or one dose of a single-dose vaccine) in long-term care facilities
"series_complete_fedltc_unknown", -- Total number of other people who are fully vaccinated (have second dose of a two-dose vaccine or one dose of a single-dose vaccine) in long-term care facilities
"administered_fed_ltc_residents", -- Total number of doses administed to long-term care facility residents
"administered_fed_ltc", -- Total number of doses administed in long-term care facilities
"series_complete_cumulative", -- Cumulative total of people who are fully vaccinated by date of administration
"series_complete_daily", -- Daily total count of people fully vaccinated by date of administration
"administered_daily_change_1", -- 7-day average of the daily change based by date of report
"administered_daily_change", -- Change between the cumulative number of doses administered on a given day and the previous day by date of report
"admin_dose_1_day_rolling", -- 7-day average count of people with at least one dose of any vaccine by date of administration
"admin_dose_1_cumulative", -- Cumulative number of people with at least one dose of any vaccine by date of administration.
"admin_dose_1_daily", -- Total number of Dose 1 administations by date of administration
"administered_7_day_rolling", -- 7-day average of the daily doses administered by date of administration
"administered_pfizer", -- Total number of J&J/Janssen doses administered
"administered_moderna", -- Total number of Pfizer-BioNTech doses administered
"administered", -- Total number of doses administered based on the jurisdiction where recipient lives
"distributed_janssen", -- Total number of doses from unknown manufacturer delivered
"mmwr_week", -- Jurisdiction abbreviation (see tab 2 for full name)
"date", -- Date
"administered_fed_ltc_dose1_1", -- Total number of residents with at least one dose of any vaccine in long-term care facilities
"administered_fed_ltc_unk", -- Total number of doses administed to other people in long-term care facility
"administered_cumulative", -- Cumulative number of reported doses administered by date of administration
"distributed_moderna", -- Total number of Pfizer-BioNTech doses delivered
"recip_administered", -- Total number of Moderna doses administered
"distributed_pfizer", -- Total number of J&J/Janssen doses delivered
"distributed_unk_manuf", -- Total number of administered doses based on the jurisdiction (state/territory) where administered
"administered_unk_manuf", -- Type of date on COVID Tracker: "Admin" = Date of Administration "Report" = Date of Report
"date_type", -- The week of the epidemiologic year as defined by the Morbidity and Mortality Weekly Report (https://ndc.services.cdc.gov/wp-content/uploads/MMWR_week_overview.pdf).
"distributed", -- Total number of Moderna doses delivered
"location", -- Total number of distributed doses
"series_complete_day_rolling", -- 7-day average count of people who are fully vaccinated by date of administration
"administered_daily", -- Total number of administered doses by date of administration.
"administered_janssen", -- Total number of doses from unknown manufacturer administered
"administered_fed_ltc_staff", -- Total number of doses administed to long-term care facility staff
"administered_fed_ltc_dose1", -- Total number of people with at least one dose of any vaccine in long-term care facilities
"administered_fed_ltc_dose1_2", -- Total number of staff with at least one dose of any vaccine in long-term care facilities
"administered_fed_ltc_dose1_3", -- Total number of other people with at least one dose of any vaccine in long-term care facilities
"series_complete_fedltc", -- Total number of people who are fully vaccinated (have second dose of a two-dose vaccine or one dose of a single-dose vaccine) in long-term care facilities
"series_complete_fedltc_1" -- Total number of residents who are fully vaccinated (have second dose of a two-dose vaccine or one dose of a single-dose vaccine) in long-term care facilities
FROM
"cdc-gov/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7:latest"."archive_covid19_ltc_program_vaccinations_and"
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/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7 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 cdc-gov/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7: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 cdc-gov/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7Checkout 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 cdc-gov/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7:latestThis will download all the objects for the latest tag of cdc-gov/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7 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 cdc-gov/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7: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 cdc-gov/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7: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, cdc-gov/archive-covid19-ltc-program-vaccinations-and-egm8-9wq7 is just another Postgres schema.