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 covid19_hospitalizations_by_date table in this repository, by referencing it like:
"sccgov/covid19-hospitalizations-by-date-5xkz-6esm:latest"."covid19_hospitalizations_by_date"or in a full query, like:
SELECT
":id", -- Socrata column ID
"icu_available_under_typical", -- Number of ICU beds remaining before standard maximum capacity is reached
"typical_non_icu_occupied_pct", -- Percent of standard capacity non-ICU beds occupied
"icu_total_patients", -- Number of total ICU patients
"non_icu_cap_pct_7davg", -- The seven day rolling average percent of staffable non-surge non-ICU hospital beds that are available
"cap_pct_7davg_total", -- The seven day rolling average percent of staffable non-surge hospital beds that are available
"non_icu_covid_pct_7davg", -- 7-day average percent of COVID cases not in ICU
"icu_covid_pct_7davg", -- 7-day average percent of COVID cases in ICU
"available_total", -- Total number of staffable hospital beds that are available
"covid_pui_pct_7davg", -- 7-day average percent of COVID cases and PUI combined
"covid_pct_7davg", -- 7-day average percent of COVID cases
"pui_total_7davg", -- The seven day rolling average of PUIs in hospital beds
"pui_total", -- Number of PUI
"covid_new", -- Number of new COVID cases
"vents_available", -- Number of ventilators available
"vents_pts", -- Number of patients on ventilators
"non_icu_available", -- Number of non-ICU beds available
"non_icu_other", -- Number of other patients not in ICU
"non_icu_pui", -- Number of person under investigation (PUI) not in ICU
"icu_covid", -- Number of COVID cases in intensive care unit (ICU)
"date", -- Date of report
"non_icu_total_patients", -- Number of total non-ICU patients
"icu_covid_pct", -- Percent of ICU beds with COVID-19 patients
"covid_total_7davg", -- The seven day rolling average of COVID-19 patients in hospital beds
"non_icu_covid", -- Number of COVID cases not in ICU
"other_total", -- Total number of other patients in hospital beds
"non_icu_covid_pct", -- Percent of non-ICU beds with COVID-19 patients
"non_icu_typical_capacity", -- Typical non-ICU capacity
"icu_available", -- Number of ICU beds available
"typical_icu_occupied_pct", -- Percent of standard capacity ICU beds occupied
"icu_cap_pct_1day", -- Percent of ICU beds currently available (including staffed surge beds)
"non_icu_available_under_typical", -- Number of non-ICU beds remaining before standard maximum capacity is reached
"icu_typical_capacity", -- Typical ICU capacity
"non_icu_cap_pct_1day", -- Percent of non-ICU beds currently available (including staffed surge beds)
"icu_cap_pct_7davg", -- The seven day rolling average percent of staffable non-surge ICU hospital beds that are available
"icu_covid_pui_pct_7davg", -- 7-day average percent of COVID cases and PUI combined in ICU
"icu_other", -- Number of other patients in ICU
"icu_pui", -- Number of person under investigation (PUI) in ICU
"non_icu_covid_pui_pct_7davg", -- 7-day average percent of COVID cases and PUI combined not in ICU
"covid_total" -- Number of total COVID cases
FROM
"sccgov/covid19-hospitalizations-by-date-5xkz-6esm:latest"."covid19_hospitalizations_by_date"
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 sccgov/covid19-hospitalizations-by-date-5xkz-6esm 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 sccgov/covid19-hospitalizations-by-date-5xkz-6esm: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 sccgov/covid19-hospitalizations-by-date-5xkz-6esmCheckout 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 sccgov/covid19-hospitalizations-by-date-5xkz-6esm:latestThis will download all the objects for the latest tag of sccgov/covid19-hospitalizations-by-date-5xkz-6esm 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 sccgov/covid19-hospitalizations-by-date-5xkz-6esm: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 sccgov/covid19-hospitalizations-by-date-5xkz-6esm: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, sccgov/covid19-hospitalizations-by-date-5xkz-6esm is just another Postgres schema.