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 20222023_kindergarten_immunization_rates_by_school
table in this repository, by referencing it like:
"ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq:latest"."20222023_kindergarten_immunization_rates_by_school"
or in a full query, like:
SELECT
":id", -- Socrata column ID
"ex_tot", -- Percentage of students with any exemption. This value is the number of students with any exemption divided by the total number of students.
"ex_med", -- Percentage of students with a medical exemption. This value is the number of students with a medical exemption divided by the total number of students.
"ex_rel", -- Percentage of students with a religious exemption. This value is the number of students with a religious exemption divided by the total number of students.
"all", -- Percentage of students with all vaccine series.
"hepa", -- Percentage of students with at least 2 doses of hepatitis A vaccine, given a minimum of six calendar months apart, with the 1st dose on or after their 1st birthday.
"varicella", -- Percentage of students with at least 2 doses of varicella vaccine separated by at least 28 days, with the 1st dose on or after their 1st birthday, or a reliable history of chickenpox disease.
"hepb", -- Percentage of students with at least 3 doses of hepatitis B vaccine, with the last dose on or after 24 weeks of age.
"mmr", -- Percentage of students with at least 2 doses of MMR (measles, mumps, and rubella) vaccine separated by at least 28 days, with the 1st dose on or after their 1st birthday.
"dtap", -- Percentage of students with at least 4 doses of DTaP (diphtheria, tetanus, and acellular pertussis) vaccine, with the last dose on or after their 4th birthday.
"polio", -- Percentage of students with at least 3 doses of inactivated polio vaccine, with the last dose on or after their 4th birthday.
"county", -- displays school county as reported
"zipcode", -- displays school zip code as reported
"city", -- displays school city as reported
"address", -- displays school address as reported
"school_name", -- displays school name as reported
"school_type" -- displays whether the school is public or private
FROM
"ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq:latest"."20222023_kindergarten_immunization_rates_by_school"
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 ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq
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; sgr
can 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 clone
and sgr checkout
.
Cloning Data
Because ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq: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 ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq
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 ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq:latest
This will download all the objects for the latest
tag of ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq
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 ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq: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 ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq: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, ct-gov/20222023-kindergarten-immunization-rates-by-school-iux5-vrzq
is just another Postgres schema.