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 student_discipline
table in this repository, by referencing it like:
"delaware-gov/student-discipline-yr4w-jdi4:latest"."student_discipline"
or in a full query, like:
SELECT
":id", -- Socrata column ID
"districtcode", -- Number representing each School District. Statewide data rows will have “0” in this column.
"students", -- The number of students in the specified subgroup who received the disciplinary action
"rowstatus", -- Indicates whether the aggregate data in this row has either been REDACTED or REPORTED. If redacted, certain data has been hidden to comply with state and federal privacy laws. For more information, contact the Delaware Department of Education.
"organization", -- Full name of the Organization which is the School if School Code is given in the row. Districtwide data rows give full name of School District. Statewide rows give "State of Delaware" in this column.
"gender", -- Represents the gender of the unique group of students within a school/district.
"category", -- The category of disciplinary action used.
"enrollment", -- The number of students in the enrolled in the specified organization.
"race", -- Represents the race/ethnicity of the unique group of students within a school/district.
"schoolyear", -- School year for which record is applicable. For example, 2016 = school year which ended in June 2016.
"incidents", -- The total number of incidents that resulted in the specified disciplinary action for the specified student demographic
"avgduration", -- The average numbers of days of the specified disciplinary action for the specified student demographic
"district", -- Full name of the School District. Statewide data rows have "State of Delaware" in this column.
"geography", -- Represents the geography of the unique group of students within a school/district.
"grade", -- Represents the grade level of the unique group of students within a school/district.
"specialdemo", -- Represents the special population status of the unique group of students within a school/district.
"subgroup", -- Names the unique group of students within a school/district described by the combination of Race, Gender, Grade, SpecialDemo, and Geography.
"schoolcode", -- Number representing each School within the school district. Statewide or Districtwide data rows will have “0” in this column.
"pctenrollment" -- The percent of students receiving the disciplinary action. This is the number disciplined students divided by the number of enrolled students.
FROM
"delaware-gov/student-discipline-yr4w-jdi4:latest"."student_discipline"
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 delaware-gov/student-discipline-yr4w-jdi4
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 delaware-gov/student-discipline-yr4w-jdi4: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 delaware-gov/student-discipline-yr4w-jdi4
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 delaware-gov/student-discipline-yr4w-jdi4:latest
This will download all the objects for the latest
tag of delaware-gov/student-discipline-yr4w-jdi4
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 delaware-gov/student-discipline-yr4w-jdi4: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 delaware-gov/student-discipline-yr4w-jdi4: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, delaware-gov/student-discipline-yr4w-jdi4
is just another Postgres schema.