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 educator_educational_level table in this repository, by referencing it like:
"delaware-gov/educator-educational-level-3543-y5sg:latest"."educator_educational_level"or in a full query, like:
SELECT
":id", -- Socrata column ID
"ed_level_total", -- Represents the total number of educators who fall under a specific educational level, with a specific years of experience.
"gender", -- Represents the gender of the unique group of educators within a school/district/state.
"total_experience", -- Represents a number of years of experience in education.
"ed_level_associate", -- Highest educational level for the particular set of educators = Associate
"subgroup", -- Names the unique group of educators within a school/district/state described by the combination of Race, Gender, Grade, SpecialDemo, and Geography.
"staff_type", -- Staff type such as professional, non-professsional or all (both professional and non-professional)
"specialdemo", -- Represents the special population status of the unique group of educators within a school/district/state such as Charter, Regular, Service or All Educators combined.
"districtcode", -- Number representing each School District. Statewide data rows will have “0” in this column.
"grade", -- Represents the grade level of the unique group of educators within a school/district/state.
"geography", -- Represents the geography of the unique group of educators within a school/district/state.
"schoolcode", -- Number representing each School within the school district. Statewide or Districtwide data rows will have “0” in this column.
"staff_category", -- Represents a respective staff category that certain educators fall under, such as Classroom Teacher, Instructional Support, or Official/Administrative.
"ed_level_less_than_bachelor_degree", -- Highest educational level for the particular set of educators = Less Than Bachelor Degree
"ed_level_bachelor_plus_30", -- Highest educational level for the particular set of educators = Bachelor Plus 30
"race", -- Represents the race/ethnicity of the unique group of educators within a school/district/state.
"ed_level_bachelor", -- Highest educational level for the particular set of educators = Bachelor
"ed_level_master_plus_45", -- Highest educational level for the particular set of educators = Master Plus 45
"schoolyear", -- School year for which record is applicable. For example, 2019 = school year which ended in June 2019.
"district", -- Full name of the School District. Statewide data rows have "State of Delaware" in this column.
"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.
"job_classification", -- Job classification category, such as Assistant Principal, Teacher, Special Secondary, or Librarian.
"ed_level_not_reported", -- Highest educational level for the particular set of educators = Not Reported
"ed_level_two_years", -- Highest educational level for the particular set of educators = Two Years
"ed_level_bachelor_plus_15", -- Highest educational level for the particular set of educators = Bachelor Plus 15
"ed_level_master", -- Highest educational level for the particular set of educators = Master
"ed_level_master_plus_15", -- Highest educational level for the particular set of educators = Master Plus 15
"ed_level_master_plus_30", -- Highest educational level for the particular set of educators = Master Plus 30
"ed_level_doctorate" -- Highest educational level for the particular set of educators = Doctorate
FROM
"delaware-gov/educator-educational-level-3543-y5sg:latest"."educator_educational_level"
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/educator-educational-level-3543-y5sg 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 delaware-gov/educator-educational-level-3543-y5sg: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/educator-educational-level-3543-y5sgCheckout 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/educator-educational-level-3543-y5sg:latestThis will download all the objects for the latest tag of delaware-gov/educator-educational-level-3543-y5sg 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/educator-educational-level-3543-y5sg: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/educator-educational-level-3543-y5sg: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, delaware-gov/educator-educational-level-3543-y5sg is just another Postgres schema.