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 strategic_measurenumber_and_percentage_of_students table in this repository, by referencing it like:
"austintexas-gov/strategic-measurenumber-and-percentage-of-students-4zte-y74h:latest"."strategic_measurenumber_and_percentage_of_students"or in a full query, like:
SELECT
":id", -- Socrata column ID
"grades_served", -- Specifies what grade level the school serves
"campus_number", -- Campus number of particular school
"campus_name", -- Name of school
":@computed_region_rxpj_nzrk", -- This column was automatically created in order to record in what polygon from the dataset 'Zipcodes' (rxpj-nzrk) the point in column 'geocode' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"start_date", -- Date data began being tracked
"end_date", -- Date data tracking ended
"school_type", -- Specifies if school serves high, middle, or elementary school
"overall_grade_rating", -- Accountability Rating for year by Texas Education Association
"accountability_system", -- A-F accountability was applied to OverallGrade/Rating. "F" now represents "Needs Improvement".
"_2_digit_esc_region", -- Region Number
"region_name", -- Region name
"total_number_of_students", -- Number of overal students in county
"total_number_of_students_1", -- Number of students in a specific school
"eco_dis", -- Percent of Economically Disadvantaged Students
"overall_score", -- Overall score given to school
":@computed_region_m2th_e4b7", -- This column was automatically created in order to record in what polygon from the dataset 'Community Registry' (m2th-e4b7) the point in column 'geocode' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_e9j2_6w3z", -- This column was automatically created in order to record in what polygon from the dataset 'Neighborhood Planning Areas' (e9j2-6w3z) the point in column 'geocode' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_q9nd_rr82", -- This column was automatically created in order to record in what polygon from the dataset 'BOUNDARIES_single_member_districts' (q9nd-rr82) the point in column 'geocode' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_jcrc_4uuy", -- This column was automatically created in order to record in what polygon from the dataset 'Boundaries: Zip Code Tabulation Areas, 2017' (jcrc-4uuy) the point in column 'geocode' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_8spj_utxs", -- This column was automatically created in order to record in what polygon from the dataset 'Single Member Council Districts' (8spj-utxs) the point in column 'geocode' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"zip_code",
"city",
"alt_ed", -- indicates school is alternative education
"county_name", -- County name
"charter_school", -- Charter school yes or no
"district_name", -- Name of school district the school falls under
"street_address",
"geocode",
"data_year" -- Year the data being tracked fell under
FROM
"austintexas-gov/strategic-measurenumber-and-percentage-of-students-4zte-y74h:latest"."strategic_measurenumber_and_percentage_of_students"
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 austintexas-gov/strategic-measurenumber-and-percentage-of-students-4zte-y74h with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.austintexas.gov. When you queryaustintexas-gov/strategic-measurenumber-and-percentage-of-students-4zte-y74h:latest on the DDN, we "mount" the repository using the socrata mount handler. The mount handler proxies your SQL query to the upstream data source, translating it from SQL to the relevant language (in this case SoQL).
We also cache query responses on the DDN, but we run the DDN on multiple nodes so a CACHE_HIT is only guaranteed for subsequent queries that land on the same node.
Query Your Local Engine
bash -c "$(curl -sL https://github.com/splitgraph/splitgraph/releases/latest/download/install.sh)"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 (like this repository), 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, where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.
Mounting Data
This repository is an external repository. It's not hosted by Splitgraph. It is hosted by data.austintexas.gov, and Splitgraph indexes it. This means it is not an actual Splitgraph image, so you cannot use sgr clone to get the data. Instead, you can use the socrata adapter with the sgr mount command. Then, if you want, you can import the data and turn it into a Splitgraph image that others can clone.
First, install Splitgraph if you haven't already.
Mount the table with sgr mount
sgr mount socrata \
"austintexas-gov/strategic-measurenumber-and-percentage-of-students-4zte-y74h" \
--handler-options '{
"domain": "data.austintexas.gov",
"tables": {
"strategic_measurenumber_and_percentage_of_students": "4zte-y74h"
}
}'That's it! Now you can query the data in the mounted table like any other Postgres table.
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, austintexas-gov/strategic-measurenumber-and-percentage-of-students-4zte-y74h is just another Postgres schema.