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 food_service_establishment_inspections_beginning table in this repository, by referencing it like:
"health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shji:latest"."food_service_establishment_inspections_beginning"or in a full query, like:
SELECT
":id", -- Socrata column ID
"operation_name", -- Name of FSE operation
"longitude", -- Longitude of facility
"violation_description", -- Description of violation
"local_health_department", -- Local Health Department issuing permit to FSE
"facility_municipality", -- Facility location name (town, village, city or hamlet)
"inspection_type", -- Type of service (inspection, re-inspection, field visit, preoperational, complaint, illness, incident)
"inspection_comments", -- Inspector’s comments and narrative regarding the inspection (optional in database)
"facility", -- Name of the Facility or establishment where FSE operates
"address", -- Street address and city of facility
"violation_item", -- Violation item from inspection form
"critical_violation", -- Violation type, critical Red (R) or non-critical Blue (B)
"total_critical_violations", -- Total number of Red (critical) violations identified during inspection
"total_crit_not_corrected", -- Total number of red (critical) violations that were NOT corrected at the time of the inspection
"total_noncritical_violations", -- Total number of Blue (noncritical) violations identified during inspection
"county", -- County where FSE is located
"facility_code", -- Local Health Department assigned code for FSE facility
"facility_address", -- Street address of facility
"facility_city", -- City where FSE is located
"facility_postal_zipcode", -- Facility postal zip code
"nysdoh_gazetteer_1980", -- Municipality code for facility location is derived from the 1980 NYSDOH Gazetteer version. The municipality code identifies the county and the town, village, or city in which the facility is located.
"latitude", -- Latitude of facility
"permit_expiration_date", -- Expiration date of FSE permit
"food_service_type", -- Description of FSE operation type
"food_service_description", -- Additional detail on description of FSE operation type
"permitted_d_b_a", -- Business name of operation, Doing Business As (D/B/A)
"permitted_corp_name", -- Permit applicant (operator) corporation name
"perm_operator_last_name", -- Permit applicant (operator) last name
"perm_operator_first_name", -- Permit applicant (operator) first name
"nys_health_operation_id", -- Unique identifier for operation, used on inspection forms
"fs_facility_state", -- State that facility is located in (NY)
"date_of_inspection" -- Date of inspection
FROM
"health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shji:latest"."food_service_establishment_inspections_beginning"
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 health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shji 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 health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shji: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 health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shjiCheckout 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 health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shji:latestThis will download all the objects for the latest tag of health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shji 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 health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shji: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 health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shji: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, health-data-ny-gov/food-service-establishment-inspections-beginning-2hcc-shji is just another Postgres schema.