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 traffic_violations table in this repository, by referencing it like:
"montgomerycountymd-gov/traffic-violations-4mse-ku6q:latest"."traffic_violations"or in a full query, like:
SELECT
":id", -- Socrata column ID
"arrest_type", -- Type of Arrest (A = Marked, B = Unmarked, etc.)
"dl_state", -- State issuing the Driver’s License.
"driver_state", -- State of the driver’s home address.
"driver_city", -- City of the driver’s home address.
"charge", -- Numeric code for the specific charge.
"color", -- Color of the vehicle.
"vehicle_type", -- Type of vehicle (Examples: Automobile, Station Wagon, Heavy Duty Truck, etc.)
"search_reason_for_stop", -- The reason for the stop that lead to a search.
"accident", -- YES if traffic violation involved an accident.
"longitude", -- Longitude location of the traffic violation.
"location", -- Location of the violation, usually an address or intersection.
"description", -- Text description of the specific charge.
"subagency", -- Court code representing the district of assignment of the officer. R15 = 1st district, Rockville B15 = 2nd district, Bethesda SS15 = 3rd district, Silver Spring WG15 = 4th district, Wheaton G15 = 5th district, Germantown M15 = 6th district, Gaithersburg / Montgomery Village HQ15 = Headquarters and Special Operations
"time_of_stop", -- Time of the traffic violation.
"date_of_stop", -- Date of the traffic violation.
"seq_id", -- Unique traffic stop ID
"search_reason", -- The reason for the search.
"search_type", -- Type of search (Person, Property, Both, etc.)
"latitude", -- Latitude location of the traffic violation.
"agency", -- Agency issuing the traffic violation. (Example: MCP is Montgomery County Police)
"make", -- Manufacturer of the vehicle (Examples: Ford, Chevy, Honda, Toyota, etc.)
"state", -- State issuing the vehicle registration.
"search_arrest_reason", -- The arrest reason from the search.
"commercial_vehicle", -- Yes if the vehicle committing the traffic violation is a commercial vehicle.
"gender", -- Gender of the driver (F = Female, M = Male)
"fatal", -- Yes if traffic violation involved a fatality.
"article", -- Article of State Law. (TA = Transportation Article, MR = Maryland Rules)
"search_outcome", -- Resulting outcome of the search.
"hazmat", -- Yes if the traffic violation involved hazardous materials.
"violation_type", -- Violation type. (Examples: Warning, Citation, SERO)
"contributed_to_accident", -- If the traffic violation was a contributing factor in an accident.
"property_damage", -- Yes if traffic violation involved Property Damage.
"geolocation", -- Geo-coded location information.
"belts", -- YES if seat belts were in use in accident cases.
"search_conducted", -- Yes if a search was conducted.
"alcohol", -- Yes if the traffic violation included an alcohol related suspension.
"geolocation_city",
"commercial_license", -- Yes if driver holds a Commercial Drivers License
"geolocation_address",
"race", -- Race of the driver. (Example: Asian, Black, White, Other, etc.)
"work_zone", -- Yes if the traffic violation was in a work zone.
"search_disposition", -- The disposition of the search.
"geolocation_zip",
"year", -- Year vehicle was made.
"geolocation_state",
"model", -- Model of the vehicle.
"personal_injury", -- Yes if traffic violation involved Personal Injury.
":@computed_region_6vgr_duib",
":@computed_region_a9cs_3ed7",
":@computed_region_rbt8_3x7n",
":@computed_region_d7bw_bq6x",
":@computed_region_kbsp_ykn9",
":@computed_region_tx5f_5em3",
":@computed_region_vu5j_pcmz"
FROM
"montgomerycountymd-gov/traffic-violations-4mse-ku6q:latest"."traffic_violations"
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 montgomerycountymd-gov/traffic-violations-4mse-ku6q 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 montgomerycountymd-gov/traffic-violations-4mse-ku6q: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 montgomerycountymd-gov/traffic-violations-4mse-ku6qCheckout 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 montgomerycountymd-gov/traffic-violations-4mse-ku6q:latestThis will download all the objects for the latest tag of montgomerycountymd-gov/traffic-violations-4mse-ku6q 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 montgomerycountymd-gov/traffic-violations-4mse-ku6q: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 montgomerycountymd-gov/traffic-violations-4mse-ku6q: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, montgomerycountymd-gov/traffic-violations-4mse-ku6q is just another Postgres schema.