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 sonoma_county_sheriffs_office_arrest_data table in this repository, by referencing it like:
"sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmk:latest"."sonoma_county_sheriffs_office_arrest_data"or in a full query, like:
SELECT
":id", -- Socrata column ID
"fullagencyname", -- Agency that wrote the arrest report including Sheriff's Office and contract city arrests.
"arrestcoordinates", -- This column contains geo-coordinates used for mapping.
"arrestlocation", -- Closest intersection to the location where the arrest was reported. Intersections are used to protect victims identities.
"arrestcity", -- Geographic area where the reported arrest took place. Some unincorporated areas are given three character codes rather then full town names. Additionally city names do not imply that the report occurred within city limits, simply within a geographic area designated with that city name. Use the intersection or geographic coordinates to identify the approximate arrest location.
"arrestid", -- Sequential number assigned to the arrest report.
"datetimearrested", -- Date and time that the arrest was reported to have occurred.
"arrestcoordinates_zip",
"chargedescription", -- English description of the code violation (arrest charge) associated with each charge.
"age", -- Reported age of the arrested individual.
"arreststatus", -- Disposition status of the arrested individual indicating if they were booked or cited and release.
"agency", -- Agency code of agency that wrote the arrest report.
"arrestdegree", -- Highest degree of significance for the overall arrest report, not specific to the individual charge.
"gender", -- Reported gender of the arrested individual.
"arrestcoordinates_state",
"arrestcoordinates_city",
"arrestcoordinates_address",
"race", -- Perceived race of the arrested individual.
"aresteefirsttname", -- First name of the arrested individual.
"aresteelastname", -- Last name of the arrested individual.
"aresteecity", -- Reported city of residence of the arrested individual.
"aresteestreet", -- Reported street of residence of the arrested individual.
"incidentnumber", -- Sequential number assigned to the incident report. Can be used in combination with agency to link to incident data.
"zone_",
"aresteemiddlename", -- Middle name of the arrested individual.
":@computed_region_dig5_f3vy",
":@computed_region_xw9s_pz78"
FROM
"sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmk:latest"."sonoma_county_sheriffs_office_arrest_data"
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 sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmk 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 sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmk: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 sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmkCheckout 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 sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmk:latestThis will download all the objects for the latest tag of sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmk 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 sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmk: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 sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmk: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, sonomacounty-ca-gov/sonoma-county-sheriffs-office-arrest-data-f6uf-eqmk is just another Postgres schema.