Query the Data Delivery Network

Query the DDN

The 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 311_requests_2017 table in this repository, by referencing it like:


or in a full query, like:

    ":id", -- Socrata column ID
    "ward_longitude", -- The longitude value for the centroid of the Ward
    "ward_latitude", -- The latitude value for the centroid of the Ward
    "nbhd_longitude", -- The longitude value for the centroid of the Neighbourhood
    "service_area_service_category", -- A combination of Service Area and Service Category so visualizations can be created
    "service_category_service", -- A combination of Service Category and Service Area so visualizations can be created
    "ward", -- A unique number give to a geographical area representing a electoral area
    "neighbourhood", -- The name given to a Neighbourhood
    "service_area", -- The business area that is responsible for the service. 
    "service_description", -- Provides a general description of the service request. 
    "service_category", -- The type of action or service request.
    "status_detail", -- Certain request types may include additional detals describing the progress or action associated with the request. The state of progress the request is at. 
    "request_status", -- The stage at which your request is at, Open or Closed. 
    "date_created", -- The date the service request ticket was created 
    "date_closed", -- The date the appropriate City department has investigated the concern and identified steps to resolve your request. Action for resolving the issue may be dependent on priority and weather conditions or your issue has been closed due to lack of information including contact details.
    "count", -- A field created to do a sum function for charting purposes (Note: having this would be equivalent to doing a row count).
    "ward_location", -- The combination of latitude/longitude for the centroid of the Ward used for mapping purposes.
    "nbhd_latitude", -- The latitude value for the centroid of the Neighbourbhood
    "service_area_service", -- A combination of Service Area and Service Description so visualizations can be created
    "neighbourhood_id", -- Unique number identifier given to Neighourhoods throughout Edmonton
    "interaction_channel", -- The channel or method in which the request was initiated
    "month_number", -- The numeric Month in which the 311 ticket was created.
    "nbhd_location", -- The combination of latitude/longitude for the centroid of the Neighbourhood used for mapping purposes.
    "row_id", -- System generated value for each 311 request created in the system
    "referral_type", -- The action associated with  how the request was handled either information provided or transferred to a business area. 
    "year", -- The Year in which the 311 ticket was created.
    "month" -- The Month in which the 311 ticket was created.
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 edmonton-ca/311-requests-2017-xq32-itvg with SQL in under 60 seconds.

Query Your Local Engine

Install Splitgraph Locally
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 edmonton-ca/311-requests-2017-xq32-itvg: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 edmonton-ca/311-requests-2017-xq32-itvg

Checkout 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 edmonton-ca/311-requests-2017-xq32-itvg:latest

This will download all the objects for the latest tag of edmonton-ca/311-requests-2017-xq32-itvg 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 edmonton-ca/311-requests-2017-xq32-itvg: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 edmonton-ca/311-requests-2017-xq32-itvg:latest

This 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, edmonton-ca/311-requests-2017-xq32-itvg is just another Postgres schema.

Related Documentation: