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 information_technology_project_schedule_and_budget table in this repository, by referencing it like:
"citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpg:latest"."information_technology_project_schedule_and_budget"or in a full query, like:
SELECT
":id", -- Socrata column ID
"within_budget", -- Project manager reporting on current project spending and whether it is at or under the original budgeted amount
"project_name", -- Name of the project
"project_manager_contact", -- Name of project manager/contact
"on_schedule", -- Is the schedule variance within 10 percent of zero – the industry standard for acceptable variance from estimated schedule
"project_status", -- Status could be from the initiating (development) phase to underway (implementing) to Live. Projects in initial phases are not counted in budget and schedule metrics as the data (budget, dates) is being developed. 0= not started 1= In Progress 3= System Live 4= Completed 5= Canceled 9 = On hold
"actual_project_go_live", -- The actual date a project goes Live
"project_description", -- Simple explanation of project objective
"project_current_status", -- Overall Status comments from SharePoint. PM notes on where the project is currently, usually includes anticipated start date for projects not started.
"implementation_status", -- Ontrack, caution or at risk. The PM determination of the project’s implementation status based on current issues and risks
"overall_status", -- Ontrack, caution or at risk. The PM determination of project status based on current issues and risks -including budget and schedule.
"issues_status", -- Ontrack, caution or at risk. The PM determination of the project’s issue status based on current or potential issues.
"rowid", -- Unique Row Identifier
"planned_go_live", -- Estimated date the project will go live
"budget_status", -- Ontrack, caution or at risk. The PM determination of the project’s budget status based on current issues and risks.
"quarter_start_date", -- The date the reported quarter started
"risks_status", -- Ontrack, caution or at risk. The PM determination of the project’s risk status based on current issues or potential risks.
"schedule_status", -- Ontrack, caution or at risk. The PM determination of the project’s schedule status based on current issues and risks.
"start_date", -- Date project was initiated
"budget_goods_services" -- Projects Budget
FROM
"citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpg:latest"."information_technology_project_schedule_and_budget"
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 citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpg 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 citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpg: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 citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpgCheckout 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 citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpg:latestThis will download all the objects for the latest tag of citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpg 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 citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpg: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 citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpg: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, citydata-mesaaz-gov/information-technology-project-schedule-and-budget-24pf-5hpg is just another Postgres schema.