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 sustainability_energy_conservation_kwh_generated table in this repository, by referencing it like:
"citydata-mesaaz-gov/sustainability-energy-conservation-kwh-generated-vgvu-gvjz:latest"."sustainability_energy_conservation_kwh_generated"or in a full query, like:
SELECT
":id", -- Socrata column ID
"owner", -- Owner
"site", -- City of Mesa facility that is being analyzed
"total_net_billable", -- The total cost of a monthly SRP bill, including energy and service costs, as well as savings associated with solar production.
"total_building_energy_use", -- Total energy use (kWh) by City Buildings
"year", -- Billing year of the solar production
"shoulder_peak_kwh", -- A period that precedes or follows regular peaks of heavy use or service.
"kw", -- Indicator for monthly energy demand at a City of Mesa site with solar production
"srp_charges_without_solar", -- Estimated cost of SRP bill if no solar energy was produced onsite, resulting in additional SRP energy demand.
"row_id", -- Unique row identifier
"off_peak_kwh", -- Demand for electricity is lower during low usage times
"on_peak_kwh", -- Demand for electricity is higher during high usage times. (ie., The energy used by one 100-watt light bulb lit for 10 hours is the same as the energy used by 10 bulbs lit for 1 hour).
"month_date", -- Date of billing month for reporting purposes
"solar_savings", -- Total dollars saved resulting from decreased SRP energy demand in favor of onsite solar energy production.
"usage_charges", -- Electricity charges for current month from Salt River Project (SRP) for each building site.
"solar_production", -- Monthly solar production at a City of Mesa solar site
"time_of_use_plan_flag", -- This is a Yes/No field identifying whether the building used SRP’s “Time-of-Use” Plan. The Time-of-Use plan saves electric customers money by designating times each day for customers to target reduced energy usage.
"month" -- Month name for reporting purposes
FROM
"citydata-mesaaz-gov/sustainability-energy-conservation-kwh-generated-vgvu-gvjz:latest"."sustainability_energy_conservation_kwh_generated"
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/sustainability-energy-conservation-kwh-generated-vgvu-gvjz 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/sustainability-energy-conservation-kwh-generated-vgvu-gvjz: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/sustainability-energy-conservation-kwh-generated-vgvu-gvjzCheckout 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/sustainability-energy-conservation-kwh-generated-vgvu-gvjz:latestThis will download all the objects for the latest tag of citydata-mesaaz-gov/sustainability-energy-conservation-kwh-generated-vgvu-gvjz 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/sustainability-energy-conservation-kwh-generated-vgvu-gvjz: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/sustainability-energy-conservation-kwh-generated-vgvu-gvjz: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/sustainability-energy-conservation-kwh-generated-vgvu-gvjz is just another Postgres schema.