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 coal_unit_train_loadings table in this repository, by referencing it like:
"internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4d:latest"."coal_unit_train_loadings"or in a full query, like:
SELECT
":id", -- Socrata column ID
"week", -- Week number calculated from the reported week ending date (Date field). Week 1 is the first week of the year with a week ending date falling on or after January 4. In other words, it is the first reported week of data which includes four days in the new year. Values range from 1 to 52 or 53, depending on the year.
"date", -- Week ending dates, ranging from 03/29/2017 to the present.
"loadings_average", -- Actual average daily coal unit train loadings for the reporting week by coal production region. Measurement is either a train- or carload-basis.
"loadings_plan", -- Planned average daily coal unit train loadings for the reporting week by coal production region. Measurement is either a train- or carload-basis.
"month", -- Month number calculated from the reported week ending date (Date field). Week ending dates falling before the fourth day of the month are assigned to the previous month. For example, a week ending date falling on February 1st, 2nd, or 3rd would correspond to “1” (January), since there are less than four days in the reported week that fall in February. Values range from 1 through 12, where 1 refers to January, 2 to February, etc.
"region", -- Coal production region (e.g., Central Appalachia, Powder River Basin, etc.).
"railroad", -- Railroad name (one of 7 Class I railroads).
"year" -- Year number calculated from the reported week ending date (Date field). Week ending dates falling on or after January 4 correspond to the calendar year of the reported week. Week ending dates falling on or before January 3 correspond to the previous calendar year. For example, a week ending date falling on January 2, 2018 would be “2017.” Values range from 2017 to the present.
FROM
"internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4d:latest"."coal_unit_train_loadings"
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 internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4d 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 internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4d: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 internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4dCheckout 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 internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4d:latestThis will download all the objects for the latest tag of internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4d 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 internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4d: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 internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4d: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, internal-agtransport-usda-gov/coal-unit-train-loadings-5pbv-pd4d is just another Postgres schema.