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 workforce_by_industry_1967_2001 table in this repository, by referencing it like:
"cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47j:latest"."workforce_by_industry_1967_2001"or in a full query, like:
SELECT
":id", -- Socrata column ID
"construction", -- Number of employees in the construction sector.
"government", -- Number of employees in the government sector.
"agriculture_forestry_fishing", -- Number of employees in the agriculture, forestry, and fishing sectors.
"total_employment", -- Average monthly number of workers covered by the unemployment insurance compensation system. Note that this figure does not include all employed persons. Mining firms are not included in the industry breakdown but are included in total employment. See attachment in this dataset's metadata for details about how data collection for this column has changed over time.
"average_annual_wage", -- In dollars. This figure is calculated by multiplying reported average weekly wage by 52.
"total_annual_payroll", -- In dollars. Due to extensions in coverage in 1972 and 1980, prior years’ data is not comparable. See Workforce Data – Historic: More Information in the attachments section.
"year", -- Year of Data
"transportation_communication_and_public_utilities", -- Number of employees in the transportation, communication, and public utilities sectors.
"finance_insurance_and_real_estate", -- Number of employees in the finance, insurance, and real estate sectors.
"services", -- Number of employees in the services sector.
"establishments", -- Average monthly number of businesses locations reporting employment in Cambridge. Some business, such as retail chains, may have more than one establishment.
"trade", -- Number of employees in the trade sector.
"manufacturing" -- Number of employees in the manufacturing sector.
FROM
"cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47j:latest"."workforce_by_industry_1967_2001"
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 cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47j 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 cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47j: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 cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47jCheckout 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 cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47j:latestThis will download all the objects for the latest tag of cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47j 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 cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47j: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 cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47j: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, cambridgema-gov/workforce-by-industry-1967-2001-pb99-d47j is just another Postgres schema.