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 employee_counts_by_industry_in_colorado table in this repository, by referencing it like:
"colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ih:latest"."employee_counts_by_industry_in_colorado"or in a full query, like:
SELECT
":id", -- Socrata column ID
"stateabbrv", -- The two letter state abbreviation.
"statename", -- State name.
"stfips", -- State FIPS code.
"areaname", -- Geographic area name.
"areatype", -- Code describing type of geographic area: e.g. county, service delivery area, MSA.
"areatyname", -- Descriptive title of the areatype.
"area", -- Six-digit code assigned to represent a geographic area. Front fill with zeroes.
"periodyear", -- Character representation of calendar-year (e.g. 2000).
"periodtype", -- Code describing type of period (e.g. Annual, quarterly, monthly, etc.).
"period", -- Period Code. Will be set to '00' where periodtype is annual.
"pertypdesc", -- A description of the period type.
"indcodty", -- Code describing the industry code type.
"indcode", -- A code used in the classification of establishments by type of activity in which they are engaged. For codes not 6 characters long, left justify and blank (ASCII 32) fill. Either SIC or NAICS code can be used. A siccode of 9999 means non-classifiable; industry not specified.
"codetitle", -- The descriptive title for this industry code.
"ownership", -- Ownership is a two-digit indicator that identifies the employer by public or private ownership.
"ownertitle", -- Title of ownership.
"prelim", -- Preliminary/revised flag 0 = Not Preliminary, 1 = Preliminary
"firms", -- The number of firms in the industry.
"estab", -- The number of employer establishments in the industry. (reporting units)
"avgemp", -- The number of workers employed in the industry.
"mnth1emp", -- Employment on the first month of the quarter.
"mnth2emp", -- Employment on the second month of the quarter.
"mnth3emp", -- Employment on the third month of the quarter.
"topempav", -- Average employment for the quarter or year of the top employer for the specified geography and industry code
"totwage", -- The total wages paid to all workers in the industry for the period.
"avgwkwage", -- Average weekly wage per worker.
"taxwage", -- Total taxable wages.
"contrib", -- Employer contributions to the UI fund.
"suppress" -- An indicator that the record contains confidential data that must be suppressed for public use. 0 = Not Suppressed, 1 = Suppress employment & wage data
FROM
"colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ih:latest"."employee_counts_by_industry_in_colorado"
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 colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ih 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 colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ih: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 colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ihCheckout 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 colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ih:latestThis will download all the objects for the latest tag of colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ih 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 colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ih: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 colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ih: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, colorado-gov/employee-counts-by-industry-in-colorado-cjkq-q9ih is just another Postgres schema.