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 employment_status_of_the_civilian_noninstitutional table in this repository, by referencing it like:
"ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbg:latest"."employment_status_of_the_civilian_noninstitutional"or in a full query, like:
SELECT
":id", -- Socrata column ID
"demographics", -- Characteristics of population
"civilian_labor_force", -- All persons in the civilian noninstitutional population who are either employed or unemployed.
"not_in_labor_force", -- The labor force is made up of the employed and the unemployed. The remainder—those who have no job and are not looking for one—are counted as not in the labor force. Many who are not in the labor force are going to school or are retired. Family responsibilities keep others out of the labor force. Also included in "not in labor force" are discouraged workers who were not currently looking for work specifically because they believed no jobs were available for them or there were none for which they would qualify.
"unemployed_as_a_percent_of_civilian_labor_force", -- The number unemployed as a percent of the civilian labor force.
"unemployed", -- People are classified as unemployed if they do not have a job, have actively looked for work in the prior 4 weeks, and are currently available for work.
"year", -- Survey Year
"employed", -- People are considered employed if they did any work at all for pay or profit during the survey reference week. This includes all parttime and temporary work, as well as regular full-time, year-round employment. Individuals also are counted as employed if they have a job at which they did not work during the survey week, whether they were paid or not, because they were: on vacation, ill, experiencing child care problems, on maternity or paternity leave, taking care of some other family or personal obligation, involved in a labor dispute or prevented from working by bad weather.
"employed_as_a_percent_of_population", -- The number employed as a percent of the civilian noninstitutional population.
"civilian_labor_force_as_a_percent_of_population", -- The civilian labor force as a percent of the civilian noninstitutional population.
"civilian_noninstitutional_population", -- People 16 years of age and older residing in New York State who are not inmates of institutions, and who are not on active duty in the Armed Forces.
"demographic_description" -- Characteristic groupings
FROM
"ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbg:latest"."employment_status_of_the_civilian_noninstitutional"
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 ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbg 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 ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbg: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 ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbgCheckout 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 ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbg:latestThis will download all the objects for the latest tag of ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbg 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 ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbg: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 ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbg: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, ny-gov/employment-status-of-the-civilian-noninstitutional-wkup-gbbg is just another Postgres schema.