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 bls_jobs_by_industry_category table in this repository, by referencing it like:
"opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9:latest"."bls_jobs_by_industry_category"or in a full query, like:
SELECT
":id", -- Socrata column ID
"government_local", -- The number of local government jobs in Maryland.
"other_services", -- Number of jobs in other services industries in Maryland.
"leisure_and_hospitality_accommodation_and_food_services", -- Number of jobs in accommodation and food service in Maryland. A subset of leisure and hospitality.
"leisure_and_hospitality_arts_entertainment_and_recreation", -- Number of jobs in arts, entertainment, and recreation in Maryland. A subset of leisure and hospitality.
"leisure_and_hospitality_total", -- Number of jobs in the leisure and hospitality service industries in Maryland. Equals the sum of arts, entertainment, and recreation; and accommodation and food services.
"education_and_health_services_health_care_and_social_assistance", -- Number of jobs in health care and social assistance in Maryland. A subset of education and health services.
"education_and_health_services_educational_services", -- Number of jobs in educational services in Maryland. A subset of education and health services.
"professional_and_business_services_management_of_companies_and_", -- Number of jobs in the management of companies and enterprises in Maryland. A subset of professional and business services.
"professional_and_business_services_professional_scientific_and_", -- Number of jobs in professional, scientific, and technical services in Maryland. A subset of professional and business services.
"professional_and_business_services_total", -- Number of jobs in the professional and business services industries in Maryland. Equals the sum of professional, scientific, and technical services; management of companies and enterprises; and administration, support, waste management, and remediation services.
"financial_activities_real_estate_and_rental_and_leasing", -- Number of jobs in real estate, rental, and leasing in Maryland. A subset of financial activities.
"financial_activities_total", -- Number of jobs in the financial activities industries in Maryland. Equals the sum of finance and insurance; and real estate, rental, and leasing.
"information", -- Number of jobs in the information industries in Maryland.
"trade_transportation_and_utilities_transportation_warehousing_a", -- Number of jobs in transportation, warehousing, and utilities in Maryland. A subset of trade, transportation, and utilities.
"trade_transportation_and_utilities_wholesale_trade", -- Number of jobs in wholesale trade in Maryland. A subset of trade, transportation, and utilities.
"trade_transportation_and_utilities_total", -- Number of jobs in the trade, transportation, and utilities industries in Maryland. Equals the sum of wholesale trade; retail trade; and transportation, warehousing, and utilities.
"manufacturing_non_durable_goods", -- Number of jobs in non-durable goods in Maryland. A subset of manufacturing.
"manufacturing_durable_goods", -- Number of jobs in durable goods in Maryland. A subset of manufacturing.
"manufacturing_total", -- Number of jobs in the manufacturing industries in Maryland. Equals the sum of durable goods and non-durable goods.
"mining_logging_and_construction", -- Number of jobs in the mining, logging, and construction industries in Maryland
"total_jobs_private_and_government", -- The total number of all non-farm jobs in Maryland. Equals the sum of all private sector and governement jobs.
"graphing_label", -- Short month abbreviation and calendar year to use as labels for graphing and other visualization purposes
"year", -- Calendar Year in which the job counts are reported
"date",
"government_state", -- The number of state government jobs in Maryland.
"education_and_health_services_total", -- Number of jobs in the education and health services industries in Maryland. Equals the sum of educational services, and health care and social assistance.
"professional_and_business_services_administrative_and_support_a", -- Number of jobs in administration, support, waste management, and remediation services in Maryland. A subset of professional and business services.
"financial_activities_finance_and_insurance", -- Number of jobs in finance and insurance in Maryland. A subset of financial activities.
"trade_transportation_and_utilities_retail_trade", -- Number of jobs in retail trade in Maryland. A subset of trade, transportation, and utilities.
"government_federal", -- The number of federal government jobs in Maryland.
"government_total", -- The total number of all government jobs in Maryland. Equals the sum of federal, state, and local government.
"private_sector_total", -- The total number of non-government, non-farming jobs in Maryland across all industries.
"month" -- Month represented by the job counts reported
FROM
"opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9:latest"."bls_jobs_by_industry_category"
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 opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9 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 opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9: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 opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9Checkout 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 opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9:latestThis will download all the objects for the latest tag of opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9 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 opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9: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 opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9: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, opendata-maryland-gov/bls-jobs-by-industry-category-dpvc-hqj9 is just another Postgres schema.