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 nonprofit_corporations table in this repository, by referencing it like:
"cambridgema-gov/nonprofit-corporations-qyv9-s3hq:latest"."nonprofit_corporations"or in a full query, like:
SELECT
":id", -- Socrata column ID
"income", -- Annual income reported to the IRS.
"assets", -- Organizational assets reported to the IRS.
"zip_code", -- Mailing address zip code provided to IRS.
"location", -- Mailing address of organization provided to IRS.
"second_name", -- Secondary name of organization.
"name", -- Primary name of organization.
"ein", -- Employer Identification Number (EIN) is a nine-digit number issued by the IRS to uniquely identify an organization.
"geocoded_column", -- Latitude-Longitude for organization address. PO Box addresses are not geocoded.
"ntee_code", -- National Taxonomy of Exempt Entities (NTEE) code. The code is up to four digits long and is used to classify a non-profit organization in terms of its primary exempt activity.
"activity_name_3", -- A description of an organization’s third activity code.
"activity_code_3", -- A three-digit code that reflects an organization’s purposes, activities, operations or type. Has been replaced by the NTEE coding system.
"ntee_core_code_name", -- A description of the organization’s NTEE core code.
"activity_name_2", -- A description of an organization’s second activity code.
"foundation_type_description", -- A description of the type of non-profit organization.
"organization_type", -- A numerical code indicating the corporate form of the organization.
"foundation_type", -- A numerical code indicating the type of type of non-profit organization.
"geocoded_column_zip",
":@computed_region_rffn_qbt6",
":@computed_region_v7jj_366k",
":@computed_region_guic_hr4a",
":@computed_region_rcj3_ccgu",
"data_current_as_of", -- Date that the source dataset was publicly posted by the IRS.
"organization_type_name", -- A description of the corporate form of the organization.
":@computed_region_swkg_bavi",
":@computed_region_e4yd_rwk4",
"ntee_common_code", -- The first digit of the full NTEE code, which categorizes non-profit organizations into 26 major groups.
"activity_code_2", -- A three-digit code that reflects an organization’s purposes, activities, operations or type. Has been replaced by the NTEE coding system.
"activity_name_1", -- A description of an organization’s first activity code.
"ntee_common_code_name", -- A description of the organization’s NTEE common code.
"activity_code_1", -- A three-digit code that reflects an organization’s purposes, activities, operations or type. Has been replaced by the NTEE coding system.
"ntee_core_code", -- The first three digits of the full NTEE code, which categorizes non-profit organizations into more specific categories within the 26 major groups.
"geocoded_column_address",
"geocoded_column_city",
"geocoded_column_state"
FROM
"cambridgema-gov/nonprofit-corporations-qyv9-s3hq:latest"."nonprofit_corporations"
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/nonprofit-corporations-qyv9-s3hq 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/nonprofit-corporations-qyv9-s3hq: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/nonprofit-corporations-qyv9-s3hqCheckout 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/nonprofit-corporations-qyv9-s3hq:latestThis will download all the objects for the latest tag of cambridgema-gov/nonprofit-corporations-qyv9-s3hq 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/nonprofit-corporations-qyv9-s3hq: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/nonprofit-corporations-qyv9-s3hq: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/nonprofit-corporations-qyv9-s3hq is just another Postgres schema.