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 county_spending table in this repository, by referencing it like:
"montgomerycountymd-gov/county-spending-vpf9-6irq:latest"."county_spending"or in a full query, like:
SELECT
":id", -- Socrata column ID
"payment_date", -- The date the check was written or the payment was made.
"payment_method", -- Type of payment, such as check, EFT, credit card (MCG JPM SUA) or wire transactions.
"inv_date", -- "The Invoice date is the date listed in ERP as the invoice date and may contain a null value. "
"invoice_id", -- A number assigned to an invoice, used to uniquely identify a supplier’s invoice.
"vendor", -- Supplier name
"description", -- Lowest level of description regarding how the County expends monies (Example: local travel).
"fund", -- Accounting device that the County uses to keep track of specific sources of funding and spending for particular purposes (Example: General Fund, Grant Fund; CIP Fund)
"po_line", -- The line number for a specific item or service that is being purchased on the Purchase Order (PO). (For example, if five different items are purchased, then there will be five PO lines.)
"contract_num", -- A unique number used to identify a County contract.
"payment_id", -- The identifying number on the paper check, electronic payment, or credit card transactions.
"amount", -- The dollar amount associated with an invoice distribution line.
"invoice_line", -- A line number from a supplier invoice, for the County’s purchase of a good or a service.
"vendor_zip", -- The zip code for the supplier’s address to which the supplier’s payment is sent.
"vendor_id", -- A unique supplier identification number
"program", -- Subdivision of Departments made up of a primary service, function, or set of activities which address a specific responsibility or goal within an agency's mission. (Example: Operations, Budget, Aquatics).
"department", -- The name of the Department.
"service", -- High Organization level grouping, such as Public Safety and Community Development.
"fiscal_year_period", -- Our fiscal year runs July 1st through June 30th. A period is equal to one month (Example: period 1 is July, period 2 is August, period 3 is September, etc.)
"invoice_distribution_line", -- The line number indicating which Department(s) or Program(s) the invoice is charged to. (For example, if five different departments are being charged for an item, then there will be five distribution lines.)
"account_code", -- A unique account identification number (related to Account Name field)
"category", -- Represents how data is presented on the County’s financial statements (expense, revenue, liability, asset, owner’s equity or fund balance).
"payment_status", -- Status of a payment through the banking system, such as Negotiable, Void, or Reconciled.
"expense_category", -- The highest level grouping of account codes that the County has spent funds on. For example, the “Travel” expense.
"fiscal_year", -- The County’s fiscal year (such as 2015) represents a 12 month period used for annual financial reporting beginning July 1st through June 30th.
"po_num" -- A unique number used to identify a purchase order issued to a vendor.
FROM
"montgomerycountymd-gov/county-spending-vpf9-6irq:latest"."county_spending"
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 montgomerycountymd-gov/county-spending-vpf9-6irq 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 montgomerycountymd-gov/county-spending-vpf9-6irq: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 montgomerycountymd-gov/county-spending-vpf9-6irqCheckout 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 montgomerycountymd-gov/county-spending-vpf9-6irq:latestThis will download all the objects for the latest tag of montgomerycountymd-gov/county-spending-vpf9-6irq 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 montgomerycountymd-gov/county-spending-vpf9-6irq: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 montgomerycountymd-gov/county-spending-vpf9-6irq: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, montgomerycountymd-gov/county-spending-vpf9-6irq is just another Postgres schema.