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 feeding_mesa_revenues_and_expenditures table in this repository, by referencing it like:
"citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4:latest"."feeding_mesa_revenues_and_expenditures"or in a full query, like:
SELECT
":id", -- Socrata column ID
"activity_name", -- The activity that the department was engaged in that led to the transaction. Activities are generally recurring functions such as accounting, inspections, or planning. Activities are used to assign accounting entries to a core business process.
"sub_activity_name", -- Activities are broken down into sub-activities for reporting and analysis purposes.
"sub_fund_code", -- The numbers assigned for the breakdown of a fund based on purpose, classification, and other specific characteristics.
"fund_code", -- The number assigned to the governmental segment that benefited from the transaction.
"department_name", -- The department that benefited from the transaction.
"budget_year_date", -- Year of the revenue or expenditure
"document_code", -- The number assigned to the type of document the transaction was recorded in the accounting system.
"sub_object_code", -- The number assigned to line items within an object to track specific expenditures related to that object.
"fund_name", -- The governmental segment that benefited from the transaction. Examples include Cemetery, Transit and Arts and Culture.
"unit_name", -- The organizational unit within the department that benefited from the transaction. Examples include Planning, Development Services, Energy Resources, Electric Utility and Gas Utility.
"fiscal_year", -- A 12-month period of time to which the Annual Budget applies and at the end of which, a governmental unit determines its financial position and the results of its operations. For the City of Mesa, the fiscal year is July 1 through June 30
"department_code", -- The number assigned to the department that benefited from the transaction.
"budget_year", -- Year of the revenue or expenditure
"fiscal_year_date", -- Fiscal year of the revenue or expenditure
"document_department_code", -- Coded documentation of the employees associated with the revenue or expenditure, by department.
"unit_code", -- A Chart of Accounts element that functions as both a budget/expense center and an organizational level element. In this case, it indicates the department that benefited from the transaction.
"month_valid", -- Month derived from the “Date Valid” field.
"object_code", -- The number assigned to the type of expense being paid for a tangible item or service obtained. In the private sector, this would be called a general ledger account number, however in the government sector, these are most often referred to as object codes.
"object_name", -- The type of expense being paid. In the private sector, this would be called a general ledger account, however in the government sector, these are most often referred to as objects. Examples include Payroll, Professional Services or Travel.
"sub_object_name", -- The name of the sub object.
"amount", -- The amount of the transaction
"document_id", -- The number assigned to the transaction by the accounting system.
"date_valid", -- The time and date the data was last updated from the accounting system.
"vendor_customer_code", -- Number assigned to a vendor for tracking purposes.
"vendor_legal_name", -- Plain Text Legal name of the vendor paid
"revenue_source_code", -- The number assigned to a revenue source for tracking purposes.
"activity_code", -- The number assigned to the activity the department was engaged in that led to the transaction.
"sub_activity_code", -- The number assigned to a sub-activity.
"revenue_source_name", -- The name of the revenue source.
"reporting_code", -- The number assigned to a reporting mechanism used to track the expenditures related to a specific event or item. Examples are shows at the Mesa Arts Center and Park expenses.
"year_valid" -- Year derived from the “Date Valid” field.
FROM
"citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4:latest"."feeding_mesa_revenues_and_expenditures"
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 citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4 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 citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4: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 citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4Checkout 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 citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4:latestThis will download all the objects for the latest tag of citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4 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 citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4: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 citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4: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, citydata-mesaaz-gov/feeding-mesa-revenues-and-expenditures-aw74-5nf4 is just another Postgres schema.