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 city_revenues table in this repository, by referencing it like:
"citydata-mesaaz-gov/city-revenues-ntuh-v7ru:latest"."city_revenues"or in a full query, like:
SELECT
":id", -- Socrata column ID
"fiscal_year", -- Fiscal year of the transaction
"major_program_name", -- A project the City is working on Generally, a major program is created to capture all of the costs of creating a new or improving an existing asset before the asset is placed in service Major programs may also track costs related to a grant awarded to the City
"program_code", -- The number assigned to a program
"program_name", -- A program represents a smaller segment of a project the City is working on For example, renovating a Park would be a major program, installing the bathroom would be a program
"as_phase_code", -- The number assigned to a phase of a project
"phase_name", -- A project is split into phases which generally represent Pre-design/Design/Construction or may be split into Purchases (where no construction is involved in the acquisition of the asset)
"unit_code", -- The number assigned to the organizational unit within the department that benefited from the transaction
"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.
"reporting_code_name", -- 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.
"document_type_code", -- The number assigned to the type of document the transaction was recorded in the accounting system
"document_type_name", -- The type of document the transaction was recorded in the accounting system
"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.
"document_id", -- The number assigned to the transaction by the accounting system
"amount", -- The Amount of the transaction
"legal_name", -- Legal Name of the revenue source
"major_program_code", -- The number assigned to a project
"appropriation_code", -- The number assigned to the type of appropriation of the transaction
"revenue_code", -- The number assigned to the type of revenue received 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 Revenue Source codes
"sub_activity_code", -- The number assigned to a sub-activity
"fiscal_month_name", -- Transaction month in the fiscal year
"calendar_year", -- Calendar year of the transaction
"appropriation_name", -- The type of appropriation of the transaction These will either be the Base Operating Budget or a Capital Improvement Project
"date", -- The time and date the data was last updated from the accounting system
"accounting_period", -- The accounting period the transaction was recorded The City's accounting year runs from July 1 to June 30, where July is accounting period 1
"record_id", -- Unique Record Identifier that is being used for sorting and grouping purposes
"fund_code", -- The number assigned to the governmental segment that benefited from the transaction
"fund_name", -- The governmental segment that benefited from the transaction. Examples include Cemetery, Transit and Arts and Culture.
"sub_fund_code", -- The numbers assigned for the breakdown of a fund based on purpose, classification, and other specific characteristics
"sub_fund_name", -- The breakdown of a fund based on purpose, classification, and other specific characteristics
"department_code", -- The number assigned to the Department that benefited from the transaction
"department_name", -- The Department that benefited from the transaction
"business_objective_code", -- The number assigned to a major line of business that aligns denotes a primary public purpose; and defines where the City allocates its resources
"accounting_fiscal_year", -- The Accounting Fiscal Year the Document was created. The Accounting Fiscal year is determined by rules of recognition of liability or revenue and can differ from the Budget Fiscal Year The City's Fiscal Year is from July 1 to June 30.
"row_id", -- Unique identifier for each row of the dataset
"business_objective_name", -- A major line of business that aligns with one or more of the purpose; and defines where the City allocates its resources. Examples include Fleet Services and Economic Development.
"service_level_code", -- The number assigned to a group of Core Business Processes related by a common purpose (mission, outcomes, and expected performance) This level of structure is optional depending on departmental needs
"service_level_name", -- A group of Core Business Processes related by a common purpose (mission, outcomes, and expected performance) This level of structure is optional depending on departmental needs. Examples include Operations Bureau and Investigations Bureau.
"core_business_process_code", -- The number assigned to a collection of related programs and services that are designed and managed to achieve a common outcome or set of outcomes
"core_business_proces_name", -- A collection of related programs and services that are designed and managed to achieve a common outcome or set of outcomes These include Patrol, Metro, and Criminal Investigations
"activity_code", -- The number assigned to the activity the department was engaged in that led to the transaction
"activity_name", -- The activity the department was engaged in that led to the transaction Activities are generally recurring activities such as accounting, inspections or planning
"sub_activity_name", -- Some activities are broken down into sub-activities for reporting and analysis purposes
"revenue_category_code", -- The number assigned to the category of revenue on the chart of accounts
"revenue_category_name", -- The grouping of revenue types into categories on the chart of accounts Category examples include Taxes and Intergovernmental
"revenue_type_code", -- The number assigned to the Revenue Type on the chart of accounts
"revenue_type_name", -- A grouping of revenues into Types on the chart of accounts Types are then grouped into categories
"revenue_name" -- The type of revenue received In the private sector, this may be called a General Ledger account, however in the Government sector, these are most often referred to as Revenue Sources. Examples include City Sales Tax, Highway User Tax and State Grants.
FROM
"citydata-mesaaz-gov/city-revenues-ntuh-v7ru:latest"."city_revenues"
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/city-revenues-ntuh-v7ru 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/city-revenues-ntuh-v7ru: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/city-revenues-ntuh-v7ruCheckout 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/city-revenues-ntuh-v7ru:latestThis will download all the objects for the latest tag of citydata-mesaaz-gov/city-revenues-ntuh-v7ru 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/city-revenues-ntuh-v7ru: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/city-revenues-ntuh-v7ru: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/city-revenues-ntuh-v7ru is just another Postgres schema.