cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w
Loading...

Query the Data Delivery Network

Query the DDN

The 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 capital_projects_database_cpdb_projects table in this repository, by referencing it like:

"cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w:latest"."capital_projects_database_cpdb_projects"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "maprojid", -- Unique identifier that defines a discrete project. The maprojid is a concatenation of magency and projectid and it is the primary key.
    "totalnoncityplannedcommit", -- Sum of Non-City funding across all commitments associated with the project.
    "magencyacro", -- Common acronym of the city agency managing the project. This value is derived from the three digit managing agency code.
    "ccnonexempt", -- Sum of City Cost (Non-Exempt) funding across all commitments associated with the project.
    "mindate", -- The earliest panned commitment date associated with the project.
    "maxdate", -- The latest panned commitment date associated with the project.
    "totalspend", -- Sum of check values from Checkbook NYC associated with the project.
    "totalcityplannedcommit", -- Sum of City funding across all commitments associated with the project.
    "totalplannedcommit", -- Sum of City Cost and Non-City Cost, which reports the total planned commitments for the project allocated in the Capital Commitment Plan.
    "ccexempt", -- Sum of City Cost (Exempt) funding across all commitments associated with the project.
    "nccother", -- Sum of Other funding across all commitments associated with the project.
    "typecategory", -- Classification given by DCP based on keywords found in the short description describing if a projects is Fixed Asset, Lump Sum, or ITT, Vehicles, and Equipment.
    "ccpversion", -- Reports the version of the Capital Commitment Plan which the record is based on.
    "projectid", -- Alphanumeric code created by the sponsor agency that identifies a distinct project. A Project ID must be unique within a managing agency.
    "magency", -- Three digit code of the distinct City agency managing the project. The managing agency is the agency overseeing the construction or implementation of a project.
    "description", -- Short description of the project as described by the sponsor agency. If one projectid had many descriptions the longest description is reported by CPDB.
    "magencyname", -- Common name for the city agency mananging the project. This value is derived from the three digit managing agency code.
    "nccfederal", -- Sum of Federal funding across all commitments associated with the project.
    "nccstate" -- Sum of State funding across all commitments associated with the project.
FROM
    "cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w:latest"."capital_projects_database_cpdb_projects"
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 cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w with SQL in under 60 seconds.

Query Your Local Engine

Install Splitgraph Locally
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 cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w: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 cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w

Checkout 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 cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w:latest

This will download all the objects for the latest tag of cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w 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 cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w: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 cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w:latest

This 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, cityofnewyork-us/capital-projects-database-cpdb-projects-fi59-268w is just another Postgres schema.

Related Documentation:

Loading...