cityofnewyork-us/covid19-expenditures-report-thut-5mdg
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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 covid19_expenditures_report table in this repository, by referencing it like:

"cityofnewyork-us/covid19-expenditures-report-thut-5mdg:latest"."covid19_expenditures_report"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "fiscal_year", -- The Fiscal Year (June - July) that the cost is associated with.
    "bc", -- Agency created code allocating funds and associating revenue within a Unit of Appropriation. For COVID-19 related costs, all Budget Codes must start with "CV".
    "contract_id", -- Unique identifier for the contract document in FMS
    "exp_type", -- Identifies whether the cost is an Expense or Capital cost.
    "pub_dt", -- 8-digit number for date of publication
    "obj_desc", -- Brief description of the Object Code
    "u_a_desc", -- Brief description of the Unit of Appropriation
    "u_a_code", -- Highest level measure of spending that has been authorized in the budget by the City Council for specific purposes,
    "obj_type", -- Identifies whether the cost is Personnel Service (PS) or Other Than Personnel Service (OTPS)
    "doc_id", -- Unique identifier for the expenditure document in FMS
    "agy_name", -- The name of the City agency incurring the cost.
    "exp_amount", -- Dollar amount transacted by the City within this expenditure
    "cap_id", -- For a Capital cost, the unique ID for the associated Capital Project.
    "cap_id_desc", -- Brief description of the project.
    "obj_code", -- Object Codes are part of the accounting structure on payment requests that represent the type of services that are being paid to a City agency's Vendor/Customer.
    "agy_code", -- Unique three-digit code representing each Agency in the City's Financial Management System (FMS).
    "date_of_exp", -- Date at which the expenditure is incurred
    "vendor", -- The legal entity or payee (if available) for the expenditure.
    "proj_fund_source", -- The expected revenue source to be used to cover these costs, including both Federal, State, and City sources.
    "bc_desc" -- Brief description of the Budget Code
FROM
    "cityofnewyork-us/covid19-expenditures-report-thut-5mdg:latest"."covid19_expenditures_report"
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/covid19-expenditures-report-thut-5mdg 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/covid19-expenditures-report-thut-5mdg: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/covid19-expenditures-report-thut-5mdg

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/covid19-expenditures-report-thut-5mdg:latest

This will download all the objects for the latest tag of cityofnewyork-us/covid19-expenditures-report-thut-5mdg 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/covid19-expenditures-report-thut-5mdg: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/covid19-expenditures-report-thut-5mdg: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/covid19-expenditures-report-thut-5mdg is just another Postgres schema.

Related Documentation:

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