cityofnewyork-us/weights-measures-and-other-tests-8fei-z6rz
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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 weights_measures_and_other_tests table in this repository, by referencing it like:

"cityofnewyork-us/weights-measures-and-other-tests-8fei-z6rz:latest"."weights_measures_and_other_tests"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "latitude", -- Latitude of business’s address.
    "zip", -- The zip code where the business is located.
    "street", -- The street name of the business’s address.
    "building_number", -- The building number of the business’s address.
    "approved", -- The number of items that passed the inspection.
    "test_type", -- The test performed and the type of equipment tested. Refer to Appendix B for details.
    "inspection_date", -- Date when DCA conducted inspection.
    "industry", -- The category that describes the business.
    "business_name", -- Primary Business Name.
    "record_id", -- An identification number assigned by DCA to record each inspection. For DCA office tracking purposes.
    "certificate_number", -- Certificate number issued to the business upon inspection. Note that there may be multiple certificate numbers for a single inspection.
    "longitude", -- Longitude of business’s address.
    "state", -- The state where the business is located.
    "unit", -- The unit number of the business’s address.
    "city", -- The city where the business is located.
    "condemned", -- The number of items that DCA condemned.
    "confiscated", -- The number of items that DCA confiscated.
    "inspection_result", -- Result of inspection (e.g., No Violation Issued, Violation Issued, Pass, Fail). Refer to Appendix A for details.
    "notes" -- This section is used only if the Inspection Result is “Fail” and the Test Type is “MISC FUEL OIL CHECK-94.” It provides an explanation of why the fuel oil truck was condemned.
FROM
    "cityofnewyork-us/weights-measures-and-other-tests-8fei-z6rz:latest"."weights_measures_and_other_tests"
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/weights-measures-and-other-tests-8fei-z6rz 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/weights-measures-and-other-tests-8fei-z6rz: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/weights-measures-and-other-tests-8fei-z6rz

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/weights-measures-and-other-tests-8fei-z6rz:latest

This will download all the objects for the latest tag of cityofnewyork-us/weights-measures-and-other-tests-8fei-z6rz 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/weights-measures-and-other-tests-8fei-z6rz: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/weights-measures-and-other-tests-8fei-z6rz: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/weights-measures-and-other-tests-8fei-z6rz is just another Postgres schema.

Related Documentation:

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