cityofnewyork-us/agency-authorized-parking-permits-a23q-dmjn
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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 agency_authorized_parking_permits table in this repository, by referencing it like:

"cityofnewyork-us/agency-authorized-parking-permits-a23q-dmjn:latest"."agency_authorized_parking_permits"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "year", -- Year the permit was issued.
    "abp_effectivedate", -- The first day the parking permit is active
    "abp_issuedate", -- The date the parking permit was issued
    "abpermitnumber", -- Unique 7 digit identifier assigned to each issued permit
    "parkingrestriction", -- Notes of parking exemptions or any areas the car can not park. 
    "agencytype", -- The type of the agency
    "vehicleplatestate", -- The state of the vehicle license plate number. 
    "privatevehicle", -- Is the permit for a Private vehicle?
    "issuingauthority", -- The name of the City Agency issued the authorized permit. 
    "parkingplacardnumber", -- Unique 7 digit identifier assigned to each issued permit.
    "abp_expirationdate", -- The last day the parking permit is active
    "active", -- The status of the permit
    "applicationplacardtype", -- The type of placard issued.
    "abpermitrecords_active", -- The status of the permit record
    "activepermit", -- The permit is active
    "agencydesc", -- The full name of the City Agency
    "agencyname", -- City agency initials. Agencies with numbers indicate branches or districts throughout City. For example: FDNY01-  Engine Company number for Fire Department or DOE15- School district for Department of Education.
    "arid", -- A sequential count for the number of records for each year.
    "returned", -- The parking permit was returned to issuer
    "parkingplacardtype", -- The name for the type of permit issued.
    "governmentvehicle", -- Is the permit for a Government vehicle??
    "deactivatedate", -- The date the parking permit was cancelled
    "returndate", -- The date the parking permit was returned to the issuer
    "permittype", -- Type of the permit
    "issuereason" -- The reason for the issuance of the parking permit
FROM
    "cityofnewyork-us/agency-authorized-parking-permits-a23q-dmjn:latest"."agency_authorized_parking_permits"
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/agency-authorized-parking-permits-a23q-dmjn 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/agency-authorized-parking-permits-a23q-dmjn: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/agency-authorized-parking-permits-a23q-dmjn

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/agency-authorized-parking-permits-a23q-dmjn:latest

This will download all the objects for the latest tag of cityofnewyork-us/agency-authorized-parking-permits-a23q-dmjn 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/agency-authorized-parking-permits-a23q-dmjn: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/agency-authorized-parking-permits-a23q-dmjn: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/agency-authorized-parking-permits-a23q-dmjn is just another Postgres schema.

Related Documentation:

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