ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq
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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 new_york_state_locality_hierarchy_with_websites table in this repository, by referencing it like:

"ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq:latest"."new_york_state_locality_hierarchy_with_websites"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "type", -- Type name: County or Borough/County; City; Town; Village.
    "municipality", -- Name of municipality, if applicable; blank if Type is ‘County’.
    "type_code", -- Type of entity described: 1 – County or Borough/County;  2 – City;  3 – Town;  4 – Village. 
    "city_name", -- City name, if applicable; blank if Type is not ‘City’ or 'Borough/County'.
    "website", -- Web link for the municipality or county, if available.
    "state_fips", -- 2-digit state Federal Information Processing Standard (FIPS) state code; New York state is 36.
    "swis_code", -- Each County, City, Town-Outside Village (TOV) area and Village in New York State has a six digit Statewide Information System (SWIS) code associated with it. The SWIS code is formatted as follows: "CCCTVT" where CC = County Code; CT = City/Town Code; VT = Village/TOV Code.  SWIS codes may be searched at http://orpts.tax.ny.gov/cfapps/MuniPro/swis/index.cfm
    "village_name", -- Village name, if applicable; blank if Type is not ‘Village’.
    "county_fips", -- 5-digit county FIPS code (concatenated state FIPS and county codes) that uniquely identifies each county in each state.
    "county_code", -- 3-digit county code for the county; they are odd numbers that are not unique to each state.
    "town_name", -- Town name, if applicable; blank if Type is not ‘Town’.
    "gnis_id", -- Geographic Names Information System (GNIS) number for the municipality.  Names may be searched at http://geonames.usgs.gov/apex/f?p=gnispq Note that villages must be searched as ‘Village of <name>’ on the database to return the proper GNIS ID. 
    "county", -- NYS county name.
    "_2nd_county" -- The name of a second county to which a municipality belongs, if applicable; blank if the municipality is in only one county.
FROM
    "ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq:latest"."new_york_state_locality_hierarchy_with_websites"
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 ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq 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 ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq: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 ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq

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 ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq:latest

This will download all the objects for the latest tag of ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq 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 ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq: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 ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq: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, ny-gov/new-york-state-locality-hierarchy-with-websites-55k6-h6qq is just another Postgres schema.

Related Documentation:

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