citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85
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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 historical_preservation_responses table in this repository, by referencing it like:

"citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85:latest"."historical_preservation_responses"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "record_status_date", -- Effective date of current status
    "record_lessthan_10days", -- 1=yes, 0=no to question 'Was request responded to in less than 10 days'
    "permit_description", -- Description of work being done under permit
    "longitude", -- System generated longitude of permit address
    "assigned_user", -- City employee assigned to permit
    "latitude", -- System generated latitude of permit address
    "task_status", -- Status of current workflow task
    "record_status_year", -- Effective year of current status
    "street_name", -- Street name where permit work will be performed
    "start_date", -- Date assigned user started work on this permit application
    "record_opened_date", -- Date record opened
    "row_id", -- Unique Row Identifier
    "task", -- Current workflow task
    "number_of_days", -- Number of days between start and end dates
    "record_status", -- Current status of permit application
    "street_direction", -- Street direction where permit work will be performed
    "record_type", -- Type of permit applied for (e.g. Residential)
    "end_date", -- Date assigned user completed work on this permit application
    "total_records", -- Always a '1'. System generated, not a useful field
    "location", -- System generated geolocation of permit address
    "council_district", -- Council district number of permit application address
    "street_number", -- Street number where permit work will be performed
    "task_status_date", -- Effective date of current workflow task status
    "street_suffix", -- Street suffix where work will be performed
    "street_address", -- Street address where permit work will be performed
    "permit_address", -- Address where permit work will be performed
    "record_id", -- System generated permit number
    "record_status_month" -- Effective month of current status
FROM
    "citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85:latest"."historical_preservation_responses"
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 citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85 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 citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85: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 citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85

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 citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85:latest

This will download all the objects for the latest tag of citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85 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 citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85: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 citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85: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, citydata-mesaaz-gov/historical-preservation-responses-cw5y-hc85 is just another Postgres schema.

Related Documentation:

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