brla-gov/animal-control-incidents-qmns-hw3s
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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 animal_control_incidents table in this repository, by referencing it like:

"brla-gov/animal-control-incidents-qmns-hw3s:latest"."animal_control_incidents"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "dispoff", -- Name of officer responsible for disposition of animal 
    "dispdate", -- Date of disposition 
    "age", -- Age of animal
    "color", -- Color of animal
    "loczip", -- ZIP code of incident
    "location", -- Location of incident
    "impound_time", -- Time animal was brought into shelter
    "impound_date", -- Date animal was brought into shelter
    "cequip", -- ID of vehicle used to respond to incident
    "cpofficer", -- ID of officer who was dispatched to incident
    "cpstreet", -- Street  of complaintant
    "cavailable", -- Time officer was finished with incident and was once again available for another call
    "cpdisptime", -- Time an officer was dispatched to incident
    "cptimercvd", -- Time incident was called in
    "cpdate", -- Date incident was called in 
    "impoundno", -- Number used to track animals being impounded into shelter
    "service_code", -- Code is used at the responding officer's discretion; may be the same as CPREMARKS but may be different if issue is not what complaint reported
    "cprequest", -- Type of incident being reported
    "cpdispatcher", -- ID of employee who dispatched the officer to incident
    "cpoperator", -- ID of employee who took the call
    "cpfileno", -- Internal file number of incident
    "vacdate", -- Date of vaccination of animal, provided by owner
    "disposition", -- How animal was processed once at ACC (e.g. transferred to the Companion Animal Alliance, an organization with which the City-Parish is contracted to perform all animal sheltering, adoptions, and animal reclaimations) 
    "petname", -- Pet has a name.  Used when turning in animal to be adopted.
    "vacc_num", -- Vaccination id number of animal, provided by owner
    "collar", -- Type of collar, if any
    "breed", -- Breed of animal
    "species", -- Species of animal
    "size", -- Size of animal
    "carrival", -- Time officer arrived on scene
    "municipality", -- Municipality of incident
    "cdispo", -- Indicates if officer was dispatched (D) or the call had to be postponed (K) and addressed the following day. 
    "collar_color", -- Collar color
    "cpremarks", -- Remarks provided during initial call, if any
    "temperment", -- Temperment of animal
    "condition", -- Condition of animal
    "sex", -- Sex of animal
    "cpstandby" -- Not dispatched by cad but there is dispatch info in record
FROM
    "brla-gov/animal-control-incidents-qmns-hw3s:latest"."animal_control_incidents"
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 brla-gov/animal-control-incidents-qmns-hw3s 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 brla-gov/animal-control-incidents-qmns-hw3s: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 brla-gov/animal-control-incidents-qmns-hw3s

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 brla-gov/animal-control-incidents-qmns-hw3s:latest

This will download all the objects for the latest tag of brla-gov/animal-control-incidents-qmns-hw3s 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 brla-gov/animal-control-incidents-qmns-hw3s: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 brla-gov/animal-control-incidents-qmns-hw3s: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, brla-gov/animal-control-incidents-qmns-hw3s is just another Postgres schema.

Related Documentation:

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