littlerock-gov/police-calls-for-service-december-2020-to-year-to-piyt-g5xb
Icon for Socrata external plugin

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 police_calls_for_service_december_2020_to_year_to table in this repository, by referencing it like:

"littlerock-gov/police-calls-for-service-december-2020-to-year-to-piyt-g5xb:latest"."police_calls_for_service_december_2020_to_year_to"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "firstenroutewitharrivaltime", -- The time that the first police unit that indicated they were en route to the call arrived at the incident location.
    ":@computed_region_3ti5_7qwp", -- This column was automatically created in order to record in what polygon from the dataset 'Neighborhood Association Boundaries 2019' (3ti5-7qwp) the point in column 'location' is located.  This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    ":@computed_region_kp8k_tt9x", -- This column was automatically created in order to record in what polygon from the dataset 'Neighborhood Associations' (kp8k-tt9x) the point in column 'location' is located.  This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    ":@computed_region_2m93_nqiv", -- This column was automatically created in order to record in what polygon from the dataset 'Neighborhood Associations 2021' (2m93-nqiv) the point in column 'location' is located.  This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    ":@computed_region_t2qk_n4g3", -- This column was automatically created in order to record in what polygon from the dataset 'Wards' (t2qk-n4g3) the point in column 'location' is located.  This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    ":@computed_region_bvk6_adqe", -- This column was automatically created in order to record in what polygon from the dataset 'LRPD Patrol Districts 2021' (bvk6-adqe) the point in column 'location' is located.  This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
    ":@computed_region_efe8_9vpd",
    ":@computed_region_r36e_4rwh",
    "incidentdate", -- Date of Call For Service
    "incidentnumber", -- Unique Identifier for each Police Incident
    "incidenttypecode", -- Code for call type
    "incidenttypedescription", -- Description of call type
    "address", -- Generalized address of call
    "insertedtimestamp", -- Date and Time the Call For Service was inserted into CAD
    "incidentstarteddatetime", -- Data and Time the Incident began
    "callreceivedtime",
    "firstunitdispatchedtime", -- Time the first police unit was notified of the call for service
    "firstunitenroutetime", -- Time the first police unit indicated they were en route to the incident
    "firstunitarrivedtime", -- Time the first police unit indicated they had arrived at the scene
    "firstdispatchwitharrivaltime", -- The time that the first police unit dispatched to the incident indicated they had arrived at the incident location
    "firstunitassignmentwitha", -- Time the first unit assigned to the call arrived at the scene of the incident
    "latitude", -- Approximate latitude of incident
    "zipcode", -- Zip code of call
    "longitude", -- Approximate longitude of incident
    "areaname", -- Police division where incident occurred
    "district", -- Police district where incident occurred
    "firstunitassignmenttime", -- Time the first unit was assigned to the call
    "location" -- Approximate location of incident
FROM
    "littlerock-gov/police-calls-for-service-december-2020-to-year-to-piyt-g5xb:latest"."police_calls_for_service_december_2020_to_year_to"
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 littlerock-gov/police-calls-for-service-december-2020-to-year-to-piyt-g5xb with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.littlerock.gov. When you querylittlerock-gov/police-calls-for-service-december-2020-to-year-to-piyt-g5xb:latest on the DDN, we "mount" the repository using the socrata mount handler. The mount handler proxies your SQL query to the upstream data source, translating it from SQL to the relevant language (in this case SoQL).

We also cache query responses on the DDN, but we run the DDN on multiple nodes so a CACHE_HIT is only guaranteed for subsequent queries that land on the same node.

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 (like this repository), 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, where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.

Mounting Data

This repository is an external repository. It's not hosted by Splitgraph. It is hosted by data.littlerock.gov, and Splitgraph indexes it. This means it is not an actual Splitgraph image, so you cannot use sgr clone to get the data. Instead, you can use the socrata adapter with the sgr mount command. Then, if you want, you can import the data and turn it into a Splitgraph image that others can clone.

First, install Splitgraph if you haven't already.

Mount the table with sgr mount

sgr mount socrata \
  "littlerock-gov/police-calls-for-service-december-2020-to-year-to-piyt-g5xb" \
  --handler-options '{
    "domain": "data.littlerock.gov",
    "tables": {
        "police_calls_for_service_december_2020_to_year_to": "piyt-g5xb"
    }
}'

That's it! Now you can query the data in the mounted table like any other Postgres table.

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, littlerock-gov/police-calls-for-service-december-2020-to-year-to-piyt-g5xb is just another Postgres schema.