Query the Data Delivery Network

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 emergency_communications_24hour_call_volume table in this repository, by referencing it like:

"norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj:latest"."emergency_communications_24hour_call_volume"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "percentage_of_911_calls_2", -- The percentage of 911 calls during the 24-hour period that were answered in 20 seconds or less.
    "outbound_non_911_calls", -- The number of outbound non-911 calls conducted during the 24-hour period.
    "average_call_duration_in", -- The average 911 and non-911 call duration in seconds during the 24-hour period.
    "average_text_session_duration", -- The average number of seconds that the text session lasts.
    "average_messages_per_session", -- The average number of text messages per text session.
    "teletypewriter_calls", -- The number of teletypewriter (TTY) calls answered during the 24-hour period.
    "percentage_of_911_calls_1", -- The percentage of 911 calls during the 24-hour period that were answered in 15 seconds or less.
    "_911_calls_answered", -- The number of 911 calls answered during the 24-hour period.
    "percentage_of_911_calls", -- The percentage of 911 calls during the 24-hour period that were answered in 10 seconds or less.
    "percentage_of_911_calls_3", -- The percentage of 911 calls during the 24-hour period that were answered in 40 seconds or less.
    "_911_text_sessions", -- The number of 911 text sessions conducted during the 24-hour period.
    "average_seconds_to_answer", -- The average number of seconds during the 24-hour period that it took to answer 911 calls.
    "_911_calls_abandoned", -- The number of 911 calls made to the emergency communication center that were dropped or abandoned by the caller prior to a telecommunicator answering. 911 telecommunicators call back these abandoned calls to see if there is an emergency.
    "abandoned_non_911_calls", -- The number of non-911 calls abandoned or dropped by the caller prior to the telecommunicator answering.
    "average_teletypewriter", -- The average number of TTY messages per call during the 24-hour period.
    "average_teletypewriter_call", -- The average number of seconds per TTY call during the 24-hour period.
    "date", -- Date of the emergency communications calls. Each row of data accounts for a 24-hour period occurring during this date.
    "inbound_non_911_calls", -- The number of non-911 calls answered during the 24-hour period.
    "total_calls_and_texts" -- The total emergency communications call and texts processed. This represents the total of fields 911 Calls Answered, 911 Text Sessions, Inbound Non-911 Calls, and Outbound Non-911 Calls.
FROM
    "norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj:latest"."emergency_communications_24hour_call_volume"
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 norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.norfolk.gov. When you querynorfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj: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

bash -c "$(curl -sL https://github.com/splitgraph/splitgraph/releases/latest/download/install.sh)"

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.norfolk.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 \
  "norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj" \
  --handler-options '{
    "domain": "data.norfolk.gov",
    "tables": {
        "emergency_communications_24hour_call_volume": "nj5u-a2dj"
    }
}'

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, norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj is just another Postgres schema.