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 camera_traffic_counts table in this repository, by referencing it like:

"datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9:latest"."camera_traffic_counts"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "bin_duration", -- Number of seconds for the aggregation interval: always 15 minutes
    "day", -- The numeric day of the aggregation interval
    "heavy_vehicle", -- A classifier for vehicles that are measured to be 17 feet or longer
    "record_id", -- A unique ID for each row created as a hash of intersection name, time, truck status, direction, and movement
    "direction", -- The travel direction of the approach toward the intersection
    "day_of_week", -- Starting with Sunday is 0 and Monday is 1, and so on
    "minute", -- The numeric minute of the aggregation interval starting time
    "seconds_in_zone_stddev", -- Standard deviation of "Seconds in Zone"
    "movement", -- The turning movement of respective traffic entering the intersection
    "speed_stddev", -- Standard deviation of all speed measurements, or 0 if Volume is less than 2.
    "read_date", -- The start of the respective time interval used for aggregation, UTC
    "volume", -- The number of vehicles traveling in the respective direction and making the respective turning movement throughout the 15-minute interval
    "speed_average", -- Average speed of vehicles that entered the intersection, including those that had started after the end of a red light
    "year", -- The numeric year of the aggregation interval
    "intersection_name", -- The general location of the counts. For further location information consult the 'Travel Detectors' dataset.
    "seconds_in_zone_average", -- Average amount of time that vehicles were in the measurement zone, including time that vehicles are stopped at a red light
    "month", -- The numeric month of the aggregation interval
    "hour", -- The numeric hour of the aggregation interval
    "atd_device_id" -- The ID of the device as noted in the "Traffic Detectors" table
FROM
    "datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9:latest"."camera_traffic_counts"
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 datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9 with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at datahub.austintexas.gov. When you querydatahub-austintexas-gov/camera-traffic-counts-sh59-i6y9: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 datahub.austintexas.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 \
  "datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9" \
  --handler-options '{
    "domain": "datahub.austintexas.gov",
    "tables": {
        "camera_traffic_counts": "sh59-i6y9"
    }
}'

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, datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9 is just another Postgres schema.