Query the Data Delivery Network
Query the DDNThe 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.
Query Your Local Engine
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 datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9: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 datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9Checkout 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 datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9:latestThis will download all the objects for the latest tag of datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9 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 datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9: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 datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9:latestThis 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, datahub-austintexas-gov/camera-traffic-counts-sh59-i6y9 is just another Postgres schema.