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 smart_green_infrastructure_monitoring_sensors table in this repository, by referencing it like:
"cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ih:latest"."smart_green_infrastructure_monitoring_sensors"or in a full query, like:
SELECT
":id", -- Socrata column ID
"units_abbreviation", -- Commonly accepted scientific abbreviation of the "Units" column.
"measurement_id", -- A unique identifier for the record, within all records produced by the Data Stream. The same Measurement ID could exist in two or more Data Streams.
"resource_id", -- An identifier for the resource providing the data. Within a Data Stream, the specific resource may change over time, even while providing comparable data.
"measurement_value", -- Value related to the sensor reading, in units expressed in "Units" column.
"longitude", -- Longitude of the sensor providing the measurement in WGS84 coordinates
"data_stream_id", -- An identifier for the measurement type and location. All records with the same value should be comparable.
"measurement_description", -- Description of the type of sensor providing the reading.
"measurement_type", -- Description of the measurement.
"units", -- The named-units describing the numerical units in "Measurement Value".
"record_id", -- A unique identifier for each record in the dataset.
"latitude", -- Latitude of the sensor providing the measurement in WGS84 coordinates
"measurement_time", -- Time the Measurement Value relates to in Central Daylight Time (UTC -5).
"measurement_title", -- Full title description of measurement, including name of location and measurement description.
"measurement_period_type", -- Whether "Measurement Value" indicates an instantaneous or cumulative reading.
"location", -- Latitude and Longitude of the sensor providing the measurement in WGS84 coordinates.
"measurement_medium" -- Whether the measurement pertains to the atmosphere or soil.
FROM
"cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ih:latest"."smart_green_infrastructure_monitoring_sensors"
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 cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ih 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 cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ih: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 cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ihCheckout 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 cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ih:latestThis will download all the objects for the latest tag of cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ih 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 cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ih: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 cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ih: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, cityofchicago/smart-green-infrastructure-monitoring-sensors-ggws-77ih is just another Postgres schema.