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 inverness_county_water_quality_data table in this repository, by referencing it like:
"novascotia-ca/inverness-county-water-quality-data-a9za-3t63:latest"."inverness_county_water_quality_data"or in a full query, like:
SELECT
":id", -- Socrata column ID
"qc_flag_salinity_psu", -- Quality control flag for salinity. Maximum flag value from three automated quality control tests: grossrange, spike, and rolling_sd. Flag values can be: "Pass", "Not Evaluated", "Suspect/Of Interest", or "Fail"
"qc_flag_dissolved_oxygen_uncorrected_mg_per_l", -- Quality control flag for dissolved oxygen (mg/L). Maximum flag value from four automated quality control tests: grossrange, climatology, spike, and rolling_sd. Flag values can be: "Pass", "Not Evaluated", "Suspect/Of Interest", or "Fail"
"qc_flag_dissolved_oxygen_percent_saturation", -- Quality control flag for dissolved oxygen (percent saturation). Maximum flag value from four automated quality control tests: grossrange, climatology, spike, and rolling_sd. Flag values can be: "Pass", "Not Evaluated", "Suspect/Of Interest", or "Fail"
"latitude", -- Latitude of the deployment (decimal degrees)
"lease", -- Aquaculture lease number associated with the station (where applicable)
"temperature_degree_c", -- Temperature measurement, in degrees Celsius
"sensor_depth_measured_m", -- Depth of the sensor, as measured by the sensor in metres
"salinity_psu", -- Salinity measurement, in practical salinity units
"dissolved_oxygen_percent_saturation", -- Dissolved oxygen measurement, in units of percent saturation
"depth_crosscheck_flag", -- Quality control flag for sensor depth at low tide. Flag values can be "Pass", "Not Evaluated", "Suspect/Of Interest", or "Fail". The same flag is applied to the whole deployment.
"sensor_depth_at_low_tide_m", -- Estimated depth of the sensor at low tide, in metres, based on its position in the sensor string configuration
"timestamp_utc", -- Timestamp at which a measurement was made, in UTC. The formatting is "YYYY-MM-DD HH:MM:SS"
"string_configuration", -- Configuration in which the sensors were deployed. This can be one of six entries: “sub-surface buoy”, “surface buoy”, “attached to gear”, “attached to fixed structure”, “floating dock”, or “unknown”
"qc_flag_sensor_depth_measured_m", -- Quality control flag for measured sensor depth. Maximum flag value from three automated quality control tests: grossrange, spike, and rolling_sd. Flag values can be: "Pass", "Not Evaluated", "Suspect/Of Interest", or "Fail"
"station", -- Name of the location for this deployment
"qc_flag_temperature_degree_c", -- Quality control flag for temperature. Maximum flag value from three automated quality control tests: grossrange, spike, and rolling_sd. Flag values can be: "Pass", "Not Evaluated", "Suspect/Of Interest", or "Fail"
"dissolved_oxygen_uncorrected_mg_per_l", -- Dissolved oxygen measurement, in units of mg/L, without applying a salinity correction factor
"waterbody", -- Waterbody in which the station for this deployment is located
"longitude", -- Longitude of the deployment (decimal degrees)
"deployment_range", -- String describing the instrument deployment and retrieval dates. The format is "YYYY-MMM-DD to YYYY-MMM-DD"
"sensor_serial_number", -- Unique identifying number for the sensor that recorded the measurement
"sensor_type" -- Model of the sensor that recorded the measurement
FROM
"novascotia-ca/inverness-county-water-quality-data-a9za-3t63:latest"."inverness_county_water_quality_data"
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 novascotia-ca/inverness-county-water-quality-data-a9za-3t63 with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.novascotia.ca. When you querynovascotia-ca/inverness-county-water-quality-data-a9za-3t63: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)"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.novascotia.ca, 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 \
"novascotia-ca/inverness-county-water-quality-data-a9za-3t63" \
--handler-options '{
"domain": "data.novascotia.ca",
"tables": {
"inverness_county_water_quality_data": "a9za-3t63"
}
}'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, novascotia-ca/inverness-county-water-quality-data-a9za-3t63 is just another Postgres schema.