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 marine_benthic_biomass_data table in this repository, by referencing it like:

"kingcounty-gov/marine-benthic-biomass-data-h6jg-f45t:latest"."marine_benthic_biomass_data"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "year", -- Year that sample was collected
    "crustacea_qualifier", -- Qualifier code with additional information about the biomass measurement specific to crustaceans. See above for definitions.
    "crustacea_grams", -- Total wet weight mass (in grams) of all crustaceans
    "annelida_grams", -- Total wet weight mass (in grams) of all annelids
    "notes", -- Additional comments about the sample from taxonomist or data reviewer
    "collection_date", -- Date that the sample was collected. In the format of MM/DD/YYYY
    "misc_grams", -- Total wet weight mass (in grams) of all miscellaneous taxa
    "sample_id", -- Unique sample identifier applied by the King County Environmental Laboratory. Note: A sample ID was not always applied to before 2002.
    "sample_type", -- Indicates if sample was collected as part of a particular project or monitoring event. Some samples were collected near wastewater treatment plant outfalls (“Outfall”), while some are part of routine monitoring events to better understand conditions in the Central Basin as a whole (“Routine”).
    "mollusca_grams", -- Total wet weight mass (in grams) of all molluscs
    "project", -- Project number used by the King County Environmental Lab.
    "approx_depth_m", -- Approximate station depth in meters
    "latitude", -- Latitude of target sample coordinate in decimal degrees
    "site", -- Descriptive location of sample location
    "locator", -- Alphanumeric station identifier
    "sample_rep_id", -- Unique identifier that combines the Locator, Year, and Field Replicate fields to identify a unique sample. Can be used to match biomass measurements to abundance data.
    "longitude", -- Longitude of target sample coordinate in decimal degrees
    "fieldreplicate", -- Grab number of a series of samples collected from the same date and location
    "annelida_qualifier", -- Qualifier code with additional information about the biomass measurement specific to annelids. See above for definitions.
    "mollusca_qualifier", -- Qualifier code with additional information about the biomass measurement specific to molluscs. See above for definitions.
    "misc_qualifier" -- Qualifier code with additional information about the biomass measurement specific to miscellaneous taxa. See above for definitions.
FROM
    "kingcounty-gov/marine-benthic-biomass-data-h6jg-f45t:latest"."marine_benthic_biomass_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 kingcounty-gov/marine-benthic-biomass-data-h6jg-f45t with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.kingcounty.gov. When you querykingcounty-gov/marine-benthic-biomass-data-h6jg-f45t: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.kingcounty.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 \
  "kingcounty-gov/marine-benthic-biomass-data-h6jg-f45t" \
  --handler-options '{
    "domain": "data.kingcounty.gov",
    "tables": {
        "marine_benthic_biomass_data": "h6jg-f45t"
    }
}'

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, kingcounty-gov/marine-benthic-biomass-data-h6jg-f45t is just another Postgres schema.