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_phytoplankton_grouped_by_size_class table in this repository, by referencing it like:

"kingcounty-gov/marine-phytoplankton-grouped-by-size-class-ap4k-tvru:latest"."marine_phytoplankton_grouped_by_size_class"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "datasource", -- Who the data were analyzed by
    "_10_25um_abundance_particles", -- Abundance of particles 10-25 um 
    "replicates", -- Indicates if there are replicate samples
    "_25_100um_biovolume_mm_3", -- Biovolume of particles 25-100 um 
    "sample_id", -- Unique identifier to link samples collected from the same bottle
    "quality", -- Code indicating overall quality of the data (see DataReadMeFile_WQ for definitions) 
    "_300um_abundance_particles", -- Abundance of particles >300 um
    "_100_300um_biovolume_mm_3", -- Biovolume of particles 100-300 um 
    "_25_100um_abundance_particles", -- Abundance of particles 25-100 um 
    "_100_300um_abundance_particles", -- Abundance of particles 100-300 um 
    "_10_25um_biovolume_mm_3_l", -- Biovolume of particles 10-25 um 
    "total_abundance_particles", -- Total phytoplankton abundance of sample
    "collect_date", -- Date samples were collected
    "replicates_of", -- Indicates the sample number of the replicate
    "grab_id", -- Unique identifier to link samples collected at the same time but run for different program components (e.g., phytoplankton and water quality data collected together)
    "_300um_biovolume_mm_3_l", -- Biovolume of particles >300 um
    "locator", -- Coordinate information available at: https://data.kingcounty.gov/dataset/WLRD-Sites/wbhs-bbzf 
    "sample_number", -- Description of sample collection location Unique identifier applied by the laboratory for samples collected from the same bottle
    "site_name", -- Description of sample collection location
    "depth_m", -- Depth sample was collected (meters)
    "profile_id", -- Unique identifier to link samples collected on the same day, at the same place, but at different depths
    "steward_note", -- Text entered by secondary data reviewers
    "total_biovolume_mm_3_l" -- Total phytoplankton biovolume of sample
FROM
    "kingcounty-gov/marine-phytoplankton-grouped-by-size-class-ap4k-tvru:latest"."marine_phytoplankton_grouped_by_size_class"
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-phytoplankton-grouped-by-size-class-ap4k-tvru 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-phytoplankton-grouped-by-size-class-ap4k-tvru: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-phytoplankton-grouped-by-size-class-ap4k-tvru" \
  --handler-options '{
    "domain": "data.kingcounty.gov",
    "tables": {
        "marine_phytoplankton_grouped_by_size_class": "ap4k-tvru"
    }
}'

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-phytoplankton-grouped-by-size-class-ap4k-tvru is just another Postgres schema.