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 mdot_plant_manual_for_slope_planting table in this repository, by referencing it like:
"michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5:latest"."mdot_plant_manual_for_slope_planting"or in a full query, like:
SELECT
":id", -- Socrata column ID
"notes",
"clear_vision", -- If the plant height is under 30”.
"cultivar_notes", -- Special features of a particular cultivar.
"various_cultivars_avail", -- If there are various cultivars available for this species.
"us_native", -- If the plant is native to the United States.
"mi_native", -- If the plant is native to Michigan.
"usda_hardiness_zone_max", -- USDA Plant Hardiness Zone is the standard by which plants are likely to thrive at a specific location.
"usda_hardiness_zone_min", -- USDA Plant Hardiness Zone is the standard by which plants are likely to thrive at a specific location.
"evergreen_deciduous", -- If the plant sheds foliage in the fall or retains foliage year-round. Applies to trees/shrubs only.
"prevents_erosion", -- If the plant prevents erosion.
"drought_tolerant", -- If the plant can tolerant drought.
"dry_soils", -- If the plant can grow thrive in dry soil.
"wet_soils", -- If the plant can grow thrive in wet soil.
"clay_soils", -- If the plant can grow thrive in clay soil.
"sandy_soils", -- If the plant can grow thrive in sandy soil.
"bloom_time", -- Bloom time for flowering plant.
"spread_max_in", -- Average spread (width) of the mature plant.
"spread_min_in", -- Average spread (width) of the mature plant.
"spread_max_ft", -- Average spread (width) of the mature plant.
"spread_min_ft", -- Average spread (width) of the mature plant.
"height_max_in", -- Average height of the mature plant.
"height_min_in", -- Average height of the mature plant.
"height_max_ft", -- Average height of the mature plant.
"height_min_ft", -- Average height of the mature plant.
"light", -- How much sun the plant needs to thrive.
"common_name", -- The name of the plant in common usage.
"cultivar", -- Cultivar used in the project.
"species", -- Species of the plant, 2nd part of the scientific name.
"genus", -- Genus of the plant, 1st part of the scientific name.
"category", -- Type of plant.
"habit", -- General appearance and growth form.
"pay_item_code", -- MDOT pay item code for the plant.
"msu_proven", -- The plants studied in the Slope Restoration on Urban Freeways research.
"wetland_w", -- If the plant can grow thrive in wetland conditions.
"upland_u" -- If the plant can grow thrive in upland conditions.
FROM
"michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5:latest"."mdot_plant_manual_for_slope_planting"
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 michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5 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 michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5: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 michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5Checkout 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 michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5:latestThis will download all the objects for the latest tag of michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5 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 michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5: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 michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5: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, michigan-gov/mdot-plant-manual-for-slope-planting-epxx-s8r5 is just another Postgres schema.