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 nyserda_2024_soils_data_for_use_in_the_largescale
table in this repository, by referencing it like:
"ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m:latest"."nyserda_2024_soils_data_for_use_in_the_largescale"
or in a full query, like:
SELECT
":id", -- Socrata column ID
"hay_yield_ton_acre", -- The average management yields of hay
"rotation", -- Number of years of corn (or other row crops) that can be grown in a corn- hay rotation without exceeding the permissible soil loss by erosion without the use of additional practices such as cover crops, no-till practices, etc.
"corn_yield_ton_acre", -- The average management yields of corn
"index_tdn", -- Index value of TDN – (TDN of soil map unit /TDN for best soil ) X 100
"change", -- Change in the information for this soil map unit. These changes may or may not result in a change within the soil group
"flooding", -- Flooding from overflow of a stream or river that results in crop loss
"mapsym", -- Abbreviation for soil unit name
"multiple_msg_flag", -- Indicates whether multiple MSG values exist for a certain soil unit, if applicable
"soil_temp_regime", -- Soil temperature regime as defined in Soil Taxonomy
"modifier", -- Describes an element of the soil unit that may be used for altering the soil group value
"texture", -- General description of the texture of the parent material
"lime", -- Lists if the need for the application of lime is indicated for the soil unit
"tdn_ton_acre", -- Total digestible nutrients - (Years Corn* Yield Corn* 0, 2) + [(10 - years Corn)* Yield Hay* 0.5]
"county", -- Name of county for the soil unit
"county_mapsym", -- Combination of county name and MAPSYM abbreviation; a unique value for each soil unit
"mukey", -- Unique ID for each soil unit used to join to the SSURGO database. Blank cells represent map symbols that are no longer in the SSURGO database
"default_mineral_soil_group", -- Value for the Mineral Soil Group (MSG) for NYSERDA’s Program purposes. Values range from 1 to 10 and defaults to the lowest value (i.e., highest quality soil type)
"flag_msg_values", -- A list of the possible MSG values for a given soil unit, if applicable
"flag_fields", -- If multiple MSG values possible, a list of the fields which differ across the subset of soils
"capability_class_fm5_cap", -- Capability class is the broadest category in the land capability classification system. Class codes 1, 2, 3, 4, 5, 6, 7, and 8 are used to represent both irrigated and non-irrigated land capability classes.
"soil_modifier", -- Describes an element of the soil unit that may be used for altering the soil group value
"soil_slope", -- Range of slope percentage for soil unit
"soil_name", -- Soil unit name
"drainage" -- Identifies the natural drainage conditions of the soil and refers to the frequency and duration of wet periods
FROM
"ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m:latest"."nyserda_2024_soils_data_for_use_in_the_largescale"
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 ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m
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; sgr
can 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 clone
and sgr checkout
.
Cloning Data
Because ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m: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 ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m
Checkout 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 ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m:latest
This will download all the objects for the latest
tag of ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m
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 ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m: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 ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m:latest
This 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, ny-gov/nyserda-2024-soils-data-for-use-in-the-largescale-7xrz-ds9m
is just another Postgres schema.