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 street_trees table in this repository, by referencing it like:
"cambridgema-gov/street-trees-82zb-7qc9:latest"."street_trees"or in a full query, like:
SELECT
":id", -- Socrata column ID
"plantingse",
"cartegra_1",
"removaldat", -- Date that a tree was last removed from this site.
"plantdate", -- Date that a tree was last planted at this site.
"treewellde",
"location", -- Designates whether the site is located along a street (Street Tree), beyond the back edge of a sidewalk in a front yard or other area not immediately adjacent to a street (Back of Sidewalk), in a park or other open space (Park Tree, Cemetery Tree, Golf Course), or on the grounds of a public school or other municipal building (Public School, City Building).
"pb",
"bareroot", -- Designates whether the last tree was planted as a bare-root tree.
"the_geom", -- Geospatial layer geometry. The latitude and longitude data for the underlying map shapes.
"treewellwi",
"treewellle",
"siteretire",
"inspectr",
"genus",
"commonname",
"diameter", -- Tree diameter in inches taken at approximately 4.5 feet above ground (DBH). If the diameter point falls on a swelling in the trunk it is customary to measure below the swelling at the point where the diameter is smallest. Note: an average diameter should be calculated for trees with multiple trunks (see the Trunks field); an online calculator for multi-stemmed trees may be found at https://www.treetec.net.au/TPZ_SRZ_DBH_calculator.php.
"streetnumb", -- Number of the street address closest to the site.
"speciessho", -- Genus of the current tree species (see Species).
"species", -- Common name of the species of the current tree.
"treewellid",
"sttreeprun",
"removalrea",
"notes",
"wateringre",
"order_",
"creator",
"scientific",
"trunks", -- Number of tree trunks (see note at Diameter about using the number of trunks to calculate an average tree diameter).
"scheduledr",
"solarratin", -- Solar radiation rating between 1 and 5, where 1 is the lowest score and 5 is the highest (receives the most light). Pictometry 2014 DSM and DEM were used to determine tree height and measure shadows from 2014 3D buildings. SolarRating is the average of the solar radiation for both the DSM and DEM results for June, July, August, and September.
"biochar_ad",
"sitereplan",
"locationre",
"plantingco",
"cartegraph",
"exposedroo", -- Indicates if the root flare of the tree is visible.
"structural", -- Indicates if the tree was planted in structural soil.
"treewellco", -- The type of cover, if any that is over the tree well. The two values are Tree Grate or Flexi-Pave.
"treegratea", -- This field is used to record if the metal tree grate surrounding the tree needs to be reset or removed. When the tree grows, it can get girdled by the tree grate.
"adacomplia", -- Designates whether the site is ADA compliant, for instance whether the site has the minimum required sidewalk width of 4 feet.
"ownership", -- Designates the ownership of the tax parcel on which the site falls.
"memtree", -- Designates whether the current tree was planted in memoriam.
"streetname", -- Name of the street for the address closest to the site.
"cultivar", -- Cultivated variety of the current tree species (see Species).
"overheadwi", -- Designates the presence of above-ground utility wires in the area of tree canopy growth at the site.
"sitetype", -- Designates whether the site is currently occupied by a tree (Tree) or stump (Stump), is an empty planting site (Planting Site), or has been paved over or is otherwise empty and no longer available for planting (Retired). Note: this field typically supersedes any conflicting data within the record; for example, a record designated as a “Planting Site” would indicate that any values for Diameter and Trunks were no longer valid.
"treeid",
"offsttreep",
"abutsopena", -- Indicates if the tree abuts an open space or if the tree well is the only open area around the tree.
":@computed_region_e4yd_rwk4", -- This column was automatically created in order to record in what polygon from the dataset 'Census Blocks 2010' (e4yd-rwk4) the point in column 'the_geom' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_swkg_bavi", -- This column was automatically created in order to record in what polygon from the dataset 'cambridge_cdd_zoning' (swkg-bavi) the point in column 'the_geom' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_rffn_qbt6", -- This column was automatically created in order to record in what polygon from the dataset 'cambridge_neighborhoods' (rffn-qbt6) the point in column 'the_geom' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_v7jj_366k", -- This column was automatically created in order to record in what polygon from the dataset 'Police Response Districts' (v7jj-366k) the point in column 'the_geom' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_guic_hr4a" -- This column was automatically created in order to record in what polygon from the dataset 'Police Neighborhood Regions' (guic-hr4a) the point in column 'the_geom' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
FROM
"cambridgema-gov/street-trees-82zb-7qc9:latest"."street_trees"
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 cambridgema-gov/street-trees-82zb-7qc9 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 cambridgema-gov/street-trees-82zb-7qc9: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 cambridgema-gov/street-trees-82zb-7qc9Checkout 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 cambridgema-gov/street-trees-82zb-7qc9:latestThis will download all the objects for the latest tag of cambridgema-gov/street-trees-82zb-7qc9 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 cambridgema-gov/street-trees-82zb-7qc9: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 cambridgema-gov/street-trees-82zb-7qc9: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, cambridgema-gov/street-trees-82zb-7qc9 is just another Postgres schema.