cityofnewyork-us/1995-street-tree-census-kyad-zm4j
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Query the Data Delivery Network

Query the DDN

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 1995_street_tree_census table in this repository, by referencing it like:

"cityofnewyork-us/1995-street-tree-census-kyad-zm4j:latest"."1995_street_tree_census"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    ":@computed_region_efsh_h5xi",
    "bbl",
    "bin",
    "council_district",
    "spc_latin", -- This is the latin/scientific name for the species of this tree. 
    "spc_common", -- This is the common name for the species of this tree. 
    "censusblock_2010", -- 2010 Census Block geocoded to the address using Geosupport 11.4 
    "censustract_2010", -- 2010 Census Tract geocoded to the address using Geosupport 11.4 
    "zip_new", -- Zip Code geocoded to the address using Geosupport 11.4 
    "cb_new", -- Community Board geocoded to the address using Geosupport 11.4 
    "latitude", -- Latitude of point in decimal degrees as geocoded using LION 02A 
    "longitude", -- Longitude of point in decimal degrees as geocoded using LION 02A 
    "y", -- Y coordinate of point in the NAD_1983_StatePlane_New_York_Long_Island_FIPS_3104_Feet coordinate system, geocoded using LION 02A 
    "x", -- X coordinate of point in the NAD_1983_StatePlane_New_York_Long_Island_FIPS_3104_Feet coordinate system, geocoded using LION 02A 
    "species", -- Species of the tree using a four-letter code, comprised of the first two letters of the genus followed by the first two letters of the species. 
    "site", -- This field clarifies the position relative to the address for trees not located in the front of buildings.   
    "cb_original", -- The community board originally geocoded to the address using LION 02A 
    "zip_original", -- The zip code originally geocoded to the address using LION 02A 
    "street", -- Street where address for tree is located. 
    "house_number", -- Numerical portion of the address. 
    "address", -- Address of the tree. 
    "segmentid", -- LION SegmentID geocoded to the address using Geosupport 11.4 
    "diameter", -- Diameter of the tree as measured at approximately 4.5 feet from the ground. 
    "recordid", -- A unique identifier for each record in the table.  Does not correspond to other datasets or identify the tree itself. 
    "nta_2010", -- Neighborhood Tabulation Area geocoded to the address using Geosupport 11.4 
    "borough", -- Borough where tree was recorded. 
    "sidewalk_condition", -- Whether the tree roots have lifted the adjacent sidewalk. 
    "location_zip",
    "location_address",
    "location_state",
    ":@computed_region_yeji_bk3q",
    ":@computed_region_f5dn_yrer",
    ":@computed_region_92fq_4b7q",
    ":@computed_region_sbqj_enih",
    "location_city",
    "condition", -- Overall tree condition. 
    "wires", -- Whether the tree is located under utility wires 
    "support_structure", -- Whether the tree has support structures installed. 
    "location"
FROM
    "cityofnewyork-us/1995-street-tree-census-kyad-zm4j:latest"."1995_street_tree_census"
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 cityofnewyork-us/1995-street-tree-census-kyad-zm4j with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.cityofnewyork.us. When you querycityofnewyork-us/1995-street-tree-census-kyad-zm4j: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

Install Splitgraph Locally
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 (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.cityofnewyork.us, 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 \
  "cityofnewyork-us/1995-street-tree-census-kyad-zm4j" \
  --handler-options '{
    "domain": "data.cityofnewyork.us",
    "tables": {
        "1995_street_tree_census": "kyad-zm4j"
    }
}'

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, cityofnewyork-us/1995-street-tree-census-kyad-zm4j is just another Postgres schema.