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 micromarket_recovery_program_addresses table in this repository, by referencing it like:

"cityofchicago/micromarket-recovery-program-addresses-cf2f-mmzv:latest"."micromarket_recovery_program_addresses"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "address_grouping_key", -- Address Group Unique Key (use this column to link Violations, Permits and Cases to MMRP Geographies data set - ADDRGRPKEY).  An Address Group is a grouping of point addresses (ADDRKEY's) at the same property; example: the Daley Center is located on 4 bounding streets (Washington, Dearborn, Randolph and Clark) and each street has many point addresses for the Daley Center.  All point addresses on all four bounding streets are grouped using the same ADDRGRPKEY.  This field allows for ALL activity at a building to be grouped into one dataset.
    ":@computed_region_awaf_s7ux",
    ":@computed_region_6mkv_f3dw",
    ":@computed_region_43wa_7qmu",
    "suffix", -- Address Suffix
    "location_address",
    "location_zip",
    "location_state",
    "location_city",
    "fire_district", -- Geography - Fire District
    "pre_direction", -- Address Pre-Direction
    "location", -- Geocoded Location based on Latitude/Longitude
    "ward", -- Geography - Ward
    "longitude", -- Longitude
    "address_key", -- Address Unique Key (use this column to link Violations, Permits and Cases to MMRP Geographies data set - ADDRKEY)
    "x_coord", -- X Coord - State Plane Eastern IL 1983
    "mmrp_zone", -- Name of MMRP Zone
    "post_direction", -- Address Post Direction
    "central_business_district", -- Central Business District as described by Ordinance - "Central Business District" means the district consisting of those streets or parts of streets within the area bounded by a line as follows: beginning at the easternmost point of Division Street extended to Lake Michigan; then west on Division Street to LaSalle Street; then south on LaSalle Street to Chicago Avenue; then west on Chicago Avenue to Halsted Street; then south on Halsted Street to Roosevelt Road; then east on Roosevelt Road to its easternmost point extended to Lake Michigan; including parking spaces on both sides of the above-mentioned streets.
    "street_name", -- Address Street Name
    "latitude", -- Latitude
    "y_coord", -- Y Coord - State Plane Eastern IL 1983
    "tif_zone", -- Geography - TIF Zone
    "census_tract", -- Geography - Census Tract
    "police_district", -- Geography - Police District
    "street_number", -- Address Street Number
    "zip_code", -- Address Zip Code
    ":@computed_region_vrxf_vc4k",
    ":@computed_region_bdys_3d7i",
    "community_area" -- Geography - Community Area
FROM
    "cityofchicago/micromarket-recovery-program-addresses-cf2f-mmzv:latest"."micromarket_recovery_program_addresses"
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 cityofchicago/micromarket-recovery-program-addresses-cf2f-mmzv with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.cityofchicago.org. When you querycityofchicago/micromarket-recovery-program-addresses-cf2f-mmzv: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.cityofchicago.org, 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 \
  "cityofchicago/micromarket-recovery-program-addresses-cf2f-mmzv" \
  --handler-options '{
    "domain": "data.cityofchicago.org",
    "tables": {
        "micromarket_recovery_program_addresses": "cf2f-mmzv"
    }
}'

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, cityofchicago/micromarket-recovery-program-addresses-cf2f-mmzv is just another Postgres schema.