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 micromarket_recovery_program_violations_and table in this repository, by referencing it like:
"cityofchicago/micromarket-recovery-program-violations-and-ujwc-724r:latest"."micromarket_recovery_program_violations_and"or in a full query, like:
SELECT
":id", -- Socrata column ID
"zip_code", -- Address Zip Code
"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.
"pre_direction", -- Address Pre-Direction
"mmrp_zone", -- Name of MMRP Zone
"violation_code_book_text", -- Predefined Violation Code Book Text/Ordinance Text
"violation_additional_comments2", -- Violation Inspector Additional Comments2
"violation_additional_comments", -- Violation Inspector Additional Comments
"partial_inspection", -- Partial Inspection Y/N
":@computed_region_43wa_7qmu",
":@computed_region_bdys_3d7i",
":@computed_region_vrxf_vc4k",
":@computed_region_6mkv_f3dw",
":@computed_region_awaf_s7ux",
"inspection_waived", -- Inspection Waived Y/N
"inspected_by", -- Inspector ID who performed the on-site Inspection
"inspection_number", -- Inspection Number
"street_name", -- Address Street Name
"ward", -- Geography - Ward
"latitude", -- Latitude
"location_state",
"location_address",
"violation_status", -- Violation Status - null value = Uncomplied/Open Violation
"violation_sequence_number", -- Sequence of Violations on an Inspection - Order Violations Written
"suffix", -- Address Suffix
"address_key", -- Address Unique Key (use this column to link violations and inspections to MMRP Geographies data set - ADDRKEY)
"template_type", -- Template Type: BLDG = Permits; CASE = Case
"inspection_status", -- Status of Case - CANCELED; CLOSED; FAILED; HOLD; PASSED
"longitude", -- Longitude
"location_city",
"inspection_type", -- Type of Inspection
"violation_code", -- Predefined Violation Code
"street_number", -- Address Street Number
"inspection_waived_date_and_time", -- Inspection Waived Date and Time
"post_direction", -- Address Post Direction
"modified_date_time", -- Date and Time stamp when record was last updated in the database
"trip_number", -- Trip Number is the inspection number in the series of inspections at the same property (aka Reinspections)
"community_area", -- Geography - Community Area
"violation_primary_key", -- Violation Primary Key
"violation_description", -- Predefined Description of Violation Code
"y_coord", -- Y Coord - State Plane Eastern IL 1983
"location", -- Geocoded Location based on Latitude/Longitude
"permit_or_case_type", -- Associated Permit or Case Type (Violations must be linked to an Inspection; Inspections must be linked to a Case or Permit)
"permit_or_case_description", -- Associated Permit or Case Description
"permit_or_case_primary_key", -- Permit or Case Primary Key (use this key to link violations and inspections with Permit APKEY_PERMIT and Case APKEY_CASE datasets)
"inspection_completed_date_and_time", -- Inspection Completed Date and Time
"violation_complied_date", -- Violation Complied Date - null value = Uncomplied/Open Violation
"violation_comments", -- Violation Inspector Comments
"violation_location", -- Location of Violation at Property
"violation_date", -- Violation Written Date
"x_coord", -- X Coord - State Plane Eastern IL 1983
"address_grouping_key", -- Address Group Unique Key (use this column to link violations and inspections 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.
"location_zip"
FROM
"cityofchicago/micromarket-recovery-program-violations-and-ujwc-724r:latest"."micromarket_recovery_program_violations_and"
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-violations-and-ujwc-724r 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 cityofchicago/micromarket-recovery-program-violations-and-ujwc-724r: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 cityofchicago/micromarket-recovery-program-violations-and-ujwc-724rCheckout 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 cityofchicago/micromarket-recovery-program-violations-and-ujwc-724r:latestThis will download all the objects for the latest tag of cityofchicago/micromarket-recovery-program-violations-and-ujwc-724r 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 cityofchicago/micromarket-recovery-program-violations-and-ujwc-724r: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 cityofchicago/micromarket-recovery-program-violations-and-ujwc-724r: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, cityofchicago/micromarket-recovery-program-violations-and-ujwc-724r is just another Postgres schema.