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 daily_tasks_park_cleaning_records table in this repository, by referencing it like:
"cityofnewyork-us/daily-tasks-park-cleaning-records-kwte-dppd:latest"."daily_tasks_park_cleaning_records"or in a full query, like:
SELECT
":id", -- Socrata column ID
"sector_name", -- The name of the sector in which the property is located.
"nhours", -- A count of the adjusted number of hours a given task was performed.
"activity", -- The type of activity captured for a record. Cleaning is indicated by the "Work" activity, while other activity codes are used for other actions.
"fixed_post", -- An indicator as to whether or not an entry was made using the "Fixed Post" module of the application.
"napsw", -- A count of the number of staff in the Associate Park Service Worker title on the cleaning crew during the indicated activity.
"nnpw", -- A count of the number of non-Parks employees on the cleaning crew during the indicated activity.
"obj_gisobjid", -- Unique identifier that links the property being serviced to an asset in AMPS.
"sector", -- Unique identification string of the Park Maintenance Sector in which the property is located.
"dumping", -- An indicator as to whether or not dumping was cleaned during a visit.
"fiscal_week", -- The relative week of the fiscal year.
"graffiti", -- An indicator as to whether or not graffiti was cleaned during a visit.
"daily_task_id", -- A unique ID assigned to each Daily Task entry.
"ncrew", -- A count of the total number of workers on the cleaning crew during the indicated activity.
"njtp", -- A count of the number of staff in the Job Training Participant title on the cleaning crew during the indicated activity.
"row_id",
"fiscal_day", -- The relative day of the fiscal year.
"end_time", -- The date and time at indicated which the activity ended.
"medical_waste", -- An indicator as to whether or not medical waste was cleaned during a visit.
"broken_glass", -- An indicator as to whether or not broken glass was cleaned during a visit.
"off_route", -- An indicator as to whether or not a property is included on the selected route.
"route_id", -- Unique identification number for the route as part of which the indicated activity was performed
"ncsa", -- A count of the number of staff in the City Seasonal Aide title on the cleaning crew during the indicated activity.
"ncpw", -- A count of the number of staff in the City Park Worker title on the cleaning crew during the indicated activity.
"fiscal_qtr", -- The fiscal year followed by the fiscal quarter for a given record.
"overlap_flag", -- An indicator as to whether or not the number of hours (nhours) were adjusted for overlapping times and tasks.
"daily_task_activity_id", -- A unique ID assigned to each Daily Task activity entry.
"vehicle_number", -- The vehicle number used for the given date and route.
"signname", -- The name of the entire site as it appears on the signs located on the exterior of the park.
"gispropnum", -- Unique identification number for each park property, identified by borough/county (B = Brooklyn; M = Manhattan; Q = Queens; R = Richmond (Staten Island); X = Bronx) and followed by a number.
"animal_waste", -- An indicator as to whether or not animal waste was cleaned during a visit.
"date_worked", -- The date on which the indicated activity was performed.
"district", -- The name of the Park Maintenance District in which the property is located.
"propid", -- Unique identification number for a property or portion of a property. In some cases – a standalone, smaller park for example – this number will be equivalent to the GIS Property Number. In other cases – a zone, playground or other site within a larger park – an additional designation of letters and/or numbers will be added.
"sector_desc", -- The numbers of the Park Maintenance Districts that comprise the associated Sector
"start_time" -- The date and time at which the indicated activity started.
FROM
"cityofnewyork-us/daily-tasks-park-cleaning-records-kwte-dppd:latest"."daily_tasks_park_cleaning_records"
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/daily-tasks-park-cleaning-records-kwte-dppd 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/daily-tasks-park-cleaning-records-kwte-dppd: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)"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/daily-tasks-park-cleaning-records-kwte-dppd" \
--handler-options '{
"domain": "data.cityofnewyork.us",
"tables": {
"daily_tasks_park_cleaning_records": "kwte-dppd"
}
}'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/daily-tasks-park-cleaning-records-kwte-dppd is just another Postgres schema.