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 transportation_graffiti table in this repository, by referencing it like:
"citydata-mesaaz-gov/transportation-graffiti-9spb-749m:latest"."transportation_graffiti"or in a full query, like:
SELECT
":id", -- Socrata column ID
"reporting_source", -- The mode used to report graffiti.
"calculated_received_month", -- The month the calculated workday request was received by the city staff.
"lat", -- Latitudinal location of graffiti.
":@computed_region_by5m_u9f6",
":@computed_region_y4ir_tfjh", -- This column was automatically created in order to record in what polygon from the dataset 'Mesa Census Tracts 2' (y4ir-tfjh) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_4svm_3hip", -- This column was automatically created in order to record in what polygon from the dataset 'Mesa Census Tracts' (4svm-3hip) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"nearest_address", -- Recorded address of graffiti.
"year_abated", -- Year the graffiti was abated
"sq_foot_abated", -- Square feet abated.
":@computed_region_5spd_7gy6",
"date_abated", -- Date that graffiti was abated.
"days_to_abatement", -- Count of days between calculated received date and date abated based on next normal workday. Normal workday is generally defined as M-Th excluding holidays.
"month_abated", -- Month the graffiti was abated
":@computed_region_fcpr_wj2n", -- This column was automatically created in order to record in what polygon from the dataset 'Mesa Census Tracts To City Boundary' (fcpr-wj2n) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"day_reported", -- Day of the month the graffiti record was generated.
"id", -- CitySourced unique identifier.
":@computed_region_c83p_wm8i", -- This column was automatically created in order to record in what polygon from the dataset 'Mesa Census Tracts To City Boundary v1.2' (c83p-wm8i) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"year_reported", -- Year the graffiti record was generated.
"calculated_received_year", -- The year the calculated workday request was received by the city staff.
"location", -- Combined Lat/Lon location
":@computed_region_b7fy_h722", -- This column was automatically created in order to record in what polygon from the dataset 'City Boundary' (b7fy-h722) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"calculated_received_date", -- Calculated workday request was received by the city staff. Normal workday is generally defined as M-Th excluding holidays.
"lon", -- Longitudinal location of graffiti.
"date_reported", -- Date that graffiti record was generated.
"day_abated", -- Day of the month the graffiti was abated
":@computed_region_v3p2_n653", -- This column was automatically created in order to record in what polygon from the dataset 'Arizona Postal Code Boundaries v1.0' (v3p2-n653) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_mawd_tskg", -- This column was automatically created in order to record in what polygon from the dataset 'Council Districts' (mawd-tskg) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"month_reported", -- Month the graffiti record was generated.
":@computed_region_p8i4_pq2n", -- This column was automatically created in order to record in what polygon from the dataset 'Mesa Reference City Property' (p8i4-pq2n) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"calculated_received_day" -- The day of the month the calculated workday request was received by the city staff.
FROM
"citydata-mesaaz-gov/transportation-graffiti-9spb-749m:latest"."transportation_graffiti"
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 citydata-mesaaz-gov/transportation-graffiti-9spb-749m with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at citydata.mesaaz.gov. When you querycitydata-mesaaz-gov/transportation-graffiti-9spb-749m: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 citydata.mesaaz.gov, 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 \
"citydata-mesaaz-gov/transportation-graffiti-9spb-749m" \
--handler-options '{
"domain": "citydata.mesaaz.gov",
"tables": {
"transportation_graffiti": "9spb-749m"
}
}'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, citydata-mesaaz-gov/transportation-graffiti-9spb-749m is just another Postgres schema.