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 mobility_management_center_issues table in this repository, by referencing it like:
"datahub-austintexas-gov/mobility-management-center-issues-v7vh-gbi6:latest"."mobility_management_center_issues"or in a full query, like:
SELECT
":id", -- Socrata column ID
"issue_type", -- The type of issue
"beacon_id", -- The asset ID of the school beacon at this issue's location.
"location", -- The geographic location of the issue
"signal_issue", -- The type of signal issue, if the issue relates to a traffic or pedestrian signal
"issue_status_code", -- The issue's status code
"tmc_activity", -- Activities performed in response to the issue
"tmc_issue_id", -- The issue's ID
"request_id", -- The asset ID of the signal request at this issue's location.
"modified_date", -- The date the record was last modified
"atd_location_id", -- The location identifier of the issue, if it is associated with a known asset location
"dms_id", -- The asset ID of the digital message sign at this issue's location.
"issue_location_name", -- The name of the location of the issue
"sr_number", -- The 311 service request number, if the issue was generated from 311
"issue_status_desc", -- The issues status
":@computed_region_rxpj_nzrk", -- This column was automatically created in order to record in what polygon from the dataset 'Zipcodes' (rxpj-nzrk) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_m2th_e4b7", -- This column was automatically created in order to record in what polygon from the dataset 'Community Registry' (m2th-e4b7) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_e9j2_6w3z", -- This column was automatically created in order to record in what polygon from the dataset 'Neighborhood Planning Areas' (e9j2-6w3z) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"created_date", -- The date the record was created
":@computed_region_q9nd_rr82", -- This column was automatically created in order to record in what polygon from the dataset 'BOUNDARIES_single_member_districts' (q9nd-rr82) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_jcrc_4uuy", -- This column was automatically created in order to record in what polygon from the dataset 'Boundaries: Zip Code Tabulation Areas, 2017' (jcrc-4uuy) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_8spj_utxs", -- This column was automatically created in order to record in what polygon from the dataset 'Single Member Council Districts' (8spj-utxs) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"signal_id", -- The asset ID of the traffic signal at this issue's location.
"id", -- The ID of this record in the source database
"source" -- The department or agency that created the issue
FROM
"datahub-austintexas-gov/mobility-management-center-issues-v7vh-gbi6:latest"."mobility_management_center_issues"
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 datahub-austintexas-gov/mobility-management-center-issues-v7vh-gbi6 with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at datahub.austintexas.gov. When you querydatahub-austintexas-gov/mobility-management-center-issues-v7vh-gbi6: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 datahub.austintexas.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 \
"datahub-austintexas-gov/mobility-management-center-issues-v7vh-gbi6" \
--handler-options '{
"domain": "datahub.austintexas.gov",
"tables": {
"mobility_management_center_issues": "v7vh-gbi6"
}
}'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, datahub-austintexas-gov/mobility-management-center-issues-v7vh-gbi6 is just another Postgres schema.