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 budget_planning_position_forecast_gold_copy table in this repository, by referencing it like:
"budget-qa-reporting-data-socrata/budget-planning-position-forecast-gold-copy-yecj-kis8:latest"."budget_planning_position_forecast_gold_copy"or in a full query, like:
SELECT
":id", -- Socrata column ID
"usersegment3segment",
"usersegment3name", -- User Segment3 Name
"usersegment3header", -- Report Header combining Segment value and Name
"organizationsegment", -- Segment Value
"locationname", -- Location Name
"grantsegment", -- Segment Value
"fundingtypesegment", -- Segment Value
"entitysegment", -- Segment Value
"divisionsegment", -- Segment Value
"divisionname", -- Division Name
"proposalname", -- Name of the Proposal
"classificationstatus", -- Classification Status
"isnewposition", -- Is this a New Postion
"isonetimeposition", -- Is this a Onetime Position
"divisionheader", -- Report Header combining Segment value and Name
"documentlink", -- A Hyperlink to the related Proposal
"iscurrentproposal", -- Is this the Most Current Proposal
"proposallinejustification", -- Justification of the line budget amount
"activityname", -- Activity Name
"agencyheader", -- Report Header combining Segment value and Name
"agencyname", -- Agency Name
"agencysegment", -- Segment Value
"categoryheader", -- Report Header combining Segment value and Name
"categoryname", -- Category Name
"categorysegment", -- Segment Value
"costcenterheader", -- Report Header combining Segment value and Name
"costcentername", -- Cost Center Name
"entityname", -- Entity Name
"functionname", -- Function Name
"functionsegment", -- Segment Value
"fundingsourceheader", -- Report Header combining Segment value and Name
"fundingsourcename", -- Funding Source Name
"fundingsourcesegment", -- Segment Value
"fundingtypeheader", -- Report Header combining Segment value and Name
"fundingtypename", -- Funding Type Name
"gradename", -- Grade Name
"gradesegment", -- Segment Value
"grantheader", -- Report Header combining Segment value and Name
"locationheader", -- Report Header combining Segment value and Name
"objectname", -- Object Name
"organizationheader", -- Report Header combining Segment value and Name
"phaseheader", -- Report Header combining Segment value and Name
"phasename", -- Phase Name
"phasesegment", -- Segment Value
"programname", -- Program Name
"projectsegment", -- Segment Value
"unitheader", -- Report Header combining Segment value and Name
"unitname", -- Unit Name
"unitsegment", -- Segment Value
"usersegment1header", -- Report Header combining Segment value and Name
"usersegment1name", -- User Segment1 Name
"usersegment2header", -- Report Header combining Segment value and Name
"usersegment2segment",
"usersegment4header", -- Report Header combining Segment value and Name
"usersegment4name", -- User Segment4 Name
"usersegment4segment",
"usersegment5header", -- Report Header combining Segment value and Name
"usersegment5segment",
"stageduedate", -- The date the stage is due for completion
"jobcode", -- The description of the Job
"accountdescription", -- The text description of the Budget line account
"activityheader", -- Report Header combining Segment value and Name
"activitysegment", -- Segment Value
"costcentersegment", -- Segment Value
"entityheader", -- Report Header combining Segment value and Name
"functionheader", -- Report Header combining Segment value and Name
"fundname", -- Fund Name
"gradeheader", -- Report Header combining Segment value and Name
"grantname", -- Grant Name
"locationsegment", -- Segment Value
"objectheader", -- Report Header combining Segment value and Name
"objectsegment", -- Segment Value
"organizationname", -- Organization Name
"programheader", -- Report Header combining Segment value and Name
"projectname", -- Project Name
"usersegment2name", -- User Segment2 Name
"departmentname", -- Department Name
"departmentsegment", -- Segment Value
"fundheader", -- Report Header combining Segment value and Name
"fundsegment", -- Segment Value
"projectheader", -- Report Header combining Segment value and Name
"usersegment1segment",
"fte", -- Full-time Equivalency
"stagename", -- Budget Plan stage
"departmentheader", -- Report Header combining Segment value and Name
"programsegment", -- Segment Value
"usersegment5name", -- User Segment4 Name
"budgetplanname", -- Budget Plan Name
"jobtitle", -- Classification Status
"lineaccount", -- The full GL Budget account
"lineamount", -- Line Account Amount
"period", -- Budget Plan Period
"positiondescription", -- The description of the Position
"positionnumber", -- Position Number
"proposalowner", -- Owner of the Proposal
"stageseqorder" -- The numeric order of the Stage
FROM
"budget-qa-reporting-data-socrata/budget-planning-position-forecast-gold-copy-yecj-kis8:latest"."budget_planning_position_forecast_gold_copy"
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 budget-qa-reporting-data-socrata/budget-planning-position-forecast-gold-copy-yecj-kis8 with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at budget-qa-reporting.data.socrata.com. When you querybudget-qa-reporting-data-socrata/budget-planning-position-forecast-gold-copy-yecj-kis8: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 budget-qa-reporting.data.socrata.com, 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 \
"budget-qa-reporting-data-socrata/budget-planning-position-forecast-gold-copy-yecj-kis8" \
--handler-options '{
"domain": "budget-qa-reporting.data.socrata.com",
"tables": {
"budget_planning_position_forecast_gold_copy": "yecj-kis8"
}
}'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, budget-qa-reporting-data-socrata/budget-planning-position-forecast-gold-copy-yecj-kis8 is just another Postgres schema.