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 citizen_connect_open_public_works_service_requests table in this repository, by referencing it like:
"memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zqu:latest"."citizen_connect_open_public_works_service_requests"or in a full query, like:
SELECT
":id", -- Socrata column ID
"created_by_user", -- User who created service request
"incident_id", -- Unique incident ID
":@computed_region_gxae_hf64",
":@computed_region_stch_rtry",
":@computed_region_qnac_u4vd",
":@computed_region_dgrd_cuuf",
":@computed_region_m99d_em2n",
":@computed_region_nyzj_ikpv",
":@computed_region_fuzm_ngj2", -- This column was automatically created in order to record in what polygon from the dataset 'Council District Boundaries Dec 2022' (fuzm-ngj2) the point in column 'location_1' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_scpn_qt9a", -- This column was automatically created in order to record in what polygon from the dataset 'Council Super District Boundaries Dec 2022' (scpn-qt9a) the point in column 'location_1' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_y9za_kydd", -- This column was automatically created in order to record in what polygon from the dataset 'Memphis Police Department Stations' (y9za-kydd) the point in column 'location_1' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"created_by", -- -
"request_priority", -- Request priority: High, Medium, or Low
"request_status", -- Request status (this dataset includes service requests NOT marked as closed or resolved: Open, In Progress, Pending Litigation, etc.)
"zone", -- Zone
"sr_creation_channel", -- Service request creation channel (phone or web)
"swm_code", -- Solid Waste Management code (if applicable)
"collection_day", -- Scheduled collection day
"followup_date", -- Followup date
"last_update_date", -- Date service request was last updated (auto-generated)
"owner_name",
"location_1", -- Address
"last_update_login",
"state", -- State (TN)
"area", -- Service request area code
"department", -- City department responsible for service request (within Division)
"summary", -- Description of service request/issue
"street_name", -- Service request street name
"resolution_code_meaning", -- Resolution code meaning
"resolution_code", -- Code indicating how the incident was resolved and/or actions taken to address the service request
"request_type", -- Request type (acronyms correspond to department: SWM = Solid Waste Management, EMI = Environmental Maintenance, CE = Code Enforcement, etc.)
"reported_date", -- User-submitted service request report date
"postal_code", -- Zip code
"parcel_id",
"number_of_tasks",
"location_1_address", -- Location
"map_page",
"last_modified_date", -- Date service request was last modified
"incident_type_id", -- Incident type ID
"creation_date", -- Auto-generated date service request was created & entered in database (may be after REPORTED_DATE)
"close_date", -- Date service request status was changed to "Closed"
"address3", -- Service request address3
"address2", -- Service request address2
"address1", -- Service request address
"next_open_task_date", -- Next open task date
"incident_resolved_date", -- Date incident status was changed to "Resolved"
"group_name", -- Group responsible for service request (similar to Division/Department)
"city", -- City (Memphis)
"ce_category", -- Code enforcement incident category
"category", -- Incident category
"sub_district", -- Council sub-district in which service request was reported
"resolution_summary", -- Summary of incident resolution/actions taken
"division", -- City division responsible for service request
"last_updated_by", -- Person who last updated
":@computed_region_me95_vbw4",
":@computed_region_xf2b_u4zq",
"incident_number", -- Unique incident number
"district", -- Council district in which the service request was reported
"target_block" -- Target block
FROM
"memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zqu:latest"."citizen_connect_open_public_works_service_requests"
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 memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zqu 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 memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zqu: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 memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zquCheckout 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 memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zqu:latestThis will download all the objects for the latest tag of memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zqu 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 memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zqu: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 memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zqu: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, memphistn-gov/citizen-connect-open-public-works-service-requests-aiee-9zqu is just another Postgres schema.