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 calls_for_service_2017 table in this repository, by referencing it like:
"nola-gov/calls-for-service-2017-bqmt-f3jk:latest"."calls_for_service_2017"or in a full query, like:
SELECT
":id", -- Socrata column ID
"block_address", -- The BLOCK unique address number for the incident. The block address has been obscured to protect the sensitivity of the data.
"location_city",
"location_address",
"location_state",
"location_zip",
"policedistrict", -- The NOPD PoliceDistrict associated with the call for service.
"selfinitiated", -- The NOPD SelfInitiated associated with the call for service. A call is considered self-initiated if the Officer generates the item in the field as opposed to responding to a 911 call.
"initialpriority", -- The NOPD InitialPriority associated with the call for service. See Priority description for more information.
"dispositiontext", -- The NOPD DispositionText associated with the call for service.
"disposition", -- The NOPD Disposition associated with the call for service.
"initialtype", -- The NOPD InitialType associated with the call for service.
"mapy", -- The NOPD MapY associated with the call for service. This is provided in state plane and obscured to protect the sensitivity of the data.
"zip", -- The NOPD Zip associated with the call for service.
"location", -- The NOPD Location associated with the call for service. The X,Y coordinates for the call for service obscured to protect the sensitivity of the data.
"beat", -- The NOPD Beat associated with the call for service. This is the area within Orleans Parish that the call for service occurred. The first number is the NOPD District, the letter is the zone, and the numbers are the subzone.
"timeclosed", -- The NOPD TimeClosed associated with the call for service. This is the time stamp of the time the call was closed in the CAD system.
"timedispatch", -- The NOPD TimeDispatch associated with the call for service. This is the entered time by OPCD or NOPD when an officer was dispatched.
"timecreate", -- The NOPD TimeCreate associated with the call for service. This is the time stamp of the create time of the incident in the CAD system.
"initialtypetext", -- The NOPD InitialTypeText associated with the call for service.
"priority", -- The NOPD Priority associated with the call for service. Code 3 is considered the highest priority and is reserved for officer needs assistance. Code 2 are considered "emergency" calls for service. Code 1 are considered "non-emergency" calls for service. Code 0 calls do not require a police presence. Priorities are differentiated further using the letter designation with "A" being the highest priority within that level.
"typetext", -- The NOPD TypeText associated with the call for service.
"nopd_item", -- The NOPD unique item number for the incident.
"timearrive", -- The NOPD TimeArrive associated with the call for service. This is the entered time by OPCD or NOPD when an officer arrived.
"mapx", -- The NOPD MapX associated with the call for service. This is provided in state plane and obscured to protect the sensitivity of the data.
"type_", -- The NOPD Type associated with the call for service.
":@computed_region_spev_d8jm",
":@computed_region_ewbu_t8bu",
":@computed_region_m56f_hbma",
":@computed_region_evki_aju8",
":@computed_region_7fw3_kdpf",
":@computed_region_u4yh_3wk9",
":@computed_region_k37d_then",
":@computed_region_sikx_bdeb"
FROM
"nola-gov/calls-for-service-2017-bqmt-f3jk:latest"."calls_for_service_2017"
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 nola-gov/calls-for-service-2017-bqmt-f3jk 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 nola-gov/calls-for-service-2017-bqmt-f3jk: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 nola-gov/calls-for-service-2017-bqmt-f3jkCheckout 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 nola-gov/calls-for-service-2017-bqmt-f3jk:latestThis will download all the objects for the latest tag of nola-gov/calls-for-service-2017-bqmt-f3jk 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 nola-gov/calls-for-service-2017-bqmt-f3jk: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 nola-gov/calls-for-service-2017-bqmt-f3jk: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, nola-gov/calls-for-service-2017-bqmt-f3jk is just another Postgres schema.