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 emergency_communications_24hour_call_volume table in this repository, by referencing it like:
"norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj:latest"."emergency_communications_24hour_call_volume"or in a full query, like:
SELECT
":id", -- Socrata column ID
"date", -- Date of the emergency communications calls. Each row of data accounts for a 24-hour period occurring during this date.
"total_calls_and_texts", -- The total emergency communications call and texts processed. This represents the total of fields 911 Calls Answered, 911 Text Sessions, Inbound Non-911 Calls, and Outbound Non-911 Calls.
"_911_calls_answered", -- The number of 911 calls answered during the 24-hour period.
"_911_calls_abandoned", -- The number of 911 calls made to the emergency communication center that were dropped or abandoned by the caller prior to a telecommunicator answering. 911 telecommunicators call back these abandoned calls to see if there is an emergency.
"_911_text_sessions", -- The number of 911 text sessions conducted during the 24-hour period.
"average_messages_per_session", -- The average number of text messages per text session.
"average_text_session_duration", -- The average number of seconds that the text session lasts.
"percentage_of_911_calls", -- The percentage of 911 calls during the 24-hour period that were answered in 10 seconds or less.
"percentage_of_911_calls_1", -- The percentage of 911 calls during the 24-hour period that were answered in 15 seconds or less.
"percentage_of_911_calls_2", -- The percentage of 911 calls during the 24-hour period that were answered in 20 seconds or less.
"percentage_of_911_calls_3", -- The percentage of 911 calls during the 24-hour period that were answered in 40 seconds or less.
"average_seconds_to_answer", -- The average number of seconds during the 24-hour period that it took to answer 911 calls.
"inbound_non_911_calls", -- The number of non-911 calls answered during the 24-hour period.
"abandoned_non_911_calls", -- The number of non-911 calls abandoned or dropped by the caller prior to the telecommunicator answering.
"outbound_non_911_calls", -- The number of outbound non-911 calls conducted during the 24-hour period.
"average_call_duration_in", -- The average 911 and non-911 call duration in seconds during the 24-hour period.
"teletypewriter_calls", -- The number of teletypewriter (TTY) calls answered during the 24-hour period.
"average_teletypewriter", -- The average number of TTY messages per call during the 24-hour period.
"average_teletypewriter_call" -- The average number of seconds per TTY call during the 24-hour period.
FROM
"norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj:latest"."emergency_communications_24hour_call_volume"
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 norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj 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 norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj: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 norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2djCheckout 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 norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj:latestThis will download all the objects for the latest tag of norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj 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 norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj: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 norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj: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, norfolk-gov/emergency-communications-24hour-call-volume-nj5u-a2dj is just another Postgres schema.