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 violence_reduction_victim_demographics_aggregated table in this repository, by referencing it like:
"cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742p:latest"."violence_reduction_victim_demographics_aggregated"or in a full query, like:
SELECT
":id", -- Socrata column ID
"juvenile_i", -- Whether the victims were juveniles (under age 18). A blank value means Unknown.
"time_period", -- The time period aggregated.
"time_period_start", -- All victimizations have been aggregated to the quarter level. This time stamp reflects the start of the quarter.
"time_period_end", -- All victimizations have been aggregated to the quarter level. This time stamp reflects the end of the quarter.
"sex", -- The sex of the victims. Victimization demographic data shown here are captured by CPD and limited to information included in the police report, which sometimes is not supported by individual self-identification including for sex/gender. In particular, CPD has historically recorded a victim’s sex rather than gender although has added an additional field for collecting gender as of January 2021.
"domestic_i", -- Indicates whether the aggregated number of victimizations were domestic-related as determined by the initial reporting officer or the investigating detective.
"race", -- The race of the victims. Victimization demographic data shown here are captured by CPD and limited to information included in the police report, which may not often be supported by individual self-identification including for race and ethnicity.
"gunshot_injury_i", -- Indicator field describing whether or not a victim was injured by gunfire. Shooting data is not available before 2010 so all non-homicide victimizations prior to 2010 will be recorded as “UNKNOWN.”
"number_of_victims", -- The number of victims matching the unique combination of all other columns.
"primary_type", -- Text description of the IUCR Code that describes the major crime category for the corresponding victimization it falls into. This column represents only the crime that this specific victim within the incident experienced.
"age" -- The age of the victims grouped by decade.
FROM
"cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742p:latest"."violence_reduction_victim_demographics_aggregated"
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 cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742p 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 cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742p: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 cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742pCheckout 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 cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742p:latestThis will download all the objects for the latest tag of cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742p 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 cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742p: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 cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742p: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, cityofchicago/violence-reduction-victim-demographics-aggregated-gj7a-742p is just another Postgres schema.