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 arrest_data_from_2020_to_present table in this repository, by referencing it like:
"lacity/arrest-data-from-2020-to-present-amvf-fr72:latest"."arrest_data_from_2020_to_present"or in a full query, like:
SELECT
":id", -- Socrata column ID
"bkg_loc_cd", -- Code of location where person was booked.
"bkg_location", -- Location person was booked.
"bkg_time", -- In 24 hour military time - Time person was booked at a detention facility.
"bkg_date", -- MM/DD/YYYY - Date person was booked at a detention facility.
"lon", -- Longitude - The location where the crime incident occurred. Actual address is omitted for confidentiality. XY coordinates reflect the nearest 100 block.
"crsst", -- Cross Street of rounded Address.
"location", -- Street address of crime incident rounded to the nearest hundred block to maintain anonymity.
"chrg_desc", -- Defines the Charge provided.
"charge", -- The charge the individual was arrested for.
"chrg_grp_cd", -- Category of arrest charge.
"descent_cd", -- Descent Code: A - Other Asian B - Black C - Chinese D - Cambodian F - Filipino G - Guamanian H - Hispanic/Latin/Mexican I - American Indian/Alaskan Native J - Japanese K - Korean L - Laotian O - Other P - Pacific Islander S - Samoan U - Hawaiian V - Vietnamese W - White X - Unknown Z - Asian Indian
"rd", -- A four-digit code that represents a sub-area within a Geographic Area. All arrest records reference the "RD" that it occurred in for statistical comparisons. Find LAPD Reporting Districts on the LA City GeoHub at http://geohub.lacity.org/datasets/lapd-reporting-districts?geometry=-121.023%2C33.621%2C-115.797%2C34.418
"area_desc", -- The 21 Geographic Areas or Patrol Divisions are also given a name designation that references a landmark or the surrounding community that it is responsible for. For example 77th Street Division is located at the intersection of South Broadway and 77th Street, serving neighborhoods in South Los Angeles.
"time", -- In 24 hour military time.
"arst_date", -- MM/DD/YYYY
"arst_typ_cd", -- A code to indicate the type of charge the individual was arrested for. D - Dependent F - Felony I - Infraction M - Misdemeanor O - Other
"location_1", -- The location where the crime incident occurred. Actual address is omitted for confidentiality. XY coordinates reflect the nearest 100 block.
"lat", -- Latitude - The location where the crime incident occurred. Actual address is omitted for confidentiality. XY coordinates reflect the nearest 100 block.
"dispo_desc", -- Disposition of Arrest.
"grp_description", -- Defines the Charge Group Code provided.
"sex_cd", -- F - Female M - Male
"age", -- Two character numeric..
"area", -- The LAPD has 21 Community Police Stations referred to as Geographic Areas within the department. These Geographic Areas are sequentially numbered from 1-21.
":@computed_region_2dna_qi2s",
":@computed_region_kqwf_mjcx",
":@computed_region_ur2y_g4cx",
":@computed_region_tatf_ua23",
":@computed_region_k96s_3jcv",
":@computed_region_qz3q_ghft",
"report_type", -- BOOKING = Person is booked at a detention facility RFC = Person is cited and Released From Custody (RFC)
"rpt_id" -- ID for the arrest.
FROM
"lacity/arrest-data-from-2020-to-present-amvf-fr72:latest"."arrest_data_from_2020_to_present"
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 lacity/arrest-data-from-2020-to-present-amvf-fr72 with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.lacity.org. When you querylacity/arrest-data-from-2020-to-present-amvf-fr72: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 data.lacity.org, 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 \
"lacity/arrest-data-from-2020-to-present-amvf-fr72" \
--handler-options '{
"domain": "data.lacity.org",
"tables": {
"arrest_data_from_2020_to_present": "amvf-fr72"
}
}'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, lacity/arrest-data-from-2020-to-present-amvf-fr72 is just another Postgres schema.