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 arrests table in this repository, by referencing it like:
"cityofchicago/arrests-dpt3-jri9:latest"."arrests"or in a full query, like:
SELECT
":id", -- Socrata column ID
"arrest_date", -- Date and time of arrest.
"charges_class", -- The classes of the first four charges filed, separated by the | character with a space on each side. Values are always listed in the same order. In other words, the nth value in each list will refer to the same charge. The "Contains" operator can be used in a filter to search for presence of a value in any of the charges.
"charges_type", -- The types of the first four charges filed, separated by the | character with a space on each side. Values are always listed in the same order. In other words, the nth value in each list will refer to the same charge. The "Contains" operator can be used in a filter to search for presence of a value in any of the charges.
"charges_description", -- The descriptions of the first four charges filed, separated by the | character with a space on each side. Values are always listed in the same order. In other words, the nth value in each list will refer to the same charge. The "Contains" operator can be used in a filter to search for presence of a value in any of the charges.
"charges_statute", -- The statutes of the first four charges filed, separated by the | character with a space on each side. Values are always listed in the same order. In other words, the nth value in each list will refer to the same charge. The "Contains" operator can be used in a filter to search for presence of a value in any of the charges.
"charge_4_description", -- Statute description for 4th most serious charge (based on class and type, then arrest report order in case of tie).
"charge_3_statute", -- Statute for 3rd most serious charge (based on class and type, then arrest report order in case of tie).
"charge_1_description", -- Statute description for most serious charge (based on class and type, then arrest report order in case of tie).
"charge_1_statute", -- Statute for most serious charge (based on class and type, then arrest report order in case of tie).
"case_number", -- Records Division Number – uniquely identifies the criminal incident report associated with the arrest . This column, if populated, corresponds to Case Number in https://data.cityofchicago.org/Public-Safety/Crimes-2001-to-present/ijzp-q8t2 and can be used to link the datasets.
"charge_3_class", -- Charge class for 3rd most serious charge (If F then X, 1, 2, 3, or 4; If M then A, B, or C; L = local ordinance violation; P = petty offense; U = business offense; Z = used for warrant arrests, criminal registration violations, and violations of court orders)
"charge_4_class", -- Charge class for 4th most serious charge (If F then X, 1, 2, 3, or 4; If M then A, B, or C; L = local ordinance violation; P = petty offense; U = business offense; Z = used for warrant arrests, criminal registration violations, and violations of court orders)
"charge_3_type", -- Charge type for 3rd most serious charge (F = felony; M = misdemeanor; Null = local ordinance, traffic arrest, other)
"charge_2_description", -- Statute description for 2nd most serious charge (based on class and type, then arrest report order in case of tie).
"charge_2_statute", -- Statute for 2nd most serious charge (based on class and type, then arrest report order in case of tie).
"charge_3_description", -- Statute description for 3rd most serious charge (based on class and type, then arrest report order in case of tie).
"charge_1_class", -- Charge class for most serious charge (If F then X, 1, 2, 3, or 4; If M then A, B, or C; L = local ordinance violation; P = petty offense; U = business offense; Z = used for warrant arrests, criminal registration violations, and violations of court orders)
"cb_no", -- Central Booking Number – uniquely identifies the arrest report
"charge_2_type", -- Charge type for 2nd most serious charge (F = felony; M = misdemeanor; Null = local ordinance, traffic arrest, other)
"charge_4_statute", -- Statute for 4th most serious charge (based on class and type, then arrest report order in case of tie).
"charge_1_type", -- Charge type for most serious charge (F = felony; M = misdemeanor; Null = local ordinance, traffic arrest, other)
"charge_4_type", -- Charge type for 4th most serious charge (F = felony; M = misdemeanor; Null = local ordinance, traffic arrest, other)
"charge_2_class", -- Charge class for 2nd most serious charge (If F then X, 1, 2, 3, or 4; If M then A, B, or C; L = local ordinance violation; P = petty offense; U = business offense; Z = used for warrant arrests, criminal registration violations, and violations of court orders)
"race", -- The race/ethnicity of the person arrested.
":@computed_region_43wa_7qmu",
":@computed_region_bdys_3d7i",
":@computed_region_6mkv_f3dw",
":@computed_region_vrxf_vc4k",
":@computed_region_rpca_8um6"
FROM
"cityofchicago/arrests-dpt3-jri9:latest"."arrests"
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/arrests-dpt3-jri9 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/arrests-dpt3-jri9: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/arrests-dpt3-jri9Checkout 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/arrests-dpt3-jri9:latestThis will download all the objects for the latest tag of cityofchicago/arrests-dpt3-jri9 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/arrests-dpt3-jri9: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/arrests-dpt3-jri9: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/arrests-dpt3-jri9 is just another Postgres schema.