texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk
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Query the Data Delivery Network

Query the DDN

The 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 texas_commission_on_environmental_quality_notices table in this repository, by referencing it like:

"texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk:latest"."texas_commission_on_environmental_quality_notices"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "b_viol_citations", -- Violation Citations for Category B violations.
    "lat_dec_coord_num", -- Latitude coordinates, as provided
    "invstn_no", -- Unique number assigned to each investigation
    "usps_state_cd", -- State associated to the mailing address
    "region", -- TCEQ region number and regional office location
    "media_cd", -- TCEQ organizational unit divided between Air, Waste, and Water
    "zip4_cd", -- Zip code extension associated to the mailing address of the Regulated Entity.
    "viol_cnt", -- Total number of violations associated with the NOE.
    "noe_id", -- Unique identifier associated with the NOE.
    "c_viol_citations", -- Violation Citations for Category C violations.
    "tnrcc_dkt_num_txt", -- Docket number and creation date associated with the NOE. Note multiple numbers and docket creation dates can be listed here.
    "rn", -- Unique number assigned to the Regulated Entity
    "deliv_txt", -- Mailing address for the Regulated Entity, as available
    "reg_ent_desc_txt", -- The desription of the primary business function that this Regualted Entity is performing
    "loc_zip_txt", -- Zip Code associated to the physical location
    "reg_ent_name", -- Name of the entity located at the specific site
    "c_viol_track_num", -- Violation Tracking Numbers for Category C violations.
    "city_name", -- City associated to the mailing address
    "zip_cd", -- Zip Code associated to the mailing address
    "phys_loc_desc_txt", -- Physical description or address for the Regulated Entity, as available
    "near_city_name", -- City associated to the physical location
    "loc_cnty_name", -- County associated to the physical location
    "long_dec_coord_num", -- Longitude coordinates, as provided
    "noe_dt", -- Date a Notice of Enforcement (NOE) letter was transmitted to the Regulated Entity
    "a_viol_track_num", -- Violation Tracking Numbers for Category A violations.
    "a_viol_citations", -- Violation Citations for Category A violations.
    "b_viol_track_num" -- Violation Tracking Numbers for Category B violations.
FROM
    "texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk:latest"."texas_commission_on_environmental_quality_notices"
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 texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk with SQL in under 60 seconds.

Query Your Local Engine

Install Splitgraph Locally
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 texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk: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 texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk

Checkout 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 texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk:latest

This will download all the objects for the latest tag of texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk 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 texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk: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 texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk:latest

This 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, texas-gov/texas-commission-on-environmental-quality-notices-rua3-iswk is just another Postgres schema.

Related Documentation:

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