cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t
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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 hazard_mitigation_plan_mitigation_actions_database table in this repository, by referencing it like:

"cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t:latest"."hazard_mitigation_plan_mitigation_actions_database"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "high_winds", -- Hazard identification for the Mitigation Action
    "prioritization_support", -- Ranking for Prioritization 
    "notes", -- General notes 
    "hazards_addressed", -- Hazard identification for the Mitigation Action
    "web_link", -- Web link for more information 
    "action_category", -- Category identification for the Mitigation Action
    "administrative_technical_capability", -- Identifies administrative and technical capabilities related to action 
    "description_problem", -- Description of the Problem the Mitigation Action addresses
    "mitigation_actions_description", -- Description of Mitigation Action
    "priority", -- Priority Ranking 
    "action_status", -- Status of the Mitigation Action
    "city_funding_source", -- City Funding Sources for the Mitigation Action 
    "related_to_a_critical_facility", -- Identifies if action is related to a critical facility  
    "earthquakes", -- Hazard identification for the Mitigation Action 
    "description_of_climate_change_addressed", -- Description of how climate change is addressed 
    "financial_capability", -- Identifies financial capabilities related to action 
    "education_outreach_capability", -- Identifies education and outreach capabilities related to action 
    "estimated_finish", -- Estimated End Date of the Mitigation Action 
    "contact_name", -- Contact Name for Mitigation Action 
    "contact_email", -- Contact Email for Mitigation Action 
    "lead_agency", -- The lead/managing Agency of the Mitigation Action
    "mitigation_actions_title", -- Brief Title of the Mitigation Action
    "hmp_index", -- Hazard Mitigation Plan Index Unique Identifier
    "flooding", -- Hazard identification for the Mitigation Action 
    "coastal_storms", -- Hazard identification for the Mitigation Action
    "prioritization_planning_and_regulation", -- Ranking for Prioritization 
    "coastal_erosion", -- Hazard identification for the Mitigation Action
    "prioritization_score", -- Sum of the Prioritization values 
    "private_funding_source", -- Private Funding Sources for the Mitigation Action 
    "description_of_critical_facility", -- Description of how action is related to critical facility 
    "drought", -- Hazard identification for the Mitigation Action 
    "prioritization_administrative_and_technical", -- Ranking for Prioritization 
    "disease_outbreak", -- Hazard identification for the Mitigation Action
    "action_status_date", -- Status date of the Mitigation Action
    "support_agency", -- Additional Agencies supporting the Mitigation Action
    "prioritization_financial", -- Ranking for Prioritization 
    "social_vulnerability_addressed", -- Identifies if action addresses social vulnerability  
    "estimated_cost", -- Estimated Cost of the Mitigation Action 
    "climate_change_addressed", -- Identifies if action addresses climate change 
    "state_funding_source", -- State Funding Sources for the Mitigation Action 
    "prioritization_environmental", -- Ranking for Prioritization 
    "description_of_social_vulnerability_addressed", -- Description of how social vulnerability is addressed 
    "federal_funding_source", -- Federal Funding Sources for the Mitigation Action 
    "prioritization_education_and_outreach", -- Ranking for Prioritization 
    "other_funding_source", -- Other Funding Sources for the Mitigation Action 
    "prioritization_social", -- Ranking for Prioritization 
    "estimated_start", -- Estimated Start Date of the Mitigation Action 
    "non_natural", -- Hazard identification for the Mitigation Action 
    "winter_weather", -- Hazard identification for the Mitigation Action 
    "planning_regulation_capability", -- Identifies planning and regulation capabilities related to action 
    "extreme_heat", -- Hazard identification for the Mitigation Action 
    "poor_air_quality" -- Hazard identification for the Mitigation Action 
FROM
    "cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t:latest"."hazard_mitigation_plan_mitigation_actions_database"
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 cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t 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 cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t: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 cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t

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 cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t:latest

This will download all the objects for the latest tag of cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t 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 cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t: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 cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t: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, cityofnewyork-us/hazard-mitigation-plan-mitigation-actions-database-veqt-eu3t is just another Postgres schema.

Related Documentation:

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