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 hhs_covid19_monthly_outcome_survey_wave_07 table in this repository, by referencing it like:
"datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxb:latest"."hhs_covid19_monthly_outcome_survey_wave_07"or in a full query, like:
SELECT
":id", -- Socrata column ID
"cv3_4_senses", -- CV3_4_Senses: Decreased sense of smell and taste
"cv3_5_flu", -- CV3_5_Flu: Flu symptoms
"cv14_2", -- CV14_2: Wore a mask
"cv14_5", -- CV14_5: None of the above
"cv5_6_chat", -- CV5_6_Chat: Consulted with healthcare provider using chat, text, or email
"public_id", -- public_id: Unique Identifier
"cam5a_vacclike", -- CAM5a_VaccLike: Vaccine Likelihood
"cam7_vaccbel_1", -- CAM7_VaccBel_1: COVID vaccine likelihood
"cam7_vaccbel_3", -- CAM7_VaccBel_3: Immunity from exposure
"cv2_1_fever", -- CV2_1_Fever: Fever
"cv2_5_flu", -- CV2_5_Flu: Flu symptoms
"cv3_1_fever", -- CV3_1_Fever: Fever
"cv3_2_cough", -- CV3_2_Cough: Dry cough
"cv3_3_breath", -- CV3_3_Breath: Shortness of breath
"cv4_1_self", -- CV4_1_Self: Self COVID diagnosis
"cv4_2_family", -- CV4_2_Family: Family COVID diagnosis
"cv4_3_no", -- CV4_3_No: No COVID diagnosis
"cv5_5_video", -- CV5_5_Video: Consulted with healthcare provider using video chat
"cv6b", -- CV6b: Employment status changed since COVID pandemic
"cv6c_rec", -- CV6c_Rec: Current employment status
"cv7b", -- CV7b: Healthcare worker
"cv8c", -- CV8c: Current insurance coverage
"cv9_3_cares", -- CV9_3_CARES: CARES Act check
"cv10_2_home_schooled", -- CV10_2_Home_schooled: home schooled children
"cv11_1_nervous", -- CV11_1_Nervous: Household nervous, anxious, on edge
"cv13", -- CV13: Time spent at home
"cv12_1_nervous", -- CV12_1_Nervous: Self nervous, anxious, on edge
"income", -- income: Income
"cam7_vaccbel_5", -- CAM7_VaccBel_5: Worried side effects
"cv6a_rec", -- CV6a_Rec: Employment status prior to COVID pandemic
"cam7_vaccbel_6", -- CAM7_VaccBel_6: Worse side effects
"cv5_3_doctor", -- CV5_3_Doctor: Visited doctor's office
"cv8a", -- CV8a: Insurance coverage prior to COVID pandemic
"cv11_3_depressed", -- CV11_3_Depressed: Household feeling down, depressed, or hopeless
"cam5_vaccuptake", -- CAM5_VaccUptake: Vaccine Uptake
"cv5_1_hospital", -- CV5_1_Hospital: Hospital or emergency room
"cv12_2_worrying", -- CV12_2_Worrying: Self not able to stop worrying
"cam7_vaccbel_2", -- CAM7_VaccBel_2: Worried COVID from vaccine
"agecat", -- agecat: Age category
"cv9_2_covid_enhanced", -- CV9_2_COVID_enhanced: COVID related enhanced unemployment benefits
"cv2_3_breath", -- CV2_3_Breath: Shortness of breath
"cv1", -- CV1: Physical health
"cv5_7_none", -- CV5_7_None: None of the above
"cv15", -- CV15: Wash hands yesterday
"cv10_3_work_from_home", -- CV10_3_Work_from_home: worked from home more than before the pandemic
"cv2_2_cough", -- CV2_2_Cough: Dry cough
"cam6_vaccwait", -- CAM6_VaccWait: Wait to get vaccinated
"cv8b", -- CV8b: Insurance changed since COVID pandemic
"cv11_2_worrying", -- CV11_2_Worrying: Household not able to stop worrying
"cv12_3_depressed", -- CV12_3_Depressed: Self feeling down, depressed, or hopeless
"cv14_1", -- CV14_1: Kept social distance from others
"cv14_4", -- CV14_4: Washed or sanitized hands frequently
"ppeducat", -- ppeducat: Education -- categorical
"ppgender", -- ppgender: Gender
"ppreg4", -- ppreg4: U.S. Census Region 4
"race", -- race: Race
"politicalideo", -- politicalideo: Political ideology
"weights", -- Weights: Weights
"cam11_par2", -- CAM11_par2: Once they are eligible, how soon will your child(ren) under the age
"cv7a", -- CV7a: Essential worker
"cv10_4_return_to_work", -- CV10_4_Return_to_work: returned to work after temporary closure
"cv14_3", -- CV14_3: Avoided enclosed spaces
"cam11_par1", -- CAM11_par1: If you have any children ages 12-17 select their vaccination status
"cv2_4_senses", -- CV2_4_Senses: Decreased sense of smell and taste
"cv5_2_urgent_care", -- CV5_2_Urgent_care: Urgent care facility
"cv11_4_little_interest", -- CV11_4_Little_interest: Household little interest or pleasure
"cv12_4_little_interest", -- CV12_4_Little_interest: Self little interest or pleasure
"cv5_4_phone", -- CV5_4_Phone: Consulted with healthcare provider over the phone
"cv10_1_children_home", -- CV10_1_Children_home: kept children home from school
"cv10_5_none", -- CV10_5_None: None
"xurbanicity", -- xurbanicity: Urbanicity
"parent", -- parent: Parent
"cv9_4_none", -- CV9_4_None: None
"cv9_1_unemployment_benefits", -- CV9_1_Unemployment_benefits: Unemployment benefits
"cv16" -- CV16: Wash hands time
FROM
"datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxb:latest"."hhs_covid19_monthly_outcome_survey_wave_07"
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 datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxb 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 datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxb: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 datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxbCheckout 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 datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxb:latestThis will download all the objects for the latest tag of datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxb 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 datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxb: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 datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxb: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, datahub-hhs-gov/hhs-covid19-monthly-outcome-survey-wave-07-6wrq-qkxb is just another Postgres schema.