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_26 table in this repository, by referencing it like:
"healthdata-gov/hhs-covid19-monthly-outcome-survey-wave-26-af8q-tquk:latest"."hhs_covid19_monthly_outcome_survey_wave_26"or in a full query, like:
SELECT
":id", -- Socrata column ID
"cv11_1_nervous", -- CV11_1_Nervous: Household nervous, anxious, on edge
"uptake_dates_1", -- Uptake_Dates_1 : Primary vaccine
"bstr_uv_uptake_2", -- BSTR_UV_Uptake_2: Updated vaccine
"ppreg4", -- ppreg4: U.S. Census Region 4
"cv2_1_fever", -- CV2_1_Fever: Fever
"bstr6_par_read_511", -- BSTR6_Par_Read_511: 5 to 11 years old
"cam11_par1_grid_511", -- CAM11_Par1_Grid_511: 5 to 11 years old
"cv3_5_flu", -- CV3_5_Flu: Flu symptoms
"cv3_2_cough", -- CV3_2_Cough: Dry cough
"cv7b", -- CV7b: Healthcare worker
"cam5_vaccuptake", -- CAM5_VaccUptake: Vaccine Uptake V2
"cv14_1", -- CV14_1: Kept social distance from others
"cv14_2", -- CV14_2: Wore a mask
"cv9_3_cares", -- CV9_3_CARES: CARES Act check
"cv5_4_phone", -- CV5_4_Phone: Consulted with healthcare provider over the phone
"cv4_3_no", -- CV4_3_No: No COVID diagnosis
"cv4_2_family", -- CV4_2_Family: Family COVID diagnosis
"cv16", -- CV16: Wash hands time
"bstr5_par_uptake_511_2", -- BSTR5_Par_Uptake_511_2: 5 to 11 years old: Received updated vaccine
"cv5_2_urgent_care", -- CV5_2_Urgent_care: Urgent care facility
"child_age_04", -- Child_Age_04: 4 years old and younger
"ppgender", -- ppgender: Gender
"cv10_2_home_schooled", -- CV10_2_Home_schooled: home schooled children
"bstr5_par_uptake_1217_1", -- BSTR5_Par_Uptake_1217_1: 12 to 17 years old: No additional dose
"cv10_5_none", -- CV10_5_None: None
"cv10_1_children_home", -- CV10_1_Children_home: kept children home from school
"cv5_1_hospital", -- CV5_1_Hospital: Hospital or emergency room
"cv2_4_senses", -- CV2_4_Senses: Decreased sense of smell and taste
"cv5_6_chat", -- CV5_6_Chat: Consulted with healthcare provider using chat, text, or email
"cv9_4_none", -- CV9_4_None: None
"cv5_3_doctor", -- CV5_3_Doctor: Visited doctor's office
"cv2_2_cough", -- CV2_2_Cough: Dry cough
"cv3_4_senses", -- CV3_4_Senses: Decreased sense of smell and taste
"cv1", -- CV1: Physical health
"cv2_5_flu", -- CV2_5_Flu: Flu symptoms
"cv10_4_return_to_work", -- CV10_4_Return_to_work: returned to work after temporary closure
"cv4_1_self", -- CV4_1_Self: Self COVID diagnosis
"bstr5_par_uptake_6mo4_0", -- BSTR5_Par_Uptake_6mo4_0: 6 months to 4 years old: No additional dose
"parent", -- parent: Parent
"cv8c", -- CV8c: Current insurance coverage
"xurbanicity", -- xurbanicity: Urbanicity
"cv12_2_worrying", -- CV12_2_Worrying: Self not able to stop worrying
"public_id", -- public_id: Unique Identifier
"bstr_uv_uptake_1", -- BSTR_UV_Uptake_1: Booster
"uptake_dates_2", -- Uptake_Dates_2 : Booster
"uptake_dates_3", -- Uptake_Dates_3 : Updated vaccine
"bstr3_like_2", -- BSTR3_Like_2: Intention to get an updated vaccine
"bstr4_readiness_2", -- BSTR4_Readiness_2: Wait to get an updated vaccine
"cam5a_vacclike", -- CAM5a_VaccLike: What is the likelihood that you will get a COVID-19 vaccine?
"cam6_vaccwait", -- CAM6_VaccWait: Wait to get vaccinated V2
"child_age_511", -- Child_Age_511: 5 years to 11 years old
"child_age_1217", -- Child_Age_1217: 12 to 17 years old
"cam11_par1_grid_6mo4", -- CAM11_Par1_Grid_6mo4: 6 months to 4 years old
"cam11_par1_grid_1217", -- CAM11_Par1_Grid_1217: 12 to 17 years old
"cam11_par2_grid_6mo4", -- CAM11_Par2_Grid_6mo4: 6 months to 4 years old
"cam11_par2_grid_511", -- CAM11_Par2_Grid_511: 5 to 11 years old
"cam11_par2_grid_1217", -- CAM11_Par2_Grid_1217: 12 to 17 years old
"bstr5_par_uptake_6mo4_1", -- BSTR5_Par_Uptake_6mo4_1: 6 months to 4 years old: Received booster
"bstr5_par_uptake_6mo4_2", -- BSTR5_Par_Uptake_6mo4_2: 6 months to 4 years old: Received updated vaccine
"bstr5_par_uptake_511_0", -- BSTR5_Par_Uptake_511_0: 5 to 11 years old: No additional dose
"bstr5_par_uptake_511_1", -- BSTR5_Par_Uptake_511_1: 5 to 11 years old: Received booster
"bstr5_par_uptake_1217_0", -- BSTR5_Par_Uptake_1217_0: 12 to 17 years old: Received updated vaccine
"bstr5_par_uptake_1217_2", -- BSTR5_Par_Uptake_1217_2: 12 to 17 years old: Received booster
"bstr6_par_read_6mo4", -- BSTR6_Par_Read_6mo4: 6 months to 4 years old
"bstr6_par_read_1217", -- BSTR6_Par_Read_1217: 12 to 17 years old
"cv2_3_breath", -- CV2_3_Breath: Shortness of breath
"cv3_1_fever", -- CV3_1_Fever: Fever
"cv3_3_breath", -- CV3_3_Breath: Shortness of breath
"cv5_5_video", -- CV5_5_Video: Consulted with healthcare provider using video chat
"cv5_7_none", -- CV5_7_None: None of the above
"cv6a_rec", -- CV6a_Rec: Employment status prior to COVID pandemic
"cv6b", -- CV6b: Employment status changed since COVID pandemic
"cv6c_rec", -- CV6c_Rec: Current employment status
"cv7a", -- CV7a: Essential worker
"cv8a", -- CV8a: Insurance coverage prior to COVID pandemic
"cv8b", -- CV8b: Insurance changed since COVID pandemic
"cv9_1_unemployment_benefits", -- CV9_1_Unemployment_benefits: Unemployment benefits
"cv9_2_covid_enhanced", -- CV9_2_COVID_enhanced: COVID related enhanced unemployment benefits
"cv10_3_work_from_home", -- CV10_3_Work_from_home: worked from home more than before the pandemic
"cv11_2_worrying", -- CV11_2_Worrying: Household not able to stop worrying
"cv11_3_depressed", -- CV11_3_Depressed: Household feeling down, depressed, or hopeless
"cv11_4_little_interest", -- CV11_4_Little_interest: Household little interest or pleasure
"cv12_1_nervous", -- CV12_1_Nervous: Self nervous, anxious, on edge
"cv12_3_depressed", -- CV12_3_Depressed: Self feeling down, depressed, or hopeless
"cv12_4_little_interest", -- CV12_4_Little_interest: Self little interest or pleasure
"cv13", -- CV13: Time spent at home
"cv14_3", -- CV14_3: Avoided enclosed spaces
"cv14_4", -- CV14_4: Washed or sanitized hands frequently
"cv14_5", -- CV14_5: None of the above
"cv15", -- CV15: Wash hands yesterday
"agecat", -- agecat: Age category
"ppeducat", -- ppeducat: Education -- categorical
"income", -- income: Income
"race", -- race: Race
"politicalideo", -- politicalideo: Political ideology
"weights" -- Weights: Weights
FROM
"healthdata-gov/hhs-covid19-monthly-outcome-survey-wave-26-af8q-tquk:latest"."hhs_covid19_monthly_outcome_survey_wave_26"
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 healthdata-gov/hhs-covid19-monthly-outcome-survey-wave-26-af8q-tquk with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at healthdata.gov. When you queryhealthdata-gov/hhs-covid19-monthly-outcome-survey-wave-26-af8q-tquk: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 healthdata.gov, 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 \
"healthdata-gov/hhs-covid19-monthly-outcome-survey-wave-26-af8q-tquk" \
--handler-options '{
"domain": "healthdata.gov",
"tables": {
"hhs_covid19_monthly_outcome_survey_wave_26": "af8q-tquk"
}
}'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, healthdata-gov/hhs-covid19-monthly-outcome-survey-wave-26-af8q-tquk is just another Postgres schema.