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_28 table in this repository, by referencing it like:
"healthdata-gov/hhs-covid19-monthly-outcome-survey-wave-28-s9tn-wwkq:latest"."hhs_covid19_monthly_outcome_survey_wave_28"or in a full query, like:
SELECT
":id", -- Socrata column ID
"cam11_par2_grid_6mo4", -- CAM11_Par2_Grid_6mo4: 6 months to 4 years old
"child_age_511", -- Child_Age_511: 5 years to 11 years old
"politicalideo", -- politicalideo: Political ideology
"cam5a_vacclike", -- CAM5a_VaccLike: What is the likelihood that you will get a COVID-19 vaccine?
"race", -- race: Race
"cam6_vaccwait", -- CAM6_VaccWait: Wait to get vaccinated V2
"bstr_uv_uptake_1", -- BSTR_UV_Uptake_1: Booster
"cv5_1_hospital", -- CV5_1_Hospital: Hospital or emergency room
"cv4_2_family", -- CV4_2_Family: Family COVID diagnosis
"cv7a", -- CV7a: Essential worker
"cv6c_rec", -- CV6c_Rec: Current employment status
"cv6a_rec", -- CV6a_Rec: Employment status prior to COVID pandemic
"cv5_7_none", -- CV5_7_None: None of the above
"cv12_4_little_interest", -- CV12_4_Little_interest: Self little interest or pleasure
"cv14_1", -- CV14_1: Kept social distance from others
"cv12_1_nervous", -- CV12_1_Nervous: Self nervous, anxious, on edge
"cv4_1_self", -- CV4_1_Self: Self COVID diagnosis
"bstr_uv_uptake_2", -- BSTR_UV_Uptake_2: Updated vaccine
"bstr5_par_uptake_6mo4_2", -- BSTR5_Par_Uptake_6mo4_2: 6 months to 4 years old: Received updated vaccine
"cv8c", -- CV8c: Current insurance coverage
"cv3_2_cough", -- CV3_2_Cough: Dry cough
"cv8a", -- CV8a: Insurance coverage prior to COVID pandemic
"cv15", -- CV15: Wash hands yesterday
"cv2_5_flu", -- CV2_5_Flu: Flu symptoms
"cam11_par1_grid_6mo4", -- CAM11_Par1_Grid_6mo4: 6 months to 4 years old
"cv9_3_cares", -- CV9_3_CARES: CARES Act check
"cv6b", -- CV6b: Employment status changed since COVID pandemic
"cv16", -- CV16: Wash hands time
"ppgender", -- ppgender: Gender
"xurbanicity", -- xurbanicity: Urbanicity
"cv5_2_urgent_care", -- CV5_2_Urgent_care: Urgent care facility
"cv4_3_no", -- CV4_3_No: No COVID diagnosis
"cv3_5_flu", -- CV3_5_Flu: Flu symptoms
"cv2_4_senses", -- CV2_4_Senses: Decreased sense of smell and taste
"cv2_3_breath", -- CV2_3_Breath: Shortness of breath
"cv14_5", -- CV14_5: None of the above
"income", -- income: Income
"cv2_2_cough", -- CV2_2_Cough: Dry cough
"cv2_1_fever", -- CV2_1_Fever: Fever
"cv1", -- CV1: Physical health
"cam11_par2_grid_511", -- CAM11_Par2_Grid_511: 5 to 11 years old
"cv5_5_video", -- CV5_5_Video: Consulted with healthcare provider using video chat
"cam11_par2_grid_1217", -- CAM11_Par2_Grid_1217: 12 to 17 years old
"bstr6_par_read_1217", -- BSTR6_Par_Read_1217: 12 to 17 years old
"cv3_1_fever", -- CV3_1_Fever: Fever
"cv3_4_senses", -- CV3_4_Senses: Decreased sense of smell and taste
"cv5_4_phone", -- CV5_4_Phone: Consulted with healthcare provider over the phone
"cv7b", -- CV7b: Healthcare worker
"cv10_3_work_from_home", -- CV10_3_Work_from_home: worked from home more than before the pandemic
"cam11_par1_grid_1217", -- CAM11_Par1_Grid_1217: 12 to 17 years old
"cv5_6_chat", -- CV5_6_Chat: Consulted with healthcare provider using chat, text, or email
"cv5_3_doctor", -- CV5_3_Doctor: Visited doctor's office
"cv12_3_depressed", -- CV12_3_Depressed: Self feeling down, depressed, or hopeless
"public_id", -- public_id: Unique Identifier
"cv12_2_worrying", -- CV12_2_Worrying: Self not able to stop worrying
"bstr5_par_uptake_511_2", -- BSTR5_Par_Uptake_511_2: 5 to 11 years old: Received updated vaccine
"cv3_3_breath", -- CV3_3_Breath: Shortness of breath
"cam5_vaccuptake", -- CAM5_VaccUptake: Vaccine Uptake V2
"uptake_dates_1", -- Uptake_Dates_1 : Primary vaccine
"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
"child_age_04", -- Child_Age_04: 4 years old and younger
"child_age_1217", -- Child_Age_1217: 12 to 17 years old
"cam11_par1_grid_511", -- CAM11_Par1_Grid_511: 5 to 11 years old
"bstr6_par_read_511", -- BSTR6_Par_Read_511: 5 to 11 years old
"bstr6_par_read_6mo4", -- BSTR6_Par_Read_6mo4: 6 months to 4 years old
"bstr5_par_uptake_1217_2", -- BSTR5_Par_Uptake_1217_2: 12 to 17 years old: Received booster
"bstr5_par_uptake_1217_1", -- BSTR5_Par_Uptake_1217_1: 12 to 17 years old: No additional dose
"bstr5_par_uptake_1217_0", -- BSTR5_Par_Uptake_1217_0: 12 to 17 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_6mo4_0", -- BSTR5_Par_Uptake_6mo4_0: 6 months to 4 years old: No additional dose
"bstr5_par_uptake_6mo4_1", -- BSTR5_Par_Uptake_6mo4_1: 6 months to 4 years old: Received booster
"cv11_4_little_interest", -- CV11_4_Little_interest: Household little interest or pleasure
"cv11_3_depressed", -- CV11_3_Depressed: Household feeling down, depressed, or hopeless
"cv11_2_worrying", -- CV11_2_Worrying: Household not able to stop worrying
"cv11_1_nervous", -- CV11_1_Nervous: Household nervous, anxious, on edge
"cv10_5_none", -- CV10_5_None: None
"cv14_2", -- CV14_2: Wore a mask
"cv8b", -- CV8b: Insurance changed since COVID pandemic
"bstr5_par_uptake_511_1", -- BSTR5_Par_Uptake_511_1: 5 to 11 years old: Received booster
"cv10_4_return_to_work", -- CV10_4_Return_to_work: returned to work after temporary closure
"cv14_3", -- CV14_3: Avoided enclosed spaces
"cv14_4", -- CV14_4: Washed or sanitized hands frequently
"parent", -- parent: Parent
"agecat", -- agecat: Age category
"ppeducat", -- ppeducat: Education -- categorical
"ppreg4", -- ppreg4: U.S. Census Region 4
"weights", -- Weights: Weights
"cv13", -- CV13: Time spent at home
"cv10_2_home_schooled", -- CV10_2_Home_schooled: home schooled children
"cv10_1_children_home", -- CV10_1_Children_home: kept children home from school
"cv9_4_none", -- CV9_4_None: None
"cv9_2_covid_enhanced", -- CV9_2_COVID_enhanced: COVID related enhanced unemployment benefits
"cv9_1_unemployment_benefits", -- CV9_1_Unemployment_benefits: Unemployment benefits
"bstr4_readiness_2" -- BSTR4_Readiness_2: Wait to get an updated vaccine
FROM
"healthdata-gov/hhs-covid19-monthly-outcome-survey-wave-28-s9tn-wwkq:latest"."hhs_covid19_monthly_outcome_survey_wave_28"
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-28-s9tn-wwkq 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-28-s9tn-wwkq: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-28-s9tn-wwkq" \
--handler-options '{
"domain": "healthdata.gov",
"tables": {
"hhs_covid19_monthly_outcome_survey_wave_28": "s9tn-wwkq"
}
}'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-28-s9tn-wwkq is just another Postgres schema.