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 feed_the_future_uganda_interim_survey_in_the_zone table in this repository, by referencing it like:
"usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijaj:latest"."feed_the_future_uganda_interim_survey_in_the_zone"or in a full query, like:
SELECT
":id", -- Socrata column ID
"h19a_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD meat from domesticated animals, such as beef, pork, lamb, goat, chicken, rabbit or duck? These meats can be in forms such as kebabs, sausage, chicken, beef stew, etc.
"height", -- Women s height in meters, based on reported height in centimeters in h08.
"today", -- Survey Date
"h20a_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD flesh from wild animals, such as hippopotamus, buffalo, Ugandan kob, warthog, cane rat or others
"h03", -- Please tell me how old you are. What was your age your last birthday?
"women_wt", -- Individual sampling weight for women aged 15 to 49 years
"hresp", -- Line number of Module H respondent
"w_nutsbeans", -- This measure indicates that the woman consumed beans, other types of legumes, nuts, or seeds.
"h22", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Eggs, for example from chicken, quail or duck
"h07", -- Measured weight in kilograms
"h27_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD sugary foods such as chocolates, sweets, candies, pastries, cakes, or biscuits
"cluster", -- Cluster number
"h15_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Pumpkin, carrots, squash, or sweet potatoes that are yellow or orange inside
"h18a_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD other fruits like banana including dishes made from it such as Matoke, guava, passionfruit, jack fruit, watermelon or orange
"w_foodmiss", -- This is a flag variable that indicates that questions H14 - H30 are all missing. This variable is created to exclude records missing the dietary information from analyses.
"h26_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD oil, fats, or butter, or foods made with any of these
"w_foodsum10", -- Calculated as the sum of 10 food groups: w_grains, w_beans, w_nuts, w_dairy, w_eggs, w_meatfish, w_lfygrn, w_vita, w_othveg, w_othfrt
"bmicat", -- Underweight (BMI 18.5), Normal (18.5 BMI 25), Overweight Obese (BMI 25)
"h14_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Food made from rice, maize, millet, sorghum, arrowroot or other grains such as bread, noodles, porridge, chapatti, doughnut, pancakes, rice cereal, weetabix, cornflakes etc.
"w_organmeat", -- This measure indicates that the woman consumed organ meat from wild or domesticated animals.
"w_vita", -- This measure indicates that the woman consumed orange-fleshed fruits or vegetables, red palm products, or other foods high in vitamin A.
"h26_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD oil, fats, or butter, or foods made with any of these
"idcode", -- Child s ID code
"h29_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Grubs, snails, or Insects, like grasshoppers, white ants, or termites
"w_othfrtveg", -- This variable indicates that the woman consumed other fruits or vegetables.
"w_beans", -- This measure indicates that the woman consumed beans or other types of legumes.
"h17_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD dark green leafy vegetables such as such as spinach, amaranth leaves, cassava leaves, pumpkin leaves, cowpea leaves, kale, or bean leaves
"h25", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Milk, cheese, yogurt, sour milk, or other milk products
"h14", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Food made from rice, maize, millet, sorghum, arrowroot or other grains such as bread, noodles, porridge, chapatti, doughnut, pancakes, rice cereal, weetabix, cornflakes etc.
"h24a", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD foods made from any type of beans, including cowpeas or pigeon peas? The beans can be served in stew, bean soup, bean paste, bean sauce, etc.
"h20_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD liver, kidney, heart, or other organ meats from wild animals, such as hippopotamus, buffalo, Ugandan kob, warthog, cane rat or others
"w_grains", -- This measure indicates that the woman consumed grains or starchy root vegetables.
"country", -- These data were collected in the Feed the Future Zone of Influence in Uganda.
"h30_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Foods made with red palm oil, red palm nut, or red palm nut pulp sauce
"h02_m", -- In what month and year were you born?
"wrasample", -- This flag variable indicates that the woman is aged 15 to 49 years.
"h19a_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD meat from domesticated animals, such as beef, pork, lamb, goat, chicken, rabbit or duck? These meats can be in forms such as kebabs, sausage, chicken, beef stew, etc.
"h15_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Pumpkin, carrots, squash, or sweet potatoes that are yellow or orange inside
"w_meatfish", -- This variable indicates that the woman consumed organ or flesh meat from wild or domesticated animals.
"h27", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD sugary foods such as chocolates, sweets, candies, pastries, cakes, or biscuits
"h24c_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD foods made from nuts or seeds, like cashews or almonds, pistachio nuts, or like pumpkin or sesame seeds
"h29_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Grubs, snails, or Insects, like grasshoppers, white ants, or termites
"h17a_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD other vegetables, such as cabbage or eggplant
"h19_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD liver, kidney, heart, or other organ meats from domesticated animals such as beef, pork, lamb, goat, chicken, rabbit or duck
"stratum", -- Administrative variable for identifying the sampling strata.
"h25_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Milk, cheese, yogurt, sour milk, or other milk products
"h24b_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD foods made from other legumes, such as lentils or groundnuts
"h16_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Cassava, yams, white sweet potatoes, Irish potatoes or any other foods made from roots
"h24c", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD foods made from nuts or seeds, like cashews or almonds, pistachio nuts, or like pumpkin or sesame seeds
"h20", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD liver, kidney, heart, or other organ meats from wild animals, such as hippopotamus, buffalo, Ugandan kob, warthog, cane rat or others
"h28_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Condiments for flavor, such as chilies, spices, herbs, curry powder or fish powder
"h16_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Cassava, yams, white sweet potatoes, Irish potatoes or any other foods made from roots
"w_eggs", -- This measure indicates that the woman consumed eggs.
"h04", -- Are you between the ages of 15 and 49 years old?
"w_nuts", -- This measure indicates that the woman consumed nuts or seeds.
"h18_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Ripe mangoes or pawpaw
"h06", -- Are you currently pregnant?
"h17_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD dark green leafy vegetables such as such as spinach, amaranth leaves, cassava leaves, pumpkin leaves, cowpea leaves, kale, or bean leaves
"h02_y", -- In what month and year were you born?
"h24b", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD foods made from other legumes, such as lentils or groundnuts
"h20a_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD flesh from wild animals, such as hippopotamus, buffalo, Ugandan kob, warthog, cane rat or others
"h17", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD dark green leafy vegetables such as such as spinach, amaranth leaves, cassava leaves, pumpkin leaves, cowpea leaves, kale, or bean leaves
"h20a", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD flesh from wild animals, such as hippopotamus, buffalo, Ugandan kob, warthog, cane rat or others
"h30_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Foods made with red palm oil, red palm nut, or red palm nut pulp sauce
"h30", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Foods made with red palm oil, red palm nut, or red palm nut pulp sauce
"w_dairy", -- This measure indicates that the woman consumed milk, cheese, yogurt or other foods made from animal milk.
"h16", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Cassava, yams, white sweet potatoes, Irish potatoes or any other foods made from roots
"h18a", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD other fruits like banana including dishes made from it such as Matoke, guava, passionfruit, jack fruit, watermelon or orange
"h23", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Fresh or dried fish, shellfish, or seafood
"h14_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Food made from rice, maize, millet, sorghum, arrowroot or other grains such as bread, noodles, porridge, chapatti, doughnut, pancakes, rice cereal, weetabix, cornflakes etc.
"h18", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Ripe mangoes or pawpaw
"np_wrasample", -- This flag variable indicates that the woman is aged 15 to 49 years and is not currently pregnant, based on question H06.
"h05", -- interviewer determined: Is the respondent between the ages of 15 and 49?
"survey", -- These data were collected in the 2015 Interim Zone of Influence Survey.
"h24c_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD foods made from nuts or seeds, like cashews or almonds, pistachio nuts, or like pumpkin or sesame seeds
"h19a", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD meat from domesticated animals, such as beef, pork, lamb, goat, chicken, rabbit or duck? These meats can be in forms such as kebabs, sausage, chicken, beef stew, etc.
"w_nrvcc_any", -- This measure identifies whether any of the targeted nutrient-rich value chain commodities were consumed in the prior day. The weighted mean of this measure will produce the Feed the Future prevalence indicator.
"h28", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Condiments for flavor, such as chilies, spices, herbs, curry powder or fish powder
"h24b_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD foods made from other legumes, such as lentils or groundnuts
"h18_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Ripe mangoes or pawpaw
"w_flesh", -- This measure indicates that the woman consumed flesh meat from wild or domesticated animals.
"h27_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD sugary foods such as chocolates, sweets, candies, pastries, cakes, or biscuits
"h24a_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD foods made from any type of beans, including cowpeas or pigeon peas? The beans can be served in stew, bean soup, bean paste, bean sauce, etc.
"urbrur", -- Location type (urban rural)
"h08", -- Measured height in centimeters
"h25_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Milk, cheese, yogurt, sour milk, or other milk products
"h26", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD oil, fats, or butter, or foods made with any of these
"h29", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Grubs, snails, or Insects, like grasshoppers, white ants, or termites
"underwght", -- Prevalence of underweight (BMI 18.5) among non-pregnant women aged 15-49. This is a Feed the Future indicator.
"w_othfrt", -- This measure indicates that the woman consumed other fruits.
"h15", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD Pumpkin, carrots, squash, or sweet potatoes that are yellow or orange inside
"w_lfygrn", -- This measure indicates that the woman consumed dark green leafy vegetables.
"h19", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD liver, kidney, heart, or other organ meats from domesticated animals such as beef, pork, lamb, goat, chicken, rabbit or duck
"bmi", -- Women s BMI calculated as height weight (squared)
"h18a_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD other fruits like banana including dishes made from it such as Matoke, guava, passionfruit, jack fruit, watermelon or orange
"w_nrvcc1", -- This measure identifies whether NRVCC was consumed in the prior day. The weighted mean of this measure will produce the Feed the Future prevalence indicator. NRVCC foods made from any type of beans, including cowpeas or pigeon peas? The beans can be served in stew, bean soup, bean paste, bean sauce, etc.
"region", -- Region
"h22_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Eggs, for example from chicken, quail or duck
"h23_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Fresh or dried fish, shellfish, or seafood
"h20_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD liver, kidney, heart, or other organ meats from wild animals, such as hippopotamus, buffalo, Ugandan kob, warthog, cane rat or others
"w_foodsum9", -- Calculated as the sum of 9 food groups: w_grains, w_nutsbeans, w_dairy, w_eggs, w_organmeat, w_flesh, w_lfygrn, w_vita, w_othfrtveg. The weighted mean of this variable is a Feed the Future indicator of women s dietary diversity.
"h28_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD Condiments for flavor, such as chilies, spices, herbs, curry powder or fish powder
"w_mdd", -- Calculated where 1 w_foodsum10 5 . This is the Feed the Future new indicator for women achieving a minimum dietary diversity, or 5 of the 10 food groups.
"h24a_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD foods made from any type of beans, including cowpeas or pigeon peas? The beans can be served in stew, bean soup, bean paste, bean sauce, etc.
"pbs_id", -- Administrative variable for identifying households
"h17a", -- This variable combines the spontaneously reported and the prompted recall of consumption of FOOD ? FOOD other vegetables, such as cabbage or eggplant
"weight", -- Women s weight in kilograms as reported in h07.
"h19_s", -- Respondent reported eating FOOD while describing the food eaten the prior day. FOOD liver, kidney, heart, or other organ meats from domesticated animals such as beef, pork, lamb, goat, chicken, rabbit or duck
"w_othveg", -- This measure indicates that the woman consumed other vegetables.
"h23_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Fresh or dried fish, shellfish, or seafood
"h22_p", -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD Eggs, for example from chicken, quail or duck
"h17a_p" -- When failing to mention FOOD during the reporting of foods eaten during the prior day, the respondents were asked, Yesterday, during the day or night, did you drink eat any FOOD ? FOOD other vegetables, such as cabbage or eggplant
FROM
"usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijaj:latest"."feed_the_future_uganda_interim_survey_in_the_zone"
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 usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijaj 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 usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijaj: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 usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijajCheckout 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 usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijaj:latestThis will download all the objects for the latest tag of usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijaj 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 usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijaj: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 usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijaj: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, usaid-gov/feed-the-future-uganda-interim-survey-in-the-zone-4xuk-ijaj is just another Postgres schema.