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) Country) Population (Population) China 600 USA 100 Canada 100 UK 200 France 300 Japan 250 Germany 200 Mexico 50 India 250 The population of Asia and North America is counted based on the population data of this country. The following result is returned. Continent Population Asia 1100 North Ame

function returns only the first qualifying value, and the remainder of the case is automatically ignored. For example, the following SQL, you can never get the "second class" result Case when Col_ in (' A ', ' B ') THEN ' first class ' When Col_ in (' a ') THEN ' Second class ' else ' other ' end Let's take a look at what we can do with the case function. First, the known data is grouped and analyzed in a different way. Have the following data: (in order to see more clea

analyzed in a different way. Have the following data: (in order to see more clearly, I did not use the country code, but directly using the country name as primary Key) Country (country) population (population) China 600 United States 100 Canada 100 United Kingdom 200 France 300 Japan 250 Germany 200 Mexico 50 India 250 According to the population data of this country, the population of Asia and North America is counted. Should get the fo

example, the following SQL, you can never get the "second class" results The code is as follows Case when col_1 in (' A ', ' B ') THEN ' first class ' When Col_1 in (' a ') THEN ' Class II ' Else ' other ' end Let's take a look at what we can do with the case function. First, the known data is grouped and analyzed in a different way. Have the following data: (in order to see more clearly, I did not use the country code, but directly using the country name as primary Key) Country (countr

= function () { emit (This.country, {count:1}); } Reduce accepts two parameters, one is key, the first value returned by emit, and an array consisting of {count:1} documents corresponding to one or more keys. reduce = function (key, value) { var result = {count:0}; for (var i = 0; i Sample table Data: {"_id": "Country": "Japan", "Money": 724} {"_id": "Country": "Germany", "Money": 520} {"_id": "Country": "India", "Money": 934} {"_id": "Country": "Our", "Money": 72

, you can never get the "second class" results The code is as follows Case when col_1 in (' A ', ' B ') THEN ' first class ' When Col_1 in (' a ') THEN ' Class II ' Else ' other ' end Let's take a look at what we can do with the case function. First, the known data is grouped and analyzed in a different way. Have the following data: (in order to see more clearly, I did not use the country code, but directly using the country name as primary Key) Country (country) population (population) China 60

the case function returns only the first qualifying value, and the remainder of the case is automatically ignored. For example, the following SQL, you can never get the "second class" results The code is as follows Copy Code Case when col_1 in (' A ', ' B ') THEN ' first class 'When Col_1 in (' a ') THEN ' Class II 'Else ' other ' end Let's take a look at what we can do with the case function. First, the known data is grouped and analyzed in a diff

a different way to group, analysis.There is the following data: (in order to see more clearly, I did not use the country code, but directly with the country name as primary Key) Country (country) Population (population) China 600 United States 100 Canada 100 United Kingdom 200 France 300 Japan 250

the country name as primary Key) Country (country) Population (population) China 600 United States 100 Canada 100 United Kingdom 200 France 300 Japan 250 Germany 200 Mexico 50 India 250 According to the population data of this country, the p

' man ' when sex = ' 2 ' Then ' Women ' Else ' other ' ENDIn both of these ways, the same functionality can be achieved. The simple case function is relatively concise, but there are some limitations in function, such as write-judgement, compared to the search function.There is also a problem to be aware that the case function returns only the first qualifying value, and the remaining case section is automatically ignored.--for example, the following SQL, you can never get the result of a "seco

primary Key) Country (country) Population (population) China 600 United States 100 Canada 100 United Kingdom 200 France 300 Japan 250 Germany 200 Mexico 50 India 250 According to the population data of this country, the population of Asia and

to see more clearly, I did not use the country code, but directly with the country name as primary Key) Country (country) Population (population) China 600 United States 100 Canada 100 United Kingdom 200 France 300 Japan 250 Germany 200 Mexico 50 India

) Country (country) Population (population) China 600 United States 100 Canada 100 United Kingdom 200 France 300 Japan 250 Germany 200 Mexico 50 India 250 According to the population data of this country, the population of Asia and North America

, the known data is grouped in another way, analyzed. has the following data: (in order to see more clearly, I did not use the country code, but directly with the country name as primary Key) Country (country) Population (population) China 600 United States 100 Canada 100 United Kingdom 200 France 300 Japan

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country code, but directly using the country name as primary Key) Country (country) Population (population) China 600 United States 100 Canada 100 United Kingdom 200 France 300 Japan 250 Germany 200 Mexico 50 India 250 According to the population data of this country, the population

another way, analyzed. has the following data: (in order to see more clearly, I did not use the country code, but directly with the country name as primary Key) Country (country) Population (population) China 600 United States 100 Canada 100 United Kingdom 200 France 300 Japan 250 Germany

', 80)INSERT into Testscore values (' John Doe ', ' English ', 90)Select Tname as ' name ',Max (case ttype "language" then Tscor else 0 end) ' Language ',Max (case ttype when ' math ' then Tscor else 0 end) ' Math ',Max (case ttype when ' English ' then Tscor else 0 end) ' English 'From TestscoreGROUP BY TnameExample TwoThere is the following data: (in order to see more clearly, I did not use the country code, but directly with the country name as primary Key) Country (country)

key) country) Population China 600 USA 100 Canada 100 UK 200 France 300 Japan 250 Germany 200 Mexico 50 India 250 The population of Asia and North America is counted based on the population data of this country. The following result is returned.

electronic devices Transfer Rate (%) √ √ √ First pass rate (%) √ √ √ Manufacturing cost per unit ($) √ × √ Material Inventory days × √ √ And so on... Looking at this table, Mo Miao frowned: "You can't waste any time organizing the data. You need to focus on analyzing and coping with the factory manufacturing work ." Alan thought for a while and thought it was time to a