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Showing posts with the label key-value-database

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Python map() and lambda() Use Cases and Examples

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 In Python, map() and lambda functions are often used together for functional programming. Here are some examples to illustrate how they work. Python map and lambda top use cases 1. Using map() with lambda The map() function applies a given function to all items in an iterable (like a list) and returns a map object (which can be converted to a list). Example: Doubling Numbers numbers = [ 1 , 2 , 3 , 4 , 5 ] doubled = list ( map ( lambda x: x * 2 , numbers)) print (doubled) # Output: [2, 4, 6, 8, 10] 2. Using map() to Convert Data Types Example: Converting Strings to Integers string_numbers = [ "1" , "2" , "3" , "4" , "5" ] integers = list ( map ( lambda x: int (x), string_numbers)) print (integers) # Output: [1, 2, 3, 4, 5] 3. Using map() with Multiple Iterables You can also use map() with more than one iterable. The lambda function can take multiple arguments. Example: Adding Two Lists Element-wise list1 = [ 1 , 2 , 3 ]

RDBMS Vs Key-value Four Top Differences

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This post tells you differences between rdbms and distributed key-value storage. Rdbms is quite  different from key-value storage. RDBMS (Relational Database) You have already used a  r elational  d atabase  m anagement  s ystem — a storage product that's commonly referred to as  RDBMS .  It is basically a structured data. RDBMS systems are fantastically useful to handle moderate data. The BIG challenge is in scaling beyond a single server.  You can't maintain redundant data in rdbms. All the data available on single server. The entire database runs on single server. So when server is down then database may not be available to normal business operations. Outages and server downs are common in this rdbms model of database. Key-Value Database Key-value storage systems often make use of redundancy within hardware resources to prevent outages. This concept is important when you're running thousands of servers because they're bound to suffer hardware bre