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Python: Built-in Functions vs. For & If Loops – 5 Programs Explained

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Python’s built-in functions make coding fast and efficient. But understanding how they work under the hood is crucial to mastering Python. This post shows five Python tasks, each implemented in two ways: Using built-in functions Using for loops and if statements ✅ 1. Sum of a List ✅ Using Built-in Function: numbers = [ 10 , 20 , 30 , 40 ] total = sum (numbers) print ( "Sum:" , total) 🔁 Using For Loop: numbers = [ 10 , 20 , 30 , 40 ] total = 0 for num in numbers: total += num print ( "Sum:" , total) ✅ 2. Find Maximum Value ✅ Using Built-in Function: values = [ 3 , 18 , 7 , 24 , 11 ] maximum = max (values) print ( "Max:" , maximum) 🔁 Using For and If: values = [ 3 , 18 , 7 , 24 , 11 ] maximum = values[ 0 ] for val in values: if val > maximum: maximum = val print ( "Max:" , maximum) ✅ 3. Count Vowels in a String ✅ Using Built-ins: text = "hello world" vowel_count = sum ( 1 for ch in text if ch i...

Apache Yarn to Manage Resources a Solution

Apache Hadoop is one of the most popular tools for big data processing. It has been successfully deployed in production by many companies for several years.  Though Hadoop is considered a reliable, scalable, and cost-effective solution, it is constantly being improved by a large community of developers. As a result, the 2.0 version offers several revolutionary features, including Yet Another Resource Negotiator (YARN), HDFS Federation, and a highly available NameNode, which make the Hadoop cluster much more efficient, powerful, and reliable.  Apache Yarn Apache Hadoop 2.0 includes YARN, which separates the resource management and processing components. The YARN-based architecture is not constrained to MapReduce. New developmens in Hadoop 2.0 Architecture with YARN:  ResourceManager instead of a cluster manager  ApplicationMaster instead of a dedicated and short-lived JobTracker  NodeManager instead of TaskTracker  A distributed application inst...