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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 ]

Microsoft HDInsight for Hadoop Cluster

HDInsight is Microsoft's implementation of a Big Data solution with Apache Hadoop at its core. HDInsight is 100 percent compatible with Apache Hadoop and is built on open source components in conjunction with Hortonworks, a company focused toward getting Hadoop adopted on the Windows platform.

HDINSIGHT


HDInsight Microsoft


Initiate


Basically, Microsoft has taken the open source Hadoop project, added the functionalities needed to make it compatible with Windows (because Hadoop is based on Linux), and submitted the project back to the community. 


All of the components are retested in typical scenarios to ensure that they work together correctly and that there are no versioning or compatibility issues.


Features


Microsoft's Hadoop-based distribution brings the robustness, manageability, and simplicity of Windows to the Hadoop environment. 


The focus is on hardening security through integration with Active Directory, thus making it enterprise ready, simplifying manageability through integration with System Center 2012, and dramatically reducing the time required to set up and deploy via simplified packaging and configuration.


Security


These improvements will enable IT to apply consistent security policies across Hadoop clusters and manage them from a single pane of glass on System Center 2012. Further, Microsoft SQL Server and its powerful BI suite can be leveraged to apply analytics and generate interactive business intelligence reports, all under the same roof. 


Easy Deployment


For the Hadoop-based service on Windows Azure, Microsoft has further lowered the barrier to deployment by enabling the seamless setup and configuration of Hadoop clusters through an easy-to-use, web-based portal and offering Infrastructure as a Service (IaaS).


Microsoft is currently the only company offering scalable Big Data solutions in the cloud and for on-premises use. These solutions are all built on a common Microsoft Data Platform with familiar and powerful BI tools.


HDInsight is available in two flavors



1. Windows Azure HDInsight Service



This is a service available to Windows Azure subscribers that uses Windows Azure clusters and integrates with Windows Azure storage. 


An Open Database Connectivity (ODBC) driver is available to connect the output from HDInsight queries to data analysis tools.


2. Windows Azure HDInsight Emulator



This is a single-node, single-box product that you can install on Windows Server 2012, or in your Hyper-V virtual machines.

 
The purpose of the emulator is to provide a development environment for use in testing and evaluating your solution before deploying it to the cloud. 


You save money by not paying for Azure hosting until after your solution is developed and tested and ready to run. The emulator is available for free and will continue to be a single-node offering.

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