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The Quick and Easy Way to Analyze Numpy Arrays

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The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par
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Advanced Oozie for Software developers (Part 1 of 3)

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Introduction to Oozie Places or points of interest in specific locations that may be important to some people. Those locations are additionally associated with data that explains what is interesting or important about them. How People Gather Data? These are typically locations where people come for entertainment, interaction, services, education, and other types of social activities. Examples of places include restaurants, museums, theaters, stadiums, hotels, landmarks, and so on. Many companies gather data about places and use this data in their applications. In the telecommunications industry, probes are small packages of information sent from mobile devices. The majority of "smartphones" send probes regularly when the device is active and is running a geographical application (such as maps, navigation, traffic reports, and so on). The probe frequency varies for different providers (from 5 seconds to 30 seconds). Probes are normally directed to phone carriers su
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Oozie - Concepts And Architecture

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Oozie is a workflow/coordination system that you can use to manage Apache Hadoop jobs. It is one of the main components of Oozie is the Oozie server — a web application that runs in a Java servlet container (the standard Oozie distribution is using Tomcat). Oozie is a workflow management-server that works on the Oozie server. Role of Oozie in Workflow Management in Hadoop Jobs This server supports reading and executing Workflows, Coordinators, Bundles, and SLA definitions . It implements a set of remote Web Services APIs that can be invoked from Oozie client components and third-party applications. Add a note where the execution of the server leverages a customizable database. This database contains Workflow, Coordinator, Bundle, and SLA definitions, as well as execution states and process variables. The list of currently supported databases includes MySQL, Oracle, and Apache Derby. The Oozie shared library component is located in the Oozie HOME directory and contains code u
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