Showing posts with the label MapR

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The Quick and Easy Way to Analyze Numpy Arrays

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

What is MapR? Here are Top Features to Use in Data Analytics

In the following post I have given information about MapR and its popular features. The MapR’ is a San Jose, California-based organization code corporation that progresses and vends Apache Hadoop-derived code. The corporation gives to Apache Hadoop programs like HBase, Pig (programming language), Apache Hive, and Apache ZooKeeper. Apache Hadoop and Apache Spark, a distributed file system, a multi-model database management system, and event stream processing, combining analytics in real-time with operational applications. Its technology runs on both commodity hardware and public cloud computing services. MapR was picked by Amazon to supply an improved variant of Amazon’s Elastic Map Reduce (EMR) facility MapR has as well been picked by Google as a technics collaborator. MapR was capable to split the minute type pace record onto Google’s calculate program. "MapR delivers 3 adaptations of their article familiar like M3, M5 and M7. M3 is a gratis variant of the M5 arti