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4 minutes read
Physical memory in a Hadoop cluster refers to the actual RAM available on the nodes within the cluster. This memory is used for storing data and executing tasks related to distributed computing in the Hadoop framework. The physical memory plays a crucial role in the performance and scalability of the Hadoop cluster, as it determines the amount of data that can be processed and the speed at which tasks can be executed.
4 minutes read
To force matplotlib to scale images, you can use the aspect parameter when plotting the image. By setting aspect='auto', matplotlib will scale the image to fit the available space in the plot. You can also adjust the size of the figure using the figsize parameter to control the overall size of the plot. Additionally, you can adjust the aspect ratio of the plot itself by setting aspect_ratio to a specific value.
7 minutes read
To get the maximum word count in Hadoop, you can start by writing a MapReduce program that counts the occurrences of each word in the input data. Make sure to design your program in a way that efficiently distributes and processes the data across the cluster. You can also consider increasing the number of reduce tasks to parallelize the processing and improve the overall performance.
5 minutes read
To show a progressive curve in matplotlib, you can use the plot function with a list of x-values and y-values that increase gradually. By plotting points with increasing y-values, you will be able to create a curve that shows progression over time or another dimension. Additionally, you can adjust the parameters of the plot such as color, line style, and markers to enhance the visual representation of the progressive curve.
6 minutes read
To sort a custom writable type in Hadoop, you need to implement the WritableComparable interface in your custom writable type class. This interface extends the Writable interface and adds a compareTo() method, which defines how instances of your class should be compared for sorting.In the compareTo() method, you need to specify the logic for comparing two instances of your custom writable type.
2 minutes read
To remove a plot in matplotlib using Python, you can use the remove() method on the plot object. First, you need to store the plot object that you want to remove in a variable. Then, you can call the remove() method on that variable to remove the plot from the current figure. This will effectively remove the plot from the plot window and the plot will no longer be visible.How can I remove a heatmap plot in matplotlib.
7 minutes read
In Hadoop, it is important to structure code directories in a way that makes it easy to manage and organize the large amount of data and computations involved. One common practice is to have separate directories for different components of the code, such as input data, output data, mapper code, reducer code, and configuration files. This makes it easier to locate and update specific parts of the code when needed.
4 minutes read
To animate a 2D NumPy array using Matplotlib, you can use the imshow() function to display the array as an image. You can then create a loop to update the data in the array and replot the image at each iteration to create the animation. Use the animation module in Matplotlib to animate the plot by creating a function that updates the data in the array, and then use the FuncAnimation class to animate the plot by calling the update function at each frame.
4 minutes read
To export data from Hadoop to a mainframe, you can use tools such as FTP or Secure FTP (SFTP) to transfer files between the Hadoop cluster and the mainframe system. Another option is to use a data integration tool like Apache Nifi or Apache Sqoop to efficiently move data from Hadoop to the mainframe. Additionally, you can write custom scripts in languages like Python or Java to facilitate the data transfer process.
5 minutes read
To remove "none" from a pie chart in matplotlib, you can update the data that is being plotted to exclude any entries with a value of "none". This can be done by filtering out the data before creating the pie chart. Make sure to replace the labels and values with the filtered data. Additionally, you can adjust the autopct parameter in the plt.pie() function to only display labels for data that you want to show. This way, the "none" label will not appear on the pie chart.