Posts

Showing posts with the label google mapreduce

Featured Post

Python Program: JSON to CSV Conversion

-
Image
JavaScript object notion is also called JSON file, it's data you can write to a CSV file. Here's a sample python logic for your ready reference.  You can write a simple python program by importing the JSON, and CSV packages. This is your first step. It is helpful to use all the JSON methods in your python logic. That means the required package is JSON. So far, so good. In the next step, I'll show you how to write a Python program. You'll also find each term explained. What is JSON File JSON is key value pair file. The popular use of JSON file is to transmit data between heterogeneous applications. Python supports JSON file. What is CSV File The CSV is comma separated file. It is popularly used to send and receive data. How to Write JSON file data to a CSV file Here the JSON data that has written to CSV file. It's simple method and you can use for CSV file conversion use. import csv, json json_string = '[{"value1": 1, "value2": 2,"value3
Post a Comment
Read more

IBM PML Vs Google MapReduce why you need to read

-
Image
IBM Parallel Machine Learning Toolbox (PML) is similar to that of Google's MapReduce programming model (Dean and Ghemawat, 2004) and the open source Hadoop system,which is to provide Application Programming Interfaces (APIs) that enable programmers who have no prior experience in parallel and distributed systems to nevertheless implement parallel algorithms with relative ease. Google MapReduce Vs IBM PML Like MapReduce and Hadoop, PML supports associative-commutative computations as its primary parallelization mechanism .  Unlike MapReduce and Hadoop, PML fundamentally assumes that learning algorithms can be iterative in nature, requiring multiple passes over data. The ability to maintain the state of each worker node between iterations, making it possible, for example, to partition and distribute data structures across workers Efficient distribution of data, including the ability of each worker to read a subset of the data, to sample the data, or to scan the entire data
Post a Comment
Read more