Oct 23, 2013 Cash Counter is useful for maintaining real time balance of denomination on your cash counter. It is handy software which works like your real Cash Counter useful for maintaining the records of inflow and outflow of the denominations. Word Counter is an application that performs a word count and a character count, but it can do much more. It can be used independently or in conjunction with other applications such as TextEdit, Microsoft Word, Pages, TextWrangler, and others. Word Counter can automatically update the count based on a user-defined time interval.
These examples give a quick overview of the Spark API.Spark is built on the concept of distributed datasets, which contain arbitrary Java orPython objects. You create a dataset from external data, then apply parallel operationsto it. The building block of the Spark API is its RDD API.In the RDD API,there are two types of operations: transformations, which define a new dataset based on previous ones,and actions, which kick off a job to execute on a cluster.On top of Spark’s RDD API, high level APIs are provided, e.g.DataFrame API andMachine Learning API.These high level APIs provide a concise way to conduct certain data operations.In this page, we will show examples using RDD API as well as examples using high level APIs.
RDD API Examples
Word Count
In this example, we use a few transformations to build a dataset of (String, Int) pairs called counts and then save it to a file.
Pi Estimation
Spark can also be used for compute-intensive tasks. This code estimates π by 'throwing darts' at a circle. We pick random points in the unit square ((0, 0) to (1,1)) and see how many fall in the unit circle. The fraction should be π / 4, so we use this to get our estimate.
DataFrame API Examples
In Spark, a DataFrameis a distributed collection of data organized into named columns.Users can use DataFrame API to perform various relational operations on both externaldata sources and Spark’s built-in distributed collections without providing specific procedures for processing data.Also, programs based on DataFrame API will be automatically optimized by Spark’s built-in optimizer, Catalyst.
Text Search
In this example, we search through the error messages in a log file.
Simple Data Operations
In this example, we read a table stored in a database and calculate the number of people for every age.Finally, we save the calculated result to S3 in the format of JSON.A simple MySQL table 'people' is used in the example and this table has two columns,'name' and 'age'.
Word Counter 1.6.2 Free
Machine Learning Example
MLlib, Spark’s Machine Learning (ML) library, provides many distributed ML algorithms.These algorithms cover tasks such as feature extraction, classification, regression, clustering,recommendation, and more. MLlib also provides tools such as ML Pipelines for building workflows, CrossValidator for tuning parameters,and model persistence for saving and loading models.
Prediction with Logistic Regression
In this example, we take a dataset of labels and feature vectors.We learn to predict the labels from feature vectors using the Logistic Regression algorithm.
Many additional examples are distributed with Spark:
WordCounter 1.6.2 Get clarity about how you write, when, and where. Measure your productivity to write more.
Thursday January 01, 1970
Why count your words? A writer should write. The WordCounter … gives immediate feedback on your productivity as a writer. encourages you by showing you your daily output. gives you clarity about your daily goals. keeps a complete history of your daily achievements. assists with finding your perfect writing environment. counts what counts: words – the ultimate metric for writing. Requires macOS 10.12+. Ready for Catalina. Home Page – https://wordcounterapp.com/
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