Mastering Spark with R notes

Using the code provided in section 4.5.1 AND 4.5.2, create an LDA model of the essays in the okc dataset. Create charts of most common terms per topic. ANSWER THE FOLLOWING QUESTIONS: 1. Explain how the html tags and newline characters were removed from the text. 2. How were the individual words combined into complete essays? 3. Explain what an LDA model does. 4. What are stop words? 5. In which 2 topics is the word 'want' not in the top ten? 6. What code snippet causes the topics...

The text is Mastering Spark with R. Using your sc connection and the correct Java version: 1. explain what each element is doing in the following code blocks and the difference between these two code blocks that explains the difference in the output. Explain what the output tables mean: >cars %>% + ml_linear_regression(mpg ~ .) %>% + summary() >cars %>% + ml_linear_regression(mpg ~ hp + cyl) %>% + summary() cars %>% + ml_linear_regression(mpg ~ ...

Following the instrutions in the book, install the sparklyr library and a Spark cluster on your local machine. The instructions in the book contemplate that you will be using Windows. If you are not running Windows, use a virtual machine. If you are using your employer's equipment, you may enounter a trusted domain error. This will also require that you install a virtual machine. The code in the book assumes Spark version 2.3 and Java 8. You are free to use any version, of course, but the co...

The text is Mastering Spark with R. After installing the dplyr library, use the following code in R studio, create a scatter plot of hp v. mpg cars2 <- copy_to(sc, mtcars) cars3 <- (cars2) cars4 <- select(cars3, hp, mpg) cars5 <- sample_n(cars4, 32) cars6 <- collect(cars5) plot(cars6)

Submit a Word or .pdf document with screen shots of R Studio where you have created a vector of three words. Whenever you are asked to submit a screenshot, include either a sliver of your desktop or a timestamp from your desktop. Always repeat the question you are answering.