R" in the Spark repo. Sets the string that indicates a time zone ID to be used to format timestamps in the JSON datasources or partition values. Other short names like 'CST' are not recommended to use because they can be ambiguous. Infers all floating-point values as a decimal type. If the values do not fit in decimal, then it infers them as doubles.
Allows a mode for dealing with corrupt records during parsing. To keep corrupt records, an user can set a string type field named columnNameOfCorruptRecord in an user-defined schema. Set up your MongoDB database and learn to search, create, and analyze your data. Lectures are taught by MongoDB curriculum engineers.
Each video lecture is about 5 minutes long. Measure your progress and test your knowledge after each lesson. Get the eBook. Unify all your data and AI with one open platform to more easily achieve your data goals Register for the livecast.
Learn how to unlock the potential inside your data lake in two ways. Watch on-demand. In this tutorial module, you will learn how to: Create sample data Load sample data View a DataSet Process and visualize the Dataset We also provide a sample notebook that you can import to access and run all of the code examples included in the module.
View the Dataset To view the data in a tabular format instead of exporting it to a third-party tool, you can use the Databricks display command. Process and visualize the Dataset A Dataset has transformations and actions.
Additional Resources Apache Spark 2. Spark: Better with Delta Lake This series of tech talk tutorials takes you through the technology foundation of Delta Lake Apache Spark and the capabilities Delta Lake adds to it to power cloud data lakes. Don't remove a quiz or an exam! One way is to find the lowest homework in code and then update the scores array with the low homework pruned. To confirm you are on the right track, here are some queries to run after you process the data with the correct answer shown: Let us count the number of students we have: use school db.
Let's see what Tamika Schildgen's record looks like: db. Making your blog accept posts In this homework you will be enhancing the blog project to insert entries into the posts collection. After this, the blog will work. It will allow you to add blog posts with a title, body and tags and have it be added to the posts collection properly. We have provided the code that creates users and allows you to login the assignment from last week.
To get started, please download hwand You will be using these files for this homework, and for HW 3. The areas where you need to add code are marked with XXX. There are three locations for you to add code for this problem. Scan that file for XXX to see where to work. As a reminder, to run your blog you type python blog.
It makes connections to both to determine if your program works properly. Validate connects to localhost and expects that mongod is running on localhost on port As before, validate will take some optional arguments if you want to run mongod on a different host or a use an external webserver. This project requires Python 2. The code is not 3. Ok, once you get the blog posts working, validate.
Please enter it below, exactly as shown with no spaces. Making your blog accept comments In this homework you will add code to your blog so that it accepts comments.
You will be using the same code as you downloaded for HW 3. There is just one location that you need to modify. You don't need to figure out how to retrieve comments for this homework because the code you did in 3. This assignment has fairly little code, but it's a little more subtle than the previous assignment because you are going to be manipulating an array within the Mongo document. For the sake of clarity, here is a document out of the posts collection from a working project.
It checks the web output as well as the database documents. Check all that apply. What can you infer from the following explain output? Making the Blog fast Please download hw This assignment requires Mongo 3. In this homework assignment you will be adding some indexes to the post collection to make the blog fast. We have provided the full code for the blog application and you don't need to make any changes, or even run the blog.
But you can, for fun. We are also providing a patriotic if you are an American data set for the blog. There are entries with lots of comments and tags. You must load this dataset to complete the problem. From the mongo shell: use blog db. There are hyperlinks from the post tags to the page that displays the 10 most recent blog entries for that tag. To figure out what queries you need to optimize, you can read the blog. Isolate those queries and use explain to explore. Once you have added the indexes to make those pages fast run the following.
In this problem you will analyze a profile log taken from a different mongoDB instance and you will import it into a collection named sysprofile. To start, please download sysprofile. What is the latency of the longest running operation to the collection, in milliseconds?
Finding the most frequent author of comments on your blog In this assignment you will use the aggregation framework to find the most frequent author of comments on your blog. We will be using a data set similar to ones we've used before. Start by downloading the handout zip file for this problem. Then import into your blog database as follows: mongoimport -d blog -c posts --drop posts. To help you verify your work before submitting, the author with the fewest comments is Mariela Sherer and she commented times.
Please choose your answer below for the most prolific comment author:. Crunching the Zipcode dataset Please calculate the average population of cities in California abbreviation CA and New York NY taken together with populations over 25, For this problem, assume that a city name that appears in more than one state represents two separate cities.
Please round the answer to a whole number. Please note: Different states might have the same city name. A city might have multiple zip codes.
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