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Databricks Coding

 

Baby Names Question 1 – Nested Data [15 Points]
Use Spark SQL’s native JSON support to read the baby names file into a dataframe. Use this dataframe to create a temporary table containing all the nested data columns (“sid”, “id”, “position”, “created_at”, “created_meta”, “updated_at”, “updated_meta”, “meta”, “year”, “first_name”, “county”, “sex”, “count”) so that they can be queried using SQL.
Hint: you can use dbutils.fs.head(baby_names_path) to take a look at the dataset before reading it in.
Suggested Steps:
1. Read in the JSON data
2. Pull all columns in the nested data column to top level, following the schema specified above. There are built-in Spark SQL functions that will accomplish this.
3. Create a temp table from this expanded dataframe using createOrReplaceTempView()
Cmd 24

1
# Please provide your code answer for Question 1 here
Command took 0.05 seconds — by a user at 1/12/2021, 5:12:00 PM on unknown cluster
Cmd 25

Please provide your brief, written description of your code here.
Cmd 26
Baby Names Question 2 – Multiple Languages [10 Points]
Using the temp table you created in the question above, write a SQL query that gives the most popular baby name for each year in the dataset. Then, write the same query using either the Scala or Python dataframe APIs.
Cmd 27

1
# Please provide your code answer for Question 2 here. You will need separate cells for your SQL answer and your Python or Scala answer.
Command took 0.04 seconds — by a user at 1/12/2021, 5:12:00 PM on unknown cluster
Cmd 28

Please provide your brief, written description of your code here.
Cmd 29
Baby Names Question 3 – Performance [10 Points]
Are there any performance considerations when choosing a language API (SQL vs Python vs Scala) in the context of Spark?
Are there any performance considerations when using different data representations (RDD, Dataframe) in Spark? Please explain, and provide references if possible. No code answer is required.
Cmd 30

Please write your written answer here.
Cmd 31
Baby Names Question 4 – Nested XML [15 Points]
Imagine that a new upstream system now automatically adds an XML field to the JSON baby dataset. The added field is called visitors. It contains an XML string with visitor information for a given birth. We have simulated this upstream system by creating another JSON file with the additional field.
Using the JSON dataset at dbfs:/interview-datasets/sa/births/births-with-visitor-data.json, do the following:
1. Read the rows-with-xml.json file into a dataframe and parse the nested XML fields into columns and print the total record count.
2. Find the county with the highest average number of visitors across all births in that county
3. Find the average visitor age for a birth in the county of KINGS
4. Find the most common birth visitor age in the county of KINGS
Cmd 32
1
visitors_path = “/interview-datasets/sa/births/births-with-visitor-data.json”
Command took 0.02 seconds — by a user at 1/26/2021, 11:31:12 AM on unknown cluster
Cmd 33

1
## Hint: the code below will read in the downloaded JSON files. However, the xml column needs to be given structure. Consider using a UDF.
2
#df = spark.read.option(“inferSchema”, True).json(visitors_path)
3

Command took 0.02 seconds — by a user at 1/12/2021, 5:12:00 PM on unknown cluster
Cmd 34

1
## Hint: check for inconsistently capitalized field values. It will make your answer incorrect.
Command took 0.02 seconds — by a user at 1/12/2021, 5:12:00 PM on unknown cluster
Cmd 35

1
## Hint: check for inconsistently capitalized field values. It will make your answer incorrect.
Command took 0.03 seconds — by a user at 1/12/2021, 5:12:00 PM on unknown cluster
Cmd 36

1
## Hint: check for inconsistently capitalized field values. It will make your answer incorrect.
Command took 0.02 seconds — by a user at 1/12/2021, 5:12:00 PM on unknown cluster
Cmd 37

Please provide your written answer for Question 4 here
Cmd 38
ML Question 1 [20 Points]
Choose a data set then demonstrate the training and testing of a Spark MLlib algorithm. You may use any dataset contained in dbfs:/databricks-datasets, or you may use a publically available dataset of your choice. However, if you choose a public data set, please ensure your code downloads the dataset from a publically available source. The grader needs to be able to run all your code. Please cite any sources/guides/blogs used.
Show and discuss an example of using hyperparameter tuning on the algorithm to improve prediction accuracy. Please describe in detail what algorithm you chose and why.
Note: Blogs and tutorials can be used to inform you in writing your answer, but if your code is copied from the blog or tutorial then your answer will be worth at most half-credit.
Cmd 39

1
# Please provide your code answer for Question 1 Here
Command took 0.03 seconds — by a user at 1/12/2021, 5:12:00 PM on unknown cluster
Cmd 40

Please provide your brief, written description of your code here
Shift+Enter to run

 

 

 

 

Sample Answer

Compelling correspondence is essential to the achievement all things considered but since of the changing idea of the present working environments, successful correspondence turns out to be more troublesome, and because of the numerous impediments that will permit beneficiaries to acknowledge the plan of the sender It is restricted. Misguided judgments.In spite of the fact that correspondence inside the association is rarely completely open, numerous straightforward arrangements can be executed to advance the effect of these hindrances.

Concerning specific contextual analysis, two significant correspondence standards, correspondence channel determination and commotion are self-evident. This course presents the standards of correspondence, the act of general correspondence, and different speculations to all the more likely comprehend the correspondence exchanges experienced in regular daily existence. The standards and practices that you learn in this course give the premise to additionally learning and correspondence.


This question has been answered

This course starts with an outline of the correspondence cycle, the method of reasoning and hypothesis. In resulting modules of the course, we will look at explicit use of relational connections in close to home and expert life. These incorporate relational correspondence, bunch correspondence and dynamic, authoritative correspondence in the work environment or relational correspondence. Rule of Business Communication In request to make correspondence viable, it is important to follow a few rules and standards. Seven of them are fundamental and applicable, and these are clear, finished, brief, obliging, right, thought to be, concrete. These standards are frequently called 7C for business correspondence. The subtleties of these correspondence standards are examined underneath: Politeness Principle: When conveying, we should build up a cordial relationship with every individual who sends data to us.

To be inviting and polite is indistinguishable, and politeness requires an insightful and amicable activity against others. Axioms are notable that gracious “pay of graciousness is the main thing to win everything”. Correspondence staff ought to consistently remember this. The accompanying standards may assist with improving courtesy:Preliminary considering correspondence with family All glad families have the mystery of progress. This achievement originates from a strong establishment of closeness and closeness. Indeed, through private correspondence these cozy family connections become all the more intently. Correspondence is the foundation of different affiliations, building solid partners of obedient devotion, improving family way of life, and assisting with accomplishing satisfaction (Gosche, p. 1). In any case, so as to keep up an amicable relationship, a few families experienced tumultuous encounters. Correspondence in the family is an intricate and alluring marvel. Correspondence between families isn’t restricted to single messages between families or verbal correspondence.

It is a unique cycle that oversees force, closeness and limits, cohesiveness and flexibility of route frameworks, and makes pictures, topics, stories, ceremonies, rules, jobs, making implications, making a feeling of family life An intelligent cycle that makes a model. This model has passed ages. Notwithstanding the view as a family and family automatic framework, one of the greatest exploration establishments in between family correspondence centers around a family correspondence model. Family correspondence model (FCP) hypothesis clarifies why families impart in their own specific manner dependent on one another ‘s psychological direction. Early FCP research established in media research is keen on how families handle broad communications data. Family correspondence was perceived as an exceptional scholastic exploration field by the National Communications Association in 1989. Family correspondence researchers were at first impacted by family research, social brain science, and relational hypothesis, before long built up the hypothesis and began research in a family framework zeroed in on a significant job. Until 2001, the primary issue of the Family Communication Research Journal, Family Communication Magazine, was given. Family correspondence is more than the field of correspondence analysts in the family. Examination on family correspondence is normally done by individuals in brain science, humanism, and family research, to give some examples models. However, as the popular family correspondence researcher Leslie Baxter stated, it is the focal point of this intelligent semantic creation measure making the grant of family correspondence special. In the field of in-home correspondence, correspondence is normally not founded on autonomous messages from one sender to one beneficiary, yet dependent on the dynamic interdependency of data shared among families It is conceptualized. The focal point of this methodology is on the shared trait of semantic development inside family frameworks. As such, producing doesn’t happen in vacuum, however it happens in a wide scope of ages and social exchange.

Standards are rules end up being followed when performing work to agree to a given objective. Hierarchical achievement relies significantly upon compelling correspondence. So as to successfully impart, it is important to follow a few standards and rules. Coming up next are rules to guarantee powerful correspondence: clearness: lucidity of data is a significant guideline of correspondence. For beneficiaries to know the message plainly, the messages ought to be sorted out in a basic language. To guarantee that beneficiaries can without much of a stretch comprehend the importance of the message, the sender needs to impart unmistakably and unhesitatingly so the beneficiary can plainly and unquestionably comprehend the data.>

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