Exam DP-203 topic 2 question 21 discussion

I think the correct order is: 1) mount onto DBFS 2) read into data frame 3) transform data frame 4) specify temporary folder 5) write to table in SQL data warehouse About temporary folder, there is a note explain this: https://docs.microsoft.com/en-us/azure/databricks/scenarios/databricks-extract-load-sql-data-warehouse#load-data-into-azure-synapse Discussions about this question: https://www.examtopics.com/discussions/microsoft/view/11653-exam-dp-200-topic-2-question-30-discussion/

1) mount the data onto DBFS 2) Read the file into a data frame 3) Perform transformations on the file 4) Specify a temporary folder to stage the data 5) Write the results to a table in Azure synapse

Answer are correct, chatgpt say : To accomplish the task in an Azure Databricks notebook, the logical sequence of actions would be: 1. **Mount the Data Lake Storage onto DBFS**: This allows access to the JSON file stored in Azure Data Lake Storage using the Databricks File System. 2. **Read the file into a data frame**: Use Spark to read the JSON file into a DataFrame for processing. 3. **Perform transformations on the data frame**: Apply transformations to concatenate the FirstName and LastName fields to create a new column. 4. **Specify a temporary folder to stage the data**: Before writing the data to Azure Synapse, it is a common practice to stage it in a temporary folder. 5. **Write the results to a table in Azure Synapse**: Finally, write the transformed DataFrame to the destination table in Azure Synapse Analytics. These steps would ensure the JSON file data is properly transformed and loaded into Azure Synapse Analytics for further use.

Just remember the initials first: M.R.P.S.W then go to the details.

1. Mount the data lake storage onto DBFS. 2. Read the file into a data frame. 3. Perform transformations on the data frame. 4. Specify a temporary folder to stage the data. 5. Write the results to a table in Azure Synapse. This will allow you to read the data from the JSON file into a data frame, perform the necessary transformations to concatenate the FirstName and LastName values, and then write the results to a table in Azure Synapse.

answer is correct, explained by the reference link in the given solution

I don not see the reason why "specify temporary folder" can not be both before or after the "read and transformation phase"

given answer is correct, after reading and rereading stand with the given answer

I think the correct order is: 1) mount onto DBFS 2) read into data frame 3) transform data frame 4) specify temporary folder 5) write to table in SQL data warehouse

Here is my answer. 1) Create a service principal - Not sure why this step is not a choice in this question. I don't thing need to mount onto DBFS, but you do need to assign permission to allow databricks talk with Data Lake and read file. 2) Read the file into data frame 3) Perform transformations on the data frame Data have been read into data from, so should transform data from data frame, not data file. 4) Specify temporary folder to stage the data 5) Write the results to a table in Azure Synapse I reviewed this online document. No any place mentioned that the data frame needs to be dropped. https://docs.microsoft.com/en-us/azure/databricks/scenarios/databricks-extract-load-sql-data-warehouse

There Is A Contradiction Between Answers On The Drag & Drop And The Answers In The Steps Listing, And I Think The Correct Ones Are That In The Listing And Not The Drag & Drop.

1) Mount the data onto DBFS 2) Read the file into a data frame 3) Perform transformations 4) Specify a temporary folder to stage the data 5) Write the results to a table in Azure synapse

The given answer is correct, after read the link provided carefully several times. There's already a service principal. With that, it's no need to mount. You do need to drop the dataframe as the last step.

Correct solution: Read the file into a data frame Perform transformations on the file Specify a temporary folder to stage the data Write the results to a table in Azure synapse Drop the data frame