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Free DP-203 Exam Braindumps (page: 34)

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PDF with 397 Questions

You have an Azure Data Factory instance that contains two pipelines named Pipeline1 and Pipeline2. Pipeline1 has the activities shown in the following exhibit.


Pipeline2 has the activities shown in the following exhibit.


You execute Pipeline2, and Stored procedure1 in Pipeline1 fails. What is the status of the pipeline runs?

  1. Pipeline1 and Pipeline2 succeeded.
  2. Pipeline1 and Pipeline2 failed.
  3. Pipeline1 succeeded and Pipeline2 failed.
  4. Pipeline1 failed and Pipeline2 succeeded.

Answer(s): A

Explanation:

Activities are linked together via dependencies. A dependency has a condition of one of the following: Succeeded, Failed, Skipped, or Completed.

Consider Pipeline1:
If we have a pipeline with two activities where Activity2 has a failure dependency on Activity1, the pipeline will not fail just because Activity1 failed. If Activity1 fails and Activity2 succeeds, the pipeline will succeed. This scenario is treated as a try-catch block by Data Factory.


The failure dependency means this pipeline reports success.

Note:
If we have a pipeline containing Activity1 and Activity2, and Activity2 has a success dependency on Activity1, it will only execute if Activity1 is successful. In this scenario, if Activity1 fails, the pipeline will fail.


Reference:

https://datasavvy.me/category/azure-data-factory/



HOTSPOT (Drag and Drop is not supported)
A company plans to use Platform-as-a-Service (PaaS) to create the new data pipeline process. The process must meet the following requirements:

Ingest:
-Access multiple data sources.
-Provide the ability to orchestrate workflow.
-Provide the capability to run SQL Server Integration Services packages.

Store:
-Optimize storage for big data workloads.
-Provide encryption of data at rest.
-Operate with no size limits.

Prepare and Train:
-Provide a fully-managed and interactive workspace for exploration and visualization.
-Provide the ability to program in R, SQL, Python, Scala, and Java.
-Provide seamless user authentication with Azure Active Directory.

Model & Serve:
-Implement native columnar storage.
-Support for the SQL language
-Provide support for structured streaming.

You need to build the data integration pipeline.

Which technologies should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Ingest: Azure Data Factory
Azure Data Factory pipelines can execute SSIS packages.
In Azure, the following services and tools will meet the core requirements for pipeline orchestration, control flow, and data movement: Azure Data Factory, Oozie on HDInsight, and SQL Server Integration Services (SSIS).

Store: Data Lake Storage
Data Lake Storage Gen1 provides unlimited storage.

Note: Data at rest includes information that resides in persistent storage on physical media, in any digital format. Microsoft Azure offers a variety of data storage solutions to meet different needs, including file, disk, blob, and table storage. Microsoft also provides encryption to protect Azure SQL Database, Azure Cosmos DB, and Azure Data Lake.

Prepare and Train: Azure Databricks
Azure Databricks provides enterprise-grade Azure security, including Azure Active Directory integration.
With Azure Databricks, you can set up your Apache Spark environment in minutes, autoscale and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch and scikit-learn.

Model and Serve: Azure Synapse Analytics
Azure Synapse Analytics/ SQL Data Warehouse stores data into relational tables with columnar storage.
Azure SQL Data Warehouse connector now offers efficient and scalable structured streaming write support for SQL Data Warehouse. Access SQL Data Warehouse from Azure Databricks using the SQL Data Warehouse connector.
Note: Note: As of November 2019, Azure SQL Data Warehouse is now Azure Synapse Analytics.


Reference:

https://docs.microsoft.com/bs-latn-ba/azure/architecture/data-guide/technology-choices/pipeline-orchestration-data-movement
https://docs.microsoft.com/en-us/azure/azure-databricks/what-is-azure-databricks



DRAG DROP (Drag and Drop is not supported)
You have the following table named Employees.


You need to calculate the employee_type value based on the hire_date value.

How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.
Select and Place:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: CASE
CASE evaluates a list of conditions and returns one of multiple possible result expressions.

CASE can be used in any statement or clause that allows a valid expression. For example, you can use CASE in statements such as SELECT, UPDATE, DELETE and SET, and in clauses such as select_list, IN, WHERE, ORDER BY, and HAVING.

Syntax: Simple CASE expression:
CASE input_expression
WHEN when_expression THEN result_expression [ ...n ]
[ ELSE else_result_expression ]
END

Box 2: ELSE


Reference:

https://docs.microsoft.com/en-us/sql/t-sql/language-elements/case-transact-sql



DRAG DROP (Drag and Drop is not supported)
You have an Azure Synapse Analytics workspace named WS1.

You have an Azure Data Lake Storage Gen2 container that contains JSON-formatted files in the following format.

You need to use the serverless SQL pool in WS1 to read the files.

How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.
Select and Place:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: openrowset
The easiest way to see to the content of your CSV file is to provide file URL to OPENROWSET function, specify csv FORMAT.

Example:
SELECT *
FROM OPENROWSET(
BULK 'csv/population/population.csv',
DATA_SOURCE = 'SqlOnDemandDemo',
FORMAT = 'CSV', PARSER_VERSION = '2.0',
FIELDTERMINATOR =',',
ROWTERMINATOR = '\n'

Box 2: openjson
You can access your JSON files from the Azure File Storage share by using the mapped drive, as shown in the following example:

SELECT book.* FROM
OPENROWSET(BULK N't:\books\books.json', SINGLE_CLOB) AS json
CROSS APPLY OPENJSON(BulkColumn)
WITH( id nvarchar(100), name nvarchar(100), price float,
pages_i int, author nvarchar(100)) AS book


Reference:

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/query-single-csv-file
https://docs.microsoft.com/en-us/sql/relational-databases/json/import-json-documents-into-sql-server






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