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Free DP-203 Exam Braindumps (page: 12)

Page 11 of 94
PDF with 397 Questions

You are designing a slowly changing dimension (SCD) for supplier data in an Azure Synapse Analytics dedicated SQL pool.

You plan to keep a record of changes to the available fields.
The supplier data contains the following columns.


Which three additional columns should you add to the data to create a Type 2 SCD? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

  1. surrogate primary key
  2. effective start date
  3. business key
  4. last modified date
  5. effective end date
  6. foreign key

Answer(s): A,B,E



HOTSPOT (Drag and Drop is not supported)
You have a Microsoft SQL Server database that uses a third normal form schema.
You plan to migrate the data in the database to a star schema in an Azure Synapse Analytics dedicated SQL pool.
You need to design the dimension tables. The solution must optimize read operations.

What should you include in the solution? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: Denormalize to a second normal form
Denormalization is the process of transforming higher normal forms to lower normal forms via storing the join of higher normal form relations as a base relation. Denormalization increases the performance in data retrieval at cost of bringing update anomalies to a database.

Box 2: New identity columns
The collapsing relations strategy can be used in this step to collapse classification entities into component entities to obtain flat dimension tables with single-part keys that connect directly to the fact table. The singlepart key is a surrogate key generated to ensure it remains unique over time.
Example:


Note: A surrogate key on a table is a column with a unique identifier for each row. The key is not generated from the table data. Data modelers like to create surrogate keys on their tables when they design data warehouse models. You can use the IDENTITY property to achieve this goal simply and effectively without affecting load performance.


Reference:

https://www.mssqltips.com/sqlservertip/5614/explore-the-role-of-normal-forms-in-dimensional-modeling/ https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tablesidentity



HOTSPOT (Drag and Drop is not supported)
You plan to develop a dataset named Purchases by using Azure Databricks. Purchases will contain the following columns:
-ProductID
-ItemPrice
-LineTotal
-Quantity
-StoreID
-Minute
-Month
-Hour
-Year
-Day
You need to store the data to support hourly incremental load pipelines that will vary for each Store ID. The solution must minimize storage costs.

How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: partitionBy
We should overwrite at the partition level.

Example:
df.write.partitionBy("y","m","d")
.mode(SaveMode.Append)
.parquet("/data/hive/warehouse/db_name.db/" + tableName)

Box 2: ("StoreID", "Year", "Month", "Day", "Hour", "StoreID")

Box 3: parquet("/Purchases")


Reference:

https://intellipaat.com/community/11744/how-to-partition-and-write-dataframe-in-spark-without-deletingpartitions-with-no-new-data



You are designing a partition strategy for a fact table in an Azure Synapse Analytics dedicated SQL pool. The table has the following specifications:
-Contain sales data for 20,000 products.
-Use hash distribution on a column named ProductID.
-Contain 2.4 billion records for the years 2019 and 2020.

Which number of partition ranges provides optimal compression and performance for the clustered columnstore index?

  1. 40
  2. 240
  3. 400
  4. 2,400

Answer(s): A

Explanation:

Each partition should have around 1 millions records. Dedication SQL pools already have 60 partitions. We have the formula: Records/(Partitions*60)= 1 million
Partitions= Records/(1 million * 60)
Partitions= 2.4 x 1,000,000,000/(1,000,000 * 60) = 40

Note: Having too many partitions can reduce the effectiveness of clustered columnstore indexes if each partition has fewer than 1 million rows. Dedicated SQL pools automatically partition your data into 60 databases. So, if you create a table with 100 partitions, the result will be 6000 partitions.


Reference:

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/best-practices-dedicated-sql-pool






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