Which number of partition ranges provides optimal compression and performance of the clustered column store index?

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 ProduclID,

• Contain 2.4 billion records for the years 20l9 and 2020.

Which number of partition ranges provides optimal compression and performance of the clustered column store index?
A . 40
B. 240
C. 400
D. 2,400

Answer: 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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