Exam DP-203 topic 1 question 37 discussion

Another way to think about this: The number of records for the period stated = 2.4 billion Number of underlying ("automatic") distributions: 60 2.4 billion / 60 distributions = 40 million rows 40 million / 40 partitions = 1 million rows As stated, 1 million rows per distribution are optimal for compression and performance. Divide the 40 million rows with the other partitioning options and you have too few rows per distribution -> suboptimal.

Thank you for your comment. I do not agree. Your logic conflates rowgroups with table partitions. You don't define partitions specifically for each distribution. The 60 distributions operate automatically, regardless of how many partitions you define.Table partitions are logical divisions, and Azure Synapse automatically handles the data distribution within each partition across its 60 distributions. If you only define 40 partitions, each partition would hold 2.4 billion ÷ 40 = 60 million rows.2.4 billion ÷ 40 = 60 million rows. This would make partitions very large and reduce the effectiveness of partition elimination, especially for date-based queries. 240 partitions aligns better with the guideline of 1–10 million rows per partition, allowing better granularity and performance for large-scale data.

1 partion : 60M = x : 2.4 B 1 partion : 60 M = x : 2400 M ==> x = 2400 / 60 ==> x = 40 partitions