Snowflake - Build and Architect Data Pipelines Using AWS - Understanding Clustering Depth and Cluster Overlap

The video tutorial explains the concepts of clustering depth and overlapping in Snowflake. It covers how micro partitions are created and how their overlapping affects clustering. The tutorial discusses scenarios of reclustering, the significance of average depth and overlaps, and how to interpret partition depth histograms. It emphasizes that a lower average depth indicates better clustering and provides practical examples to illustrate these concepts.

What is the initial overlap percentage when a table is first clustered in Snowflake?

• 50%

• 25%

• 75%

• 100%

How many micro partitions are created when a table is reclustered with new data?

• 4

• 3

• 5

• 2

What happens to the overlapping depth when micro partitions overlap partially?

• It becomes zero

• It increases

• It remains the same

• It decreases

What does a high average overlapping depth indicate about a table's clustering?

• The table has no partitions

• The table is not well clustered

• The table is empty

• The table is well clustered

What is the minimum value for average overlapping depth?

• 3

• 1

• 2

• 0

What does the partition depth histogram depict?

• The distribution of overlap depth

• The number of tables

• The size of the database

• The number of users

If most micro partitions have a low average depth, what does it indicate?

• The table has no data

• The table is empty

• The table is well clustered

• The table is poorly clustered