Which of the following is true of Delta Lake and the Lakehouse?

Which of the following is true of Delta Lake and the Lakehouse?
A . Because Parquet compresses data row by row. strings will only be compressed when a character is repeated multiple times.
B . Delta Lake automatically collects statistics on the first 32 columns of each table which are leveraged in data skipping based on query filters.
C . Views in the Lakehouse maintain a valid cache of the most recent versions of source tables at all times.
D . Primary and foreign key constraints can be leveraged to ensure duplicate values are never entered into a dimension table.
E . Z-order can only be applied to numeric values stored in Delta Lake tables

Answer: B

Explanation:

https://docs.delta.io/2.0.0/table-properties.html

Delta Lake automatically collects statistics on the first 32 columns of each table, which are leveraged in data skipping based on query filters1. Data skipping is a performance optimization technique that aims to avoid reading irrelevant data from the storage layer1. By collecting statistics such as min/max values, null counts, and bloom filters, Delta Lake can efficiently prune unnecessary files or partitions from the query plan1. This can significantly improve the query performance and reduce the I/O cost. The other options are false because:

Parquet compresses data column by column, not row by row2. This allows for better compression ratios, especially for repeated or similar values within a column2.

Views in the Lakehouse do not maintain a valid cache of the most recent versions of source tables at

all times3. Views are logical constructs that are defined by a SQL query on one or more base tables3. Views are not materialized by default, which means they do not store any data, but only the query definition3. Therefore, views always reflect the latest state of the source tables when queried3. However, views can be cached manually using the CACHE TABLE or CREATE TABLE AS SELECT commands.

Primary and foreign key constraints can not be leveraged to ensure duplicate values are never entered into a dimension table. Delta Lake does not support enforcing primary and foreign key constraints on tables. Constraints are logical rules that define the integrity and validity of the data in a table. Delta Lake relies on the application logic or the user to ensure the data quality and consistency.

Z-order can be applied to any values stored in Delta Lake tables, not only numeric values. Z-order is a technique to optimize the layout of the data files by sorting them on one or more columns. Z-order can improve the query performance by clustering related values together and enabling more efficient data skipping. Z-order can be applied to any column that has a defined ordering, such as numeric, string, date, or boolean values.

Reference: Data Skipping, Parquet Format, Views, [Caching], [Constraints], [Z-Ordering]