Online Access Free HP2-N36 Practice Test

What are the benefits of ordenng data in projection design? (Select two.)

• A.It enables partitioning of data.
• B., It enables efficient application of query predicates.
• C.It enables segmentation of data.
• D.It enables optimum encoding.
• E.It enables efficient sharing of data between similarly-ordered projections.

What are characteristics of projections in Vertica? (Select three.)

• A.A projection can contain data from only one source table.
• B.A projection can contain a subset of rows from the source table.
• C.A projection can contain data from one or more source tables.
• D.Each projection contains all rows from the source table.
• E.Each projection contains all columns from the source table.
• F.A projection can contain a subset of columns from the source table.

Which methods are available to optimize a projection for delete processing? (Select two.)

• A.Add a low cardinality column to the end of all projections on the source table.
• B.Add a high cardinality column to the end of all projections on the source table.
• C.Add a high cardinality column to the beginning of all projections on the source table.
• D.Add a low cardinality column to the beginning of all projections on the source table.
• E.Add all columns used as delete predicates to all projections on the source table.

What is a buddy projection?

• A.a projection that contains a subset of rows from the original projection, stored in different files on a neighboring node of the original
• B.a projection that contains a subset of rows from the original projection, stored in different files on the same node as the original
• C.a projection that contains the same columns and has the same segmentation as the original projection, using different node ordering, stored in different files on a different node than the original
• D.a projection that contains the same columns and has the same segmentation as the original projection, using different node ordering, stored in different files on the same node as the original

How are records marked for deletion?

• A.Vertica deletes the records from the original source files.
• B.Vertica removes the file that stores the deleted data.
• C.Vertica creates a delete vector, Identifying records to be deleted.
• D.Vertica rewrites the files that contained the deleted records, ignoring records to be deleted.