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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. Your Iceberg table experiences frequent schema evolution, with new columns being added regularly. Which of the following might you need to adjust to maintain optimal performance?

A) The Iceberg table's write format (vl or v2)
B) Spark shuffle partitions (spark.sql.shuffle.partitions)
C) Iceberg metadata table pruning frequency
D) Kubernetes resource requests for Spark executors

2. What information does an "Explain Plan" typically provide in the context of SQL query optimization?

A) The cost of the query in monetary terms
B) The names of users who have executed the query
C) The sequence of operations the database will perform to execute the query
D) The expected time of query completion

3. In Spark, what is the advantage of using the 'coalesce' method over the 'repartition' method when reducing the number of partitions in an RDD?

A) 'coalesce' reduces the number of partitions without a full data shuffle, enhancing performance.
B) 'coalesce' triggers a full shuffle of the data, improving data distribution.
C) 'repartition' is incapable of reducing the number of partitions.
D) 'coalesce' can increase the number of partitions without shuffling.

4. Which technique in the Optimization Framework is primarily used to improve query performance by reducing the number of rows to be scanned in a table?

A) Indexing
B) Data replication
C) Data compaction
D) Predicate pushdown

5. In the context of caching data for reuse in Spark, how does the Tungsten project contribute to enhancing memory management and execution efficiency?

A) By enforcing strict data typing to reduce runtime type checking overhead
B) By optimizing Spark's internal memory management and data processing operations
C) By rewriting Spark operations in a lower-level language for direct memory access
D) By providing a graphical interface for memory management

Solutions: