Cloudera CDP Data Engineer - Certification 認定 CDP-3002 試験問題:
1. You've discovered that a production Iceberg table has several corrupted data files. Which of the following actions could help address this issue?
A) Run the VACUUM procedure on the Iceberg table.
B) Restore the table to a previous snapshot using Iceberg's time travel feature.
C) Apply Iceberg's REMOVE ORPHAN FILES procedure.
D) Drop and recreate the Iceberg table from scratch.
2. In Spark, when is it most beneficial to use the repartitionByRange method?
A) When decreasing the number of partitions to reduce task scheduling overhead.
B) When sorting data within each partition by a specified column or set of columns is required.
C) When minimizing network traffic during shuffle operations is the primary concern.
D) When the data is highly skewed and a uniform distribution of data across partitions is required.
3. Consider the following code snippet:# Sample DataFrame (assuming it exists) df = spark.createDataFrame(...)
# Attempt to explode a nested array column (fix the error)
df_exploded = df.withColumn("items", F.explode(df["items"]))
df_exploded.show()
What is the error in this code, and how can it be fixed?
A) There is no error in the code snippet.
B) The error is missing parentheses around the column name in the explode function. Fix: F.explode(df("items"))
C) The error is attempting to modify the original DataFrame in-place. Fix: Use a separate variable to store the exploded DataFrame.
D) The error is using withColumn instead of a dedicated method for exploding arrays. Fix: Use df.withColumnExploded. (This function doesn't exist in Spark)
4. When creating a data pipeline in the Cloudera Data Engineering service, what is the primary file format used to define the pipeline steps and configuration?
A) Shell script
B) YAML
C) Python script
D) JSON
5. Which strategy is most effective for managing schema evolution in a big data application that relies on schema inference?
A) Completely disabling schema inference and relying on static schemas
B) Integrating schema registry services that track and manage schema versions
C) Using a single version of the schema for all data, regardless of changes
D) Manually updating the inferred schema for each data ingestion
質問と回答：
| 質問 # 1 正解： C | 質問 # 2 正解： B | 質問 # 3 正解： C | 質問 # 4 正解： B | 質問 # 5 正解： B |
1286 お客様のコメント
品質保証JPexamはIT認定試験のシラバスに従って、試験問題の範囲を正確に絞って、的中率が99％の最新問題集を捧げます。
1年間の無料更新サービスJPexamは1年以内に問題集の無料更新サービスを提供し、お客様がいつでも最新版の問題集を持つことを保証いたします。もし試験の内容が変更されたら、弊社は直ちにお客様にお知らせします。それに、弊社の問題集が更新されたら、早速メールで最新バージョンを送付いたします。
全額返金JPexamの問題集を利用すると、短時間で勉強しても試験に合格できるのを保証いたします。試験に不合格になってしまった場合、弊社は全額返金いたします。(
ご購入前のお試しJPexamは問題集のサンプルを無料で提供いたします。ご購入前にサンプルを試用して製品の品質を確認することができます。ご遠慮なく利用してください。
