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NEW QUESTION: 1
Why are early adopters considered as opinion leaders?
A. They are instrumental in bringing other buyer categories to the market.
B. They do not give up on products easily and use a particular version until it is not in production.
C. They wait until a product is at its lowest price and influence others to make bulk purchases.
D. They purchase enough products for the overall price to fall below a certain level and pave the entry for the late majority.
E. They read reviews of critics before buying a product.
Answer: A
NEW QUESTION: 2
다음 중 Monte Carlo 프로세스를 사용하는 시뮬레이션 관련 모델에 해당하지 않는 것은 무엇입니까?
A. 실제 성능을 수학적으로 추정합니다.
B. 샘플링이 필요할 수 있습니다.
C. 확률 론적 시스템을 모방한다.
D. 본질적으로 결정 론적입니다.
Answer: D
Explanation:
The Monte Carlo simulation is often used in computer modeling to generate the individual values for a random variable. The performance of a quantitative model under uncertainty may be investigated by randomly selecting values for each variable in the model (based on the probability distribution of each variable) and then calculating the value of the solution. Because Monte Carlo processes use the laws of probability to generate values for random variables, simulations using them are probabilistic, not deterministic.
NEW QUESTION: 3
Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You are implementing a batch processing solution by using Azure HDInsight.
You have two tables. Each table is larger than 250 TB. Both tables have approximately the same number of rows and columns.
You need to match the tables based on a key column. You must minimize the size of the data table that is produced.
What should you do?
A. Increase the number of spark.executor.cores in an Apache Spark job that stores the data in a text format.
B. Use an Azure Data Factory linked service that stores the data in Azure Data Lake.
C. Use a shuffle join in an Apache Hive query that stores the data in a JSON format.
D. Use an Azure Data Factory linked service that stores the data in an Azure DocumentDB database.
E. Decrease the level of parallelism in an Apache Spark job that stores the data in a text format.
F. Increase the number of spark.executor.instances in an Apache Spark job that stores the data in a text format.
G. Use an action in an Apache Oozie workflow that stores the data in a text format.
H. Use a broadcast join in an Apache Hive query that stores the data in an ORC format.
Answer: C
Explanation:
References: http://www.openkb.info/2014/11/understanding-hive-joins-in-explain.html