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NEW QUESTION: 1
外部調達に必須の組織の割り当てはどれですか?
正解をお選びください。
応答:
A. 参照購買組織-購買組織
B. 会社コード-購買組織
C. プラント-購買グループ
D. プラント-購買組織
Answer: D

NEW QUESTION: 2

A. Option C
B. Option B
C. Option A
D. Option D
Answer: A
Explanation:
Starting with the Oracle Solaris 11 Express release, Fast Reboot is supported on the SPARC platform, as well as the x86 platform. On both platforms, this feature is controlled by the SMF and implemented through a boot configuration service, svc:/system/boot- config. The boot-config service provides a means for setting or changing the default boot configuration parameters.
The fastreboot_default property of the boot-config service enables an automatic fast reboot of the system when either the reboot or the init 6 command is used. When the config/fastreboot_default property is set to true the system automatically performs a fast reboot, without the need to use the reboot -f command. By default, this property's value is set to false on the SPARC platform and to true on the x86 platform.

NEW QUESTION: 3
How does Rational Application Developer increase developer productivity?
A. It implements innovative task control to ensure timely responses.
B. It automatically generates code from the design model.
C. It serves as a central library to automate reuse of existing designs.
D. It eliminates mundane tasks to allow developers to be innovative.
Answer: D

NEW QUESTION: 4
You need to develop a pipeline for processing data. The pipeline must meet the following requirements.
*Scale up and down resources for cost reduction.
*Use an in-memory data processing engine to speed up ETL and machine learning operations.
*Use streaming capabilities.
*Provide the ability to code in SQL, Python, Scala, and R.
*Integrate workspace collaboration with Git.
What should you use?
A. Azure Stream Analytics
B. HDInsight Spark Cluster
C. HDInsight Hadoop Cluster
D. Azure SQL Data Warehouse
Answer: B
Explanation:
Explanation
Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
Languages: R, Python, Java, Scala, SQL
You can create an HDInsight Spark cluster using an Azure Resource Manager template. The template can be found in GitHub.
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing