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NEW QUESTION: 1
1) 고정 또는 결정 가능한 지불, 2 고정 된 만기, 그리고 3) 만기가 어떤 금융 상품의 범주가 될 때까지 보유 할 의지와 능력이 있는 투자 회사가 보유한 파생 금융 상품이 없습니까?
A. 공정 가치 위험 회피.
B. 거래를 위해 보유한 금융 자산 또는 부채.
C. 매도 가능 금융 자산.
D. 만기 보유 투자.
Answer: D
Explanation:
Financial instruments are classified in three categories. Held-to-maturity investments are No derivatives that have fixed or determinable payments and a fixed maturity. The entity must have a positive intent and ability to hold such investments to maturity. The other categories are financial assets or liabilities held for trading and available-for-sale financial assets.
NEW QUESTION: 2
You are using a tool that allows you to see signal strength for all APs in the area with a visual representation. It shows you SSIDs available and the security settings for each SSID. It allows you to filter by frequency band to see only 2.4 GHz networks or only 5 GHz networks. No additional features are available. What kind of application is described?
A. Spectrum analyzer
B. Protocol analyzer
C. Wireless Intrusion Protection System
D. WLAN discovery tool
E. Wireless Network Management System
F. Site survey utility
Answer: D
NEW QUESTION: 3
You are developing a solution using a Lambda architecture on Microsoft Azure.
The data at test layer must meet the following requirements:
Data storage:
*Serve as a repository (or high volumes of large files in various formats.
*Implement optimized storage for big data analytics workloads.
*Ensure that data can be organized using a hierarchical structure.
Batch processing:
*Use a managed solution for in-memory computation processing.
*Natively support Scala, Python, and R programming languages.
*Provide the ability to resize and terminate the cluster automatically.
Analytical data store:
*Support parallel processing.
*Use columnar storage.
*Support SQL-based languages.
You need to identify the correct technologies to build the Lambda architecture.
Which technologies should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Data storage: Azure Data Lake Store
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With the hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Batch processing: HD Insight Spark
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
Analytic data store: SQL Data Warehouse
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP).
SQL Data Warehouse stores data into relational tables with columnar storage.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is