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NEW QUESTION: 1
Which of the following are the characteristics of supplier evaluation in SAP S/4HANA?
There are 2 correct answers to this question. Response:
A. Usage of hard facts and soft facts
B. Sending questionnaires to suppliers
C. Configurable questionnaires
D. Integration with Dun & Bradstreet
Answer: B,C

NEW QUESTION: 2
You are the DBA supporting an Oracle 11g Release 2 database and wish to move a table containing several DATE, CHAR, VARCHAR2, and NUMBER data types, and the table's indexes, to another tablespace.
The table does not have a primary key and is used by an OLTP application.
Which technique will move the table and indexes while maintaining the highest level of availability to the application?
A. Oracle Data Pump.
B. Online Table Redefinition.
C. An ALTER TABLE MOVE to move the table and ALTER INDEX REBUILD to move the indexes.
D. Edition-Based Table Redefinition.
E. An ALTER TABLE MOVE to move the table and ALTER INDEX REBUILD ONLINE to movethe indexes.
Answer: B
Explanation:
* Oracle Database provides a mechanism to make table structure modifications without significantly affecting the availability of the table. The mechanism is called online table redefinition. Redefining tables online provides a substantial increase in availability compared to traditional methods of redefining tables.
* To redefine a table online:
Choose the redefinition method: by key or by rowid
* By key-Select a primary key or pseudo-primary key to use for the redefinition. Pseudo- primary keys are unique keys with all component columns having NOT NULL constraints.
For this method, the versions of the tables before and after redefinition should have thesame primary key columns. This is the preferred and default method of redefinition.
* By rowid-Use this method if no key is available. In this method, a hidden column named
M_ROW$$ is added to the post-redefined version of the table. It is recommended that this column be dropped or marked as unused after the redefinition is complete. If
COMPATIBLE is set to 10.2.0 or higher, the final phase of redefinition automatically sets this column unused. You can then use the ALTER TABLE ... DROP UNUSED COLUMNS statement to drop it.
You cannot use this method on index-organized tables.
Note:
* When you rebuild an index, you use an existing index as the data source. Creating an index in this manner enables you to change storage characteristics or move to a newtablespace. Rebuilding an index based on an existing data source removes intra-block fragmentation. Compared to dropping the index and using the CREATE INDEX statement, re-creating an existing index offers better performance.
Incorrect:
Not E: Edition-based redefinition enables you to upgrade the database component of an application while it is in use, thereby minimizing or eliminating down time.

NEW QUESTION: 3

クラウドウォッチがジョブリクエスト（キューに入れられたメッセージ）とAuto Scalingグループの数を監視するバッチプロセッサとして使用されるEC2インスタンス間にメッセージキューを設定するために、Simple Queue Service（SQS）を使用するバッチ処理ソリューションの上記のアーキテクチャ図を参照してくださいCloud Watchアラームで設定されたパラメーターに基づいて、バッチサーバーを自動的に追加または削除します。
このアーキテクチャを使用して、次の機能のどれを費用対効果の高い効率的な方法で実装できますか？
A. 優先度メタデータフィールドをSQSメッセージに割り当てることにより、優先度の低いジョブの前に優先度の高いジョブを処理します。
B. SQSを介してメッセージを交換することにより、バッチ内のEC2インスタンス間でメッセージの受け渡しを実装します。
C. メッセージを受信するビジーなEC2インスタンスがデイジーチェーン設定で次のインスタンスにメッセージを渡すことを許可することにより、並列処理によるジョブ実行の全体的な時間を短縮します。
D. EC2インスタンスの数とジョブ要求の数を自動的に調整するため、費用対効果が向上します。
E. EC2インスタンスの障害に対するフォールトトレランスを実装します。メッセージはSQSに残り、EC2インスタンスの回復を続行できるため、メッセージをS3にバックアップすることでSQS障害に対するフォールトトレランスを実装できます。
Answer: D
Explanation:
Explanation
There are cases where a large number of batch jobs may need processing, and where the jobs may need to be re-prioritized.
For example, one such case is one where there are differences between different levels of services for unpaid users versus subscriber users (such as the time until publication) in services enabling, for example, presentation files to be uploaded for publication from a web browser. When the user uploads a presentation file, the conversion processes, for example, for publication are performed as batch processes on the system side, and the file is published after the conversion. Is it then necessary to be able to assign the level of priority to the batch processes for each type of subscriber?
Explanation of the Cloud Solution/Pattern
A queue is used in controlling batch jobs. The queue need only be provided with priority numbers. Job requests are controlled by the queue, and the job requests in the queue are processed by a batch server. In Cloud computing, a highly reliable queue is provided as a service, which you can use to structure a highly reliable batch system with ease. You may prepare multiple queues depending on priority levels, with job requests put into the queues depending on their priority levels, to apply prioritization to batch processes. The performance (number) of batch servers corresponding to a queue must be in accordance with the priority level thereof.
Implementation
In AWS, the queue service is the Simple Queue Service (SQS). Multiple SQS queues may be prepared to prepare queues for individual priority levels (with a priority queue and a secondary queue). Moreover, you may also use the message Delayed Send function to delay process execution.
Use SQS to prepare multiple queues for the individual priority levels.
Place those processes to be executed immediately (job requests) in the high priority queue.
Prepare numbers of batch servers, for processing the job requests of the queues, depending on the priority levels.
Queues have a message "Delayed Send" function. You can use this to delay the time for starting a process.
Configuration

Benefits
You can increase or decrease the number of servers for processing jobs to change automatically the processing speeds of the priority queues and secondary queues.
You can handle performance and service requirements through merely increasing or decreasing the number of EC2 instances used in job processing.
Even if an EC2 were to fail, the messages (jobs) would remain in the queue service, enabling processing to be continued immediately upon recovery of the EC2 instance, producing a system that is robust to failure.
Cautions
Depending on the balance between the number of EC2 instances for performing the processes and the number of messages that are queued, there may be cases where processing in the secondary queue may be completed first, so you need to monitor the processing speeds in the primary queue and the secondary queue.

NEW QUESTION: 4
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You are planning a big data infrastructure by using an Apache Spark cluster in Azure HDInsight. The cluster has 24 processor cores and 512 GB of memory.
The architecture of the infrastructure is shown in the exhibit. (Click the Exhibit button.)

The architecture will be used by the following users:
Support analysts who run applications that will use REST to submit Spark jobs.

Business analysts who use JDBC and ODBC client applications from a real-time view. The business

analysts run monitoring queries to access aggregate results for 15 minutes. The results will be referenced by subsequent queries.
Data analysts who publish notebooks drawn from batch layer, serving layer, and speed layer queries.

All of the notebooks must support native interpreters for data sources that are batch processed. The serving layer queries are written in Apache Hive and must support multiple sessions. Unique GUIDs are used across the data sources, which allow the data analysts to use Spark SQL.
The data sources in the batch layer share a common storage container. The following data sources are used:
Hive for sales data

Apache HBase for operations data

HBase for logistics data by using a single region server

You need to ensure that the support analysts can develop embedded analytics applications by using the least amount of development effort.
Which technology should you implement?
A. Apache Ambari
B. Jupyter
C. Livy
D. Zeppelin
Answer: C
Explanation:
Explanation/Reference:
Explanation:
References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-apache-spark-livy-rest-interface