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NEW QUESTION: 1
Sie haben eine Datenbankanwendung, die Microsoft SQL Server 2012 verwendet. Sie haben eine Abfrage mit dem Namen Query1, die vier Spalten aus einer häufig aktualisierten Tabelle mit einem Clustered-Index zurückgibt. In der WHERE-Klausel der Abfrage wird auf drei der Spalten verwiesen. Die drei Spalten sind Teil eines nicht gruppierten Index. Auf die vierte Spalte wird in der WHERE-Klausel nicht verwiesen.
Benutzer berichten, dass die Anwendung langsam ausgeführt wird. Sie stellen fest, dass die Hauptursache für das Leistungsproblem Abfrage1 ist.
Sie müssen die Anweisung optimieren.
Was tun?
A. Fügen Sie eine Anweisung SET TRANSACTION ISOLATION LEVEL REPEATABLE READ ein, bevor Sie die Abfrage ausführen.
B. Fügen Sie der Abfrage einen HASH-Hinweis hinzu.
C. Fügen Sie eine SET STATISTICS SHOWPLAN_XML ON-Anweisung ein, bevor Sie die Abfrage ausführen.
D. Fügen Sie eine Anweisung SET TRANSACTION ISOLATION LEVEL SERIALIZABLE ein, bevor Sie die Abfrage ausführen.
E. Decken Sie den eindeutigen Clustered-Index mit einem Columnstore-Index ab.
F. Fügen Sie der Abfrage einen FORCESEEK-Hinweis hinzu.
G. Fügen Sie eine SET STATISTICS PROFILE ON-Anweisung ein, bevor Sie die Abfrage ausführen.
H. Fügen Sie dem Index eine INCLUDE-Klausel hinzu.
I. Aktivieren Sie die Option zur Optimierung für Ad-hoc-Workloads.
J. Fügen Sie der Attach-Abfrage einen FORCESCAN-Hinweis hinzu.
K. Fügen Sie eine Anweisung SET TRANSACTION ISOLATION LEVEL SNAPSHOT ein, bevor Sie die Abfrage ausführen.
L. Fügen Sie eine SET FORCEPLAN ON-Anweisung ein, bevor Sie die Abfrage ausführen.
M. Fügen Sie der Abfrage einen LOOP-Hinweis hinzu.
N. Fügen Sie einen Columnstore-Index hinzu, um die Abfrage abzudecken.
Answer: C
Explanation:
SET SHOWPLAN_XML (Transact-SQL) causes SQL Server not to execute Transact-SQL statements. Instead, SQL Server returns detailed information about how the statements are going to be executed in the form of a well-defined XML document Incorrect:
Not F: Columnstore indexes in the SQL Server Database Engine can be used to significantly speed-up the processing time of common data warehousing queries. Typical data warehousing workloads involve summarizing large amounts of data. But in this question the query is run on a table that is updated frequently, not a warehousing table.
Reference:
https://msdn.microsoft.com/en-us/library/ms187757.aspx

NEW QUESTION: 2
ユーザーのジョーは、自分の机で作業しているときに、ノートブックをモニター、マウス、キーボードに接続する必要があります。彼のノートブックはビジネスクラスではありませんが、パーソナルコンピューターに関する会社のポリシーを満たしています。
技術者がジョーのためにインストールする必要があるのは次のどれですか？
A. KVMスイッチ
B. ドッキングステーション
C. USBハブ
D. ポート転送デバイス
Answer: B

NEW QUESTION: 3
애플리케이션은 데이터 지속성을 위해 두 개의 AZ와 다중 AZ RDS 인스턴스에 배포 된 웹 / 애플리케이션 서버의 Auto Scaling 그룹 앞에서 ELB를 사용하고 있습니다.
데이터베이스 CPU는 종종 사용량이 80 % 이상이며 데이터베이스에서 I / O 작업의 90 %를 읽습니다. 성능을 향상시키기 위해 최근에 자주 단일 DB 쿼리 결과를 캐시하기 위해 단일 노드 Memcached ElastiCache 클러스터를 추가했습니다. 다음 주에는 전체 작업량이 30 % 증가 할 것으로 예상됩니다.
예상되는 추가 로드로 고 가용성 또는 응용 프로그램을 유지 보수하려면 아키텍처에서 무엇을 변경해야 합니까? 왜?
A. 예. 하나의 캐시 노드가 실패 할 경우 로드를 처리하려면 RDS DB 마스터 인스턴스와 동일한 AZ에 두 개의 노드가있는 Memcached ElastiCache 클러스터를 배포해야 합니다.
B. 예. 캐시 노드에 장애가 발생하면 RDS 인스턴스가 로드를 처리 할 수 없으므로 서로 다른 AZ에 2 개의 Memcached ElastiCache 클러스터를 배포해야 합니다.
C. 아니요, 캐시 노드에 장애가 발생하면 자동 ElastiCache 노드 복구 기능이 가용성에 미치는 영향을 방지합니다.
D. 아니요, 캐시 노드가 실패하면 가용성에 영향을 주지 않고 DB에서 항상 동일한 데이터를 얻을 수 있습니다.
Answer: B
Explanation:
Explanation
ElastiCache for Memcached
The primary goal of caching is typically to offload reads from your database or other primary data source. In most apps, you have hot spots of data that are regularly queried, but only updated periodically. Think of the front page of a blog or news site, or the top 100 leaderboard in an online game. In this type of case, your app can receive dozens, hundreds, or even thousands of requests for the same data before it's updated again.
Having your caching layer handle these queries has several advantages. First, it's considerably cheaper to add an in-memory cache than to scale up to a larger database cluster. Second, an in-memory cache is also easier to scale out, because it's easier to distribute an in-memory cache horizontally than a relational database.
Last, a caching layer provides a request buffer in the event of a sudden spike in usage. If your app or game ends up on the front page of Reddit or the App Store, it's not unheard of to see a spike that is 10 to 100 times your normal application load. Even if you autoscale your application instances, a 10x request spike will likely make your database very unhappy.
Let's focus on ElastiCache for Memcached first, because it is the best fit for a caching focused solution. We'll revisit Redis later in the paper, and weigh its advantages and disadvantages.
Architecture with ElastiCache for Memcached
When you deploy an ElastiCache Memcached cluster, it sits in your application as a separate tier alongside your database. As mentioned previously, Amazon ElastiCache does not directly communicate with your database tier, or indeed have any particular knowledge of your database. A simplified deployment for a web application looks something like this:

In this architecture diagram, the Amazon EC2 application instances are in an Auto Scaling group, located behind a load balancer using Elastic Load Balancing, which distributes requests among the instances. As requests come into a given EC2 instance, that EC2 instance is responsible for communicating with ElastiCache and the database tier. For development purposes, you can begin with a single ElastiCache node to test your application, and then scale to additional cluster nodes by modifying the ElastiCache cluster. As you add additional cache nodes, the EC2 application instances are able to distribute cache keys across multiple ElastiCache nodes. The most common practice is to use client-side sharding to distribute keys across cache nodes, which we will discuss later in this paper.

When you launch an ElastiCache cluster, you can choose the Availability Zone(s) that the cluster lives in. For best performance, you should configure your cluster to use the same Availability Zones as your application servers. To launch an ElastiCache cluster in a specific Availability Zone, make sure to specify the Preferred Zone(s) option during cache cluster creation. The Availability Zones that you specify will be where ElastiCache will launch your cache nodes. We recommend that you select Spread Nodes Across Zones, which tells ElastiCache to distribute cache nodes across these zones as evenly as possible. This distribution will mitigate the impact of an Availability Zone disruption on your ElastiCache nodes. The trade-off is that some of the requests from your application to ElastiCache will go to a node in a different Availability Zone, meaning latency will be slightly higher. For more details, refer to Creating a Cache Cluster in the Amazon ElastiCache User Guide.
As mentioned at the outset, ElastiCache can be coupled with a wide variety of databases. Here is an example architecture that uses Amazon DynamoDB instead of Amazon RDS and MySQL:

This combination of DynamoDB and ElastiCache is very popular with mobile and game companies, because DynamoDB allows for higher write throughput at lower cost than traditional relational databases. In addition, DynamoDB uses a key-value access pattern similar to ElastiCache, which also simplifies the programming model. Instead of using relational SQL for the primary database but then key-value patterns for the cache, both the primary database and cache can be programmed similarly. In this architecture pattern, DynamoDB remains the source of truth for data, but application reads are offloaded to ElastiCache for a speed boost.