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NEW QUESTION: 1
Hinweis: Diese Frage ist Teil einer Reihe von Fragen, bei denen die gleichen oder ähnliche Antwortmöglichkeiten verwendet werden. Eine Antwortauswahl kann für mehr als eine Frage in der Reihe richtig sein. Jede Frage ist unabhängig von den anderen Fragen in dieser Reihe. In einer Frage angegebene Informationen und Details gelten nur für diese Frage.
Sie haben eine Microsoft SQL Server-Datenbank mit dem Namen DB1, die die folgenden Tabellen enthält:
Benutzer führen häufig die folgende Abfrage aus. Die Benutzer berichten, dass die Abfrage lange dauert, um Ergebnisse zurückzugeben.
Sie müssen die Zeit minimieren, die die Abfrage benötigt, um Daten zurückzugeben. Was tun?
A. Erstellen Sie CHECK-Einschränkungen für TBL1 und TBL2. Erstellen Sie eine partitionierte Ansicht, die Spalten aus TBL1 und TBL2 kombiniert.
B. Löschen Sie vorhandene Indizes in TBL1 und erstellen Sie dann einen Clustered-Columnstore-Index. Erstellen Sie einen nicht gruppierten Columnstore-Index für TBL1. Erstellen Sie einen nicht gruppierten Index für TBL2.
C. Erstellen Sie Clustered-Indizes für TBL1 und TBL2.
D. Löschen Sie vorhandene Indizes in tbli und erstellen Sie dann einen gruppierten Columnstore-Index. Erstellen Sie einen nicht gruppierten Columnstore-Index für tbli. Nehmen Sie keine Änderungen an TBL2 vor.
E. Erstellen Sie eindeutige Einschränkungen für TBL1 und TBL2. Erstellen Sie eine partitionierte Ansicht, die Spalten aus TBL1 und TBL2 kombiniert.
F. Erstellen Sie einen Clustered-Index für TBL1. Erstellen Sie einen Nonclustered-Index für TBL2 und fügen Sie die am häufigsten abgefragten Spalten als eingeschlossene Spalten hinzu.
G. Erstellen Sie eine indizierte Ansicht, die Spalten aus TBL1 und TBL2 kombiniert.
H. Erstellen Sie einen nicht gruppierten Index nur für TBL2.
Answer: G
NEW QUESTION: 2
Drag and Drop Question
You are a developer for a software as a service (SaaS) company that uses an Azure Function to process orders. The Azure Function currently runs on an Azure Function app that is triggered by an Azure Storage queue.
You are preparing to migrate the Azure Function to Kubernetes using Kubernetes-based Event Driven Autoscaling (KEDA).
You need to configure Kubernetes Custom Resource Definitions (CRD) for the Azure Function.
Which CRDs should you configure? To answer, drag the appropriate CRD types to the correct locations. Each CRD type may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Deployment
To deploy Azure Functions to Kubernetes use the func kubernetes deploy command has several attributes that directly control how our app scales, once it is deployed to Kubernetes.
Box 2: ScaledObject
With --polling-interval, we can control the interval used by KEDA to check Azure Service Bus Queue for messages.
Example of ScaledObject with polling interval
apiVersion: keda.k8s.io/v1alpha1
kind: ScaledObject
metadata:
name: transformer-fn
namespace: tt
labels:
deploymentName: transformer-fn
spec:
scaleTargetRef:
deploymentName: transformer-fn
pollingInterval: 5
minReplicaCount: 0
maxReplicaCount: 100
Box 3: Secret
Store connection strings in Kubernetes Secrets.
Example: to create the Secret in our demo Namespace:
# create the k8s demo namespace
kubectl create namespace tt
# grab connection string from Azure Service Bus
KEDA_SCALER_CONNECTION_STRING=$(az servicebus queue authorization-rule keys list \ -g
$RG_NAME \
--namespace-name $SBN_NAME \
--queue-name inbound \
-n keda-scaler \
--query "primaryConnectionString" \
-o tsv)
# create the kubernetes secret
kubectl create secret generic tt-keda-auth \
--from-literal KedaScaler=$KEDA_SCALER_CONNECTION_STRING \
--namespace tt
Reference:
https://www.thinktecture.com/en/kubernetes/serverless-workloads-with-keda/
NEW QUESTION: 3
A lower recovery time objective (RTO) results in:
A. higher disaster tolerance.
B. higher cost.
C. more permissive data loss.
D. wider interruption windows.
Answer: B
Explanation:
Explanation/Reference:
Explanation:
A recovery time objective (RTO) is based on the acceptable downtime in case of a disruption of operations.
The lower the RTO, the higher the cost of recovery strategies. The lower the disaster tolerance, the narrower the interruption windows, and the lesser the permissive data loss.
NEW QUESTION: 4
A. Option A
B. Option D
C. Option C
D. Option B
Answer: A