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NEW QUESTION: 1
Wählen Sie für jede der folgenden Aussagen Ja aus, wenn die Aussage wahr ist. Andernfalls wählen Sie Nein. HINWEIS: Jede richtige Auswahl ist einen Punkt wert.
Answer:
Explanation:
NEW QUESTION: 2
DRAG DROP
Answer:
Explanation:
Explanation:
NodeWeight settings are used during quorum voting to support disaster recovery and multi-subnet scenarios for AlwaysOn Availability Groups and SQL Server Failover Cluster Instances.
Example (Powershell)
The following example changes the NodeWeight setting to remove the quorum vote for the
"AlwaysOnSrv1" node.
Import-Module FailoverClusters
$node = "AlwaysOnSrv1"
(Get-ClusterNode $node).NodeWeight = 0
Reference: Configure Cluster Quorum NodeWeight Settings.
NEW QUESTION: 3
Answer:
Explanation:
Explanation
Box 1: Ole DB Source
Box 2: Conditional Split
Disregard lines with a 0 sum.
Box 3: Derived column
Box 4: Ole DB Destination
Note:
* You configure a Data Flow task by adding components to the Data Flow tab. SSIS supports three types of data flow components:
Sources: Where the data comes from
Transformations: How you can modify the data
Destinations: Where you want to put the data
* Creating a data flow includes the following steps:
/ Adding one or more sources to extract data from files and databases, and add connection managers to connect to the sources.
/ Adding the transformations that meet the business requirements of the package. A data flow is not required to include transformations.
Some transformations require a connection manager. For example, the Lookup transformation uses a connection manager to connect to the database that contains the lookup data.
/ Connecting data flow components by connecting the output of sources and transformations to the input of transformations and destinations.
/ Adding one or more destinations to load data into data stores such as files and databases, and adding connection managers to connect to the data sources.
/ Configuring error outputs on components to handle problems.
At run time, row-level errors may occur when data flow components convert data, perform a lookup, or evaluate expressions. For example, a data column with a string value cannot be converted to an integer, or an expression tries to divide by zero. Both operations cause errors, and the rows that contain the errors can be processed separately using an error flow.
/ Include annotations to make the data flow self-documenting.
* The capabilities of transformations vary broadly. Transformations can perform tasks such as updating, summarizing, cleaning, merging, and distributing data. You can modify values in columns, look up values in tables, clean data, and aggregate column values.
* The Data Flow task encapsulates the data flow engine that moves data between sources and destinations, and lets the user transform, clean, and modify data as it is moved. Addition of a Data Flow task to a package control flow makes it possible for the package to extract, transform, and load data.
A data flow consists of at least one data flow component, but it is typically a set of connected data flow components: sources that extract data; transformations that modify, route, or summarize data; and destinations that load data.
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