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NEW QUESTION: 1
A. Option A
B. Option C
C. Option B
D. Option D
Answer: D
NEW QUESTION: 2
Sie haben eine Data-Warehouse-Faktentabelle mit einem Clustered-Columnstore-Index.
Sie haben mehrere CSV-Dateien mit insgesamt 3 Millionen Datenzeilen.
Sie müssen die Daten in die Faktentabelle hochladen. Die Lösung muss die Delta-Gruppe vermeiden, wenn Sie die Daten importieren.
Welche Lösung erreicht das Ziel in kürzester Zeit?
A. Laden Sie die Quelldaten in die Faktentabelle, indem Sie bcp.exe ausführen und die Option _ Tablock angeben.
B. Laden Sie die Quelldaten in eine Staging-Tabelle. Laden Sie die Daten mithilfe der Anweisung insert_select in die Faktentabelle und geben Sie die Tablock-Option in der Staging-Tabelle an.
C. Laden Sie die Quelldaten in eine Staging-Tabelle mit einem Clustered-Index für den Primärschlüssel. Kopieren Sie die Daten mit der Anweisung insert_select in die Faktentabelle.
D. Laden Sie die Quelldaten mithilfe der Bulk-Insert-Anweisung in die Faktentabelle und geben Sie die Tablock-Option an.
Answer: C
Explanation:
Explanation
If you are loading data only to stage it before running more transformations, loading the table to heap table will be much faster than loading the data to a clustered columnstore table. In addition, loading data to a
[temporary table][Temporary] will also load much faster than loading a table to permanent storage.
A common pattern for data load is to load the data into a staging table, do some transformation and then load it into the target table using the following command INSERT INTO <columnstore index> SELECT <list of columns> FROM <Staging Table> This command loads the data into the columnstore index in similar ways to BCP or Bulk Insert but in a single batch. If the number of rows in the staging table < 102400, the rows are loaded into a delta rowgroup otherwise the rows are directly loaded into compressed rowgroup. One key limitation was that this INSERT operation was single threaded. To load data in parallel, you could create multiple staging table or issue INSERT/SELECT with non-overlapping ranges of rows from the staging table. This limitation goes away with SQL Server 2016 (13.x). The command below loads the data from staging table in parallel but you will need to specify TABLOCK.
References:
https://docs.microsoft.com/en-us/sql/relational-databases/indexes/columnstore-indexes-data-loading-guidance?vi
NEW QUESTION: 3
Which two steps would NOT be required to create and deploy a new Service to Alfresco?
A. Create the proxy class and bean definition.
B. Define message bundles for the service.
C. Create the implementation class and bean definition.
D. Define bean definition and register.
E. Register the new class with ServiceRegistry.newService().
Answer: B,E
NEW QUESTION: 4
Bottom-up service Identification analyzes existing systems to Identify SOA Services. Top-down service identification analyzes business processes to identify SOA services.
Which statement best describes the relationship between top down and bottom-up service identification in Service-Oriented Integration?
A. A bottom-up approach should be used to identify which SOA Services are built; then a top-down approach should be used to determine which SOA Services are used by each composite application.
B. A top-down approach should be used to determine the needed SOA Services; then a bottom-up approach should be used to determine how existing source systems can meet the requirements top-down approach should be used by business, and a bottom-up approach should be used by IT.Theoverlap between the SOA Services Identified by the two methods are the ones that should
C. Only a top-down approach should be used because the goal of SOI is composite application assembly.
D. Only a bottom up approach shouldbe used because the goal of SOIis to provide SOA Services exposing existing systems.
Answer: B
Explanation:
Note: There are three schools of thought around "how to build an Enterprise Service Oriented Architecture." They are:
*Top down - central group decides everything and the dev teams adopt them.
*Bottom up - central group provides a directory and dev teams make whatever services they want. Dev teams go to the directory to find services they can use.
*Middle out - central group provides key elements of the interface, including numbering schemes, message exchange patterns, standard communication mechanisms, and monitoring infrastructure, and encourages the dev teams to use it to build services that can be shared.