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NEW QUESTION: 1
Examine the commands executed in the root container of your multitenant container database (CDB) that has multiple pluggable databases (PDBs):
SQL> CREATE USER c##a_admin IDENTIFIED BY orcl123;
SQL> CREATE ROLE c##role1 CONTAINER=ALL;
SQL> GRANT CREATE VIEW TO C##roleI CONTAINER=ALL;
SQL> GRANT c##role1 TO c##a_admin CONTAINER=ALL;
SQL> REVOKE c##role1 FROM c##a_admin;
What is the result of the revoke command?
A. It executes successfully and the c##role1 role is revoked from the c##a_admin user only in the root container.
B. It fails and reports an error because the container=all clause is not used.
C. It executes successfully and the c##rocl1 role is revoked from the c##a_admin user in the root database and all the PDBs.
D. It fails and reports an error because the comtainer=current clause is not used.
Answer: B
Explanation:
Explanation
SQL> REVOKE c##role1 FROM c##a_admin; REVOKE c##role1 FROM c##a_admin * ERROR at line 1:
ORA - 01951: ROLE 'C##ROLE1' not granted to 'C##A_ADMIN' SQL> REVOKE c##role1 FROM c##a_admin CONTAINER=ALL; Revoke succeeded. SQL> This CREATE USER c##a_admin IDENTIFIED BY orcl123; will create common user event container is not specified.

NEW QUESTION: 2
You are developing a solution using a Lambda architecture on Microsoft Azure.
The data at test layer must meet the following requirements:
Data storage:
*Serve as a repository (or high volumes of large files in various formats.
*Implement optimized storage for big data analytics workloads.
*Ensure that data can be organized using a hierarchical structure.
Batch processing:
*Use a managed solution for in-memory computation processing.
*Natively support Scala, Python, and R programming languages.
*Provide the ability to resize and terminate the cluster automatically.
Analytical data store:
*Support parallel processing.
*Use columnar storage.
*Support SQL-based languages.
You need to identify the correct technologies to build the Lambda architecture.
Which technologies should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Data storage: Azure Data Lake Store
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With the hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Batch processing: HD Insight Spark
Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
Languages: R, Python, Java, Scala, SQL
Analytic data store: SQL Data Warehouse
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP).
SQL Data Warehouse stores data into relational tables with columnar storage.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is

NEW QUESTION: 3
Given the following SAS data sets ONE and TWO:
ONE TWO
YEAR QTR BUDGET YEAR QTR SALES
2001 3 500 2001 4 300
2001 4 400 2002 1 600
2002 1 700
The following SAS program is submitted:
proc sql;
select one.*, sales
from one, two;
quit;
Which one of the following reports is generated?
A. YEAR QTR BUDGET SALES
2001 4 400 300
2002 1 700 600
B. YEAR QTR BUDGET SALES
2001 3 500 300
2001 4 400 300
2002 1 700 300
2001 3 500 600
2001 4 400 600
2002 1 700 600
C. YEAR QTR BUDGET SALES
2001 3 500 300
2001 4 400 300
2002 1 700 600
D. YEAR QTR BUDGET SALES
2001 3 500
2001 4 400 300
2002 1 700 600
Answer: B

NEW QUESTION: 4
Which two of the following statements are true regarding standalone and lightweight access points? (Choose two.)
A. Lightweight access points are self-contained, each offering one or more fully functional BSSs.
B. Lightweight access points are also known as autonomous access points.
C. Standalone access points can be configured one-by-one and offer complete functionality by themselves.
D. Lightweight access points rely on a central wireless LAN controller to retrieve their configurations.
Answer: C,D

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