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NEW QUESTION: 1

A. add ns simpleacl
B. add ns acl6
C. add ns acl
D. add ns simpleacl6
Answer: C
Explanation:
https://docs.citrix.com/en-us/netscaler/12/networking/access-control-lists-acls.html

NEW QUESTION: 2
You have data stored in thousands of CSV files in Azure Data Lake Storage Gen2. Each file has a header row followed by a property formatted carriage return (/r) and line feed (/n).
You are implementing a pattern that batch loads the files daily into an Azure SQL data warehouse by using PolyBase.
You need to skip the header row when you import the files into the data warehouse.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Which three actions you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:
Explanation:

Explanation

Step 1: Create an external data source and set the First_Row option.
Creates an External File Format object defining external data stored in Hadoop, Azure Blob Storage, or Azure Data Lake Store. Creating an external file format is a prerequisite for creating an External Table.
FIRST_ROW = First_row_int
Specifies the row number that is read first in all files during a PolyBase load. This parameter can take values
1-15. If the value is set to two, the first row in every file (header row) is skipped when the data is loaded.
Rows are skipped based on the existence of row terminators (/r/n, /r, /n).
Step 2: Create an external data source that uses the abfs location
The hadoop-azure module provides support for the Azure Data Lake Storage Gen2 storage layer through the
"abfs" connector
Step 3: Use CREATE EXTERNAL TABLE AS SELECT (CETAS) and create a view that removes the empty row.
References:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-external-file-format-transact-sql
https://hadoop.apache.org/docs/r3.2.0/hadoop-azure/abfs.html

NEW QUESTION: 3
An organization must process a stream of large-volume hashtag data in real time and needs to run custom SQL
queries on the data to get insights on certain tags. The organization needs this solution to be elastic and does
not want to manage clusters.
Which of the following AWS services meets these requirements?
A. Amazon Athena
B. Amazon Kinesis Data Analytics
C. Amazon Elasticsearch Service
D. Amazon Redshift
Answer: B