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NEW QUESTION: 1

A. IDS
B. Antivirus
C. IPS
D. Firewall
Answer: B

NEW QUESTION: 2
You want to capture column group usage and gather extended statistics for better cardinality estimates for the CUSTOMERS table in the SH schema.
Examine the following steps:
1.Issue the SELECT DBMS_STATS.CREATE_EXTENDED_STATS ('SH', 'CUSTOMERS') FROM dual statement.
2.Execute the DBMS_STATS.SEED_COL_USAGE (null, 'SH', 500) procedure.
3.Execute the required queries on the CUSTOMERS table.
4.Issue the SELECT DBMS_STATS.REPORT_COL_USAGE ('SH', 'CUSTOMERS') FROM dual statement.
Identify the correct sequence of steps.
A. 2, 3, 4, 1
B. 3, 2, 4, 1
C. 4, 1, 3, 2
D. 3, 2, 1, 4
Answer: A
Explanation:
Step 1 (2). Seed column usage Oracle must observe a representative workload, in order to determine the appropriate column groups. Using the new procedure DBMS_STATS.SEED_COL_USAGE, you tell Oracle how long it should observe the workload. Step 2: (3) You don't need to execute all of the queries in your work during this window. You can simply run explain plan for some of your longer running queries to ensure column group information is recorded for these queries. Step 3. (1) Create the column groups At this point you can get Oracle to automatically create the column groups for each of the tables based on the usage information captured during the monitoring window. You simply have to call the DBMS_STATS.CREATE_EXTENDED_STATS function for each table.This function requires just two arguments, the schema name and the table name. From then on, statistics will be maintained for each column group whenever statistics are gathered on the table.
Note:
*DBMS_STATS.REPORT_COL_USAGE reports column usage information and records all the
SQL operations the database has processed for a given object.
*The Oracle SQL optimizer has always been ignorant of the implied relationships between data
columns within the same table. While the optimizer has traditionally analyzed the distribution of
values within a column, he does not collect value-based relationships between columns.
*Creating extended statisticsHere are the steps to create extended statistics for related table
columns withdbms_stats.created_extended_stats:
1 - The first step is to create column histograms for the related columns.2 - Next, we run
dbms_stats.create_extended_stats to relate the columns together.
Unlike a traditional procedure that is invoked via an execute ("exec") statement, Oracle extended
statistics are created via a select statement.

NEW QUESTION: 3
DTPには何が当てはまりますか？ （3つ選択してください。）
A. デフォルトで有効化
B. レイヤー2プロトコル
C. デフォルトで無効
D. 独自のプロトコル
E. レイヤー3プロトコル
Answer: A,B,D

NEW QUESTION: 4
You are developing a SQL Server Analysis Services (SSAS) tabular project. The model has tables named Invoice Line Items and Products.
The Invoice Line Items table has the following columns:
Product Id

Unit Sales Price

The Unit Sales Price column stores the unit price of the product sold.
The Products table has the following columns:
Product Id

Minimum Sales Price

The Minimum Sales Price column is available only in the Products table.
You add a column named Is Undersell to the Invoice Line Items table. The Is Undersell column must store a value of TRUE if the value of the Unit Sales Price is less than the value of the Minimum Sales Price.
Otherwise, a value of FALSE must be stored.
You need to define the Data Analysis Expressions (DAX) expression for the Is Undersell column.
Which DAX formula should you use? (Each answer represents a complete solution. Choose all that apply.)
A. =IF([Unit Sales Price])< LOOKUPVALUE(Products[Minimum Sales Price], Products[Product Id],
[Product id]), TRUE, FALSE)
B. =IF (RELATED(Products[Unit Sales Price])< [Minimum Sales Price], TRUE, FALSE)
C. =IF([Unit Sales Price]< RELATED(Products[Minimum Sales Price]), TRUE, FALSE)
D. =IF(LOOKUPVALUE (Products[Unit Sales Price], Products[Product Id], [Product id])<[ Minimum Sales price]), TRUE, FALSE)
Answer: A,C
Explanation:
Explanation/Reference:
Explanation:
A: RELATED Function
Returns a related value from another table.
The RELATED function requires that a relationship exists between the current table and the table with related information.
You specify the column that contains the data that you want, and the function follows an existing many-to- one relationship to fetch the value from the specified column in the related table.
C: The lookupvalue function returns the value in result_columnName for the row that meets all criteria specified by search_columnName and search_value.
Syntax:
LOOKUPVALUE( <result_columnName>, <search_columnName>, <search_value>
[,<search_columnName>, <search_value>]...)
Note:
The syntax of DAX formulas is very similar to that of Excel formulas, and uses a combination of functions, operators, and values.