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NEW QUESTION: 1
You plan to bulk load data INSERT INTO . . . SELECT FROM statements.
Which two situations benefit from parallel INSERT operations on tables that have no materialized views defined on them?
A. Conventional path insert of 10 rows into a nonpartitioned, heap-organized table one million rows and a bitmapped index.
B. Direct path insert of 10 rows into a partitioned, index-organized table containing 10 rows and a bitmapped secondary index
C. Direct path insert of 10 rows into a partitioned, index-organized table containing one million rows and conventional B* tree secondary index.
D. Direct path insert of a million rows into a partitioned, index-organized table containing 10 rows and a bitmapped secondary index.
E. Direct path insert of a million rows into a partitioned, index-organized table containing one million rows and a conventional B*tree secondary index.
F. Conventional path insert of a million rows into a nonpartitioned, heap-organized containing 10 rows and having a conventional B* tree index.
Answer: D,E
Explanation:
Note:
*A materialized view is a database object that contains the results of a query.
*You can use the INSERT statement to insert data into a table, partition, or view in two ways: conventional INSERTand direct-path INSERT.
*With direct-path INSERT, the database appends the inserted data after existing data in the table. Data is written directly into datafiles, bypassing the buffer cache. Free space in the existing data is not reused. This alternative enhances performance during insert operations and is similar to the functionality of the Oracle direct-path loader utility, SQL*Loader. When you insert into a table that has been created in parallel mode, direct-path INSERT is the default.
*Direct-path INSERT is not supported for an index-organized table (IOT) if it is not partitioned, if it has a mapping table, or if it is reference by a materialized view.
*When you issue a conventional INSERT statement, Oracle Database reuses free space in the table into which you are inserting and maintains referential integrity constraints
*Conventional INSERT always generates maximal redo and undo for changes to both data and metadata, regardless of the logging setting of the table and the archivelog and force logging settings of the database

NEW QUESTION: 2
ある企業は、複数の資格情報を同期させなくても、従業員が複数のアプリケーションに同じユーザー名とパスワードを使用できるようにするアクセス管理ソリューションを実装したいと考えています。
次の解決策のうちどれがこれらの要件を最もよく満たすでしょうか？
A. SSO
B. バイオメトリクス
C. 多要素認証
D. PKI
E. フェデレーション
Answer: A

NEW QUESTION: 3
Azure Machine Learning Studioで分類タスクを実行しています。
提供されたデータセットに基づいて、バランスの取れたテストおよびトレーニングサンプルを準備する必要があります。
0.75：0.25の比率でデータを分割する必要があります。
各パラメーターにどの値を使用する必要がありますか？ 回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation:
Box 1: Split rows
Use the Split Rows option if you just want to divide the data into two parts. You can specify the percentage of data to put in each split, but by default, the data is divided 50-50.
You can also randomize the selection of rows in each group, and use stratified sampling. In stratified sampling, you must select a single column of data for which you want values to be apportioned equally among the two result datasets.
Box 2: 0.75
If you specify a number as a percentage, or if you use a string that contains the "%" character, the value is interpreted as a percentage. All percentage values must be within the range (0, 100), not including the values 0 and 100.
Box 3: Yes
To ensure splits are balanced.
Box 4: No
If you use the option for a stratified split, the output datasets can be further divided by subgroups, by selecting a strata column.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/split-data

NEW QUESTION: 4
ネットワークにはActive Directoryフォレストが含まれています。 フォレストにはcontoso.comという名前のドメインが含まれています。ドメインには3つのドメインコントローラーが含まれています。
lon-dc1という名前のドメインコントローラーが失敗します。lon-dc1は修復できません。
あなたは、他のドメイン・コントローラが、lon-dc1に複製することを試みることを防止する必要がある。
Solution: Active Directoryサイトと信頼から、lon-dc1の操作マスタの役割を転送します。
これは目標を満たしていますか？
A. NO
B. Yes
Answer: A