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NEW QUESTION: 1
Given:
package p1;
public interface DoInterface { void method1(int n1); // line n1
}
package p3;
import p1.DoInterface;
public class DoClass implements DoInterface { public DoClass(int p1) { } public void method1(int p1) { } // line n2 private void method2(int p1) { } // line n3
}
public class Test {
public static void main(String[] args) {
DoInterface doi= new DoClass(100); // line n4
doi.method1(100);
doi.method2(100);
}
}
A. Option C
B. Option D
C. Option A
D. Option B
Answer: A
NEW QUESTION: 2
技術者がUSBストレージデバイス上のソースファイルを使用してサーバーにオペレーティングシステムをインストールしています。 技術者は、サーバー上の異なるUSBポートを使用してUSBデバイスを起動できません。 USBストレージからオペレーティングシステムをインストールできるように、技術者が行うべきことは次のうちどれですか？
A. BIOSファームウェアを更新する
B. 起動順序を再設定する
C. 最新のUSBデバイスドライバをインストールする
D. ソースファイルをCDにコピーする
Answer: B
NEW QUESTION: 3
次のAzure Stream Analyticsクエリがあります。
次の各文について、文が真の場合は「はい」を選択します。 それ以外の場合は、[いいえ]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: Yes
You can now use a new extension of Azure Stream Analytics SQL to specify the number of partitions of a stream when reshuffling the data.
The outcome is a stream that has the same partition scheme. Please see below for an example:
WITH step1 AS (SELECT * FROM [input1] PARTITION BY DeviceID INTO 10),
step2 AS (SELECT * FROM [input2] PARTITION BY DeviceID INTO 10)
SELECT * INTO [output] FROM step1 PARTITION BY DeviceID UNION step2 PARTITION BY DeviceID Note: The new extension of Azure Stream Analytics SQL includes a keyword INTO that allows you to specify the number of partitions for a stream when performing reshuffling using a PARTITION BY statement.
Box 2: Yes
When joining two streams of data explicitly repartitioned, these streams must have the same partition key and partition count.
Box 3: Yes
10 partitions x six SUs = 60 SUs is fine.
Note: Remember, Streaming Unit (SU) count, which is the unit of scale for Azure Stream Analytics, must be adjusted so the number of physical resources available to the job can fit the partitioned flow. In general, six SUs is a good number to assign to each partition. In case there are insufficient resources assigned to the job, the system will only apply the repartition if it benefits the job.
Reference:
https://azure.microsoft.com/en-in/blog/maximize-throughput-with-repartitioning-in-azure-stream-analytics/