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NEW QUESTION: 1
Given:
1 . class Test {
2 . public static void main(String args[]) {
3 . int num;
4 . num = 10;
5 . calc(num);
6 . System.out.println("num = " + num);
7 . }
8 .
9 . static void calc(int num) { 1
0 . num += 100; 11. } 12. }
What is the result?
A. Compilation fails because of an error at line 3.
B. num = 10
C. num = 110
D. num = 100
E. Compilation fails because of an error at line 9.
Answer: B

NEW QUESTION: 2
What steps can be taken if IPS is causing a High Performance Impact?
A. Consider activating the "Bypass under Load" IPS setting on the gateway
B. All options listed
C. Check your IPS configuration assigned to this gateway and deactivate protections with critical or high performance impact
D. Determine if different or custom IPS profiles are better suited for different gateways in your organization
Answer: B

NEW QUESTION: 3









A. Option A
B. Option C
C. Option D
D. Option B
Answer: A,D
Explanation:
Using Cross Joins
A cross join that does not have a WHERE clause produces the Cartesian product of the tables involved in the join. The size of a Cartesian product result set is the number of rows in the first table multiplied by the number of rows in the second table.
However, if a WHERE clause is added, the cross join behaves as an inner join.
B: You can use the IIF in the ON-statement.
IIF returns one of two values, depending on whether the Boolean expression evaluates to true or false in SQL Server.
References:
https://technet.microsoft.com/en-us/library/ms190690(v=sql.105).aspx
https://msdn.microsoft.com/en-us/library/hh213574.aspx

NEW QUESTION: 4
機械学習モデルを使用してインテリジェントなソリューションを構築しています。
環境は、次の要件をサポートする必要があります。
*データサイエンティストはクラウド環境でノートブックを作成する必要があります
*データサイエンティストは、機械学習パイプラインで自動機能エンジニアリングとモデル構築を使用する必要があります。
*動的なワーカー割り当てを備えたSparkインスタンスを使用して再トレーニングするには、ノートブックをデプロイする必要があります。
*ノートブックは、ローカルでバージョン管理できるようにエクスポート可能である必要があります。
環境を作成する必要があります。

Answer:
Explanation:

Explanation:
Step 1: Create an Azure HDInsight cluster to include the Apache Spark Mlib library Step 2: Install Microsot Machine Learning for Apache Spark You install AzureML on your Azure HDInsight cluster.
Microsoft Machine Learning for Apache Spark (MMLSpark) provides a number of deep learning and data science tools for Apache Spark, including seamless integration of Spark Machine Learning pipelines with Microsoft Cognitive Toolkit (CNTK) and OpenCV, enabling you to quickly create powerful, highly-scalable predictive and analytical models for large image and text datasets.
Step 3: Create and execute the Zeppelin notebooks on the cluster
Step 4: When the cluster is ready, export Zeppelin notebooks to a local environment.
Notebooks must be exportable to be version controlled locally.
References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-zeppelin-notebook
https://azuremlbuild.blob.core.windows.net/pysparkapi/intro.html