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NEW QUESTION: 1
If the OPTHINTS subsystem parameter is set to YES, and you issue the following DB2 command relating to optimization parameter hints:
BIND QUERY LOOKUP (YES)
what is the result of the execution of this command?
A. A list of queries that are in error is produced.
B. Messages containing only the status of rows in catalog tables SYSIBM.SYSQUERY and SYSIBM.SYSQUERYPLAN.
C. Updated values are placed in SYSIBM.SYSQUERY and SYSIBM.SYSQUERYPLAN tables.
D. New values are inserted into the SYSIBM.SYSQUERY and SYSIBM.SYSQUERYPLAN tables.
Answer: B

NEW QUESTION: 2
R1 is unable to establish an OSPF neighbor relationship with R3. What are possible reasons for this problem? (Choose two)

A. All of the routers need to be configured for backbone Area 1.
B. R1 and R3 are configured in different areas.
C. The hello and dead interval timers are not set to the same values on R1 and R3.
D. EIGRP is also configured on these routers with a lower administrative distance.
E. R1 and R2 are the DR and BDR, so OSPF will not establish neighbor adjacency with R3.
F. A static route has been configured from R1 to R3 and prevents the neighbor adjacency from being established.
Answer: B,C
Explanation:
Explanation/Reference:
Explanation:
To become OSPF neighbors, routers must meet these requirements: Hello interval, Dead interval and AREA number -> D and F are correct.

NEW QUESTION: 3
You are running a training experiment on remote compute in Azure Machine Learning.
The experiment is configured to use a conda environment that includes the mlflow and azureml-contrib-run packages.
You must use MLflow as the logging package for tracking metrics generated in the experiment.
You need to complete the script for the experiment.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: import mlflow
Import the mlflow and Workspace classes to access MLflow's tracking URI and configure your workspace.
Box 2: mlflow.start_run()
Set the MLflow experiment name with set_experiment() and start your training run with start_run().
Box 3: mlflow.log_metric(' ..')
Use log_metric() to activate the MLflow logging API and begin logging your training run metrics.
Box 4: mlflow.end_run()
Close the run:
run.endRun()
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow

NEW QUESTION: 4
ある会社がゲームプラットフォームを開発しています。ユーザーはチームに参加してオンラインでプレイし、プレーヤーの統計を含むリーダーボードを見ることができます。このソリューションには、Teamという名前のエンティティが含まれています。
Azure Redis Cacheインスタンスを実装して、ほとんど変更されないエンティティのデータ操作の効率を向上させることを計画しています。
チームデータが変更された場合は、キャッシュを無効にする必要があります。
コードをどのように完成させる必要がありますか？回答するには、回答領域で適切なオプションを選択します。
注：正しい選択はそれぞれ1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1: IDatabase cache = connection.GetDatabase();
Connection refers to a previously configured ConnectionMultiplexer.
Box 2: cache.StringSet("teams",")
To specify the expiration of an item in the cache, use the TimeSpan parameter of StringSet.
cache.StringSet("key1", "value1", TimeSpan.FromMinutes(90));
References:
https://azure.microsoft.com/sv-se/blog/lap-around-azure-redis-cache-preview/

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