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NEW QUESTION: 1
ユーザーは、AutoScalingグループの3つの終了ポリシーをどのように構成できますか？
A. 複数のポリシーをランダムな順序で定義します
B. AutoScalingグループを各ポリシーで更新し続けます
C. 順序付きリストで複数のポリシーを定義します
D. ユーザーはAutoScalingに3つ以上のポリシーを指定できません
Answer: C
Explanation:
Auto Scaling終了ポリシーを設定するには、ユーザーはいずれかのポリシーをスタンドアロンポリシーとして指定するか、複数のポリシーを順序付きリストにリストできます。
ポリシーは、リストされている順序で実行されます。
http://docs.aws.amazon.com/AutoScaling/latest/DeveloperGuide/us-termination-policy.html

NEW QUESTION: 2
配信APIエラーを解決する必要があります。
あなたは何をするべきか？
A. Invoke a custom execution strategy in Entity Framework.
B. Implement a Circuit Breaker pattern by using the EnableRetryOnFailure feature of Entity Framework.
C. Implement simple retry by using the EnableRetryOnFailure feature of Entity Framework.
D. Implement exponential backoff by using the EnableRetryOnFailure feature of Entity Framework.
Answer: D
Explanation:
Explanation
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-develop-error-messages

NEW QUESTION: 3
You have an Azure Cosmos DB account named Account1 that uses the SQL APL Account1 contains a collection named Coll1.
You have an Apache Spark cluster in Azure HDInsight. The duster is located in the same Azure region as Account1.
You configure a Spark to Cosmos DB connector to access Coll1.
You successfully use the following code to run non-aggregate queries from within a Spark session by using the connector (Line numbers are included for reference only.)
01 query= client QueryDocuments (
02 collLink, querystr,
03 options=
04 {
05 'enablecrossPartitionQuery': True
06 },
07 partition_key-None)
08 df = spark.createDataFrame(list(query))
You need to modify the code to ensure that you can run couNT aggregate quenes.
What should you do?
A. Replace line 08 with the following code: df - spark.createDataFrame (spark.sparkContext.parallelize (list (query))
B. Replace line 05 with the following code. 'enablescanInQuery': True
C. Replace fine OS with the following code: 'enableCrossPartitilonQuery': False
D. Replace line 08 with the following code: df - spark. createDataFrame (list(query), IntegerType ())
Answer: A

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