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NEW QUESTION: 1
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、記載された目標を達成する可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合もあれば、正しい解決策がない場合もあります。
このセクションの質問に回答すると、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
Azure Data Lake Gen1ストレージを使用するHDInsight / Hadoopクラスターソリューションを設計しています。
ソリューションにはPOSIX権限が必要であり、監査の診断ログを有効にします。
ストレージを最適化するソリューションを推奨する必要があります。
提案されたソリューション：圧縮ジョブを実装して、小さなファイルを大きなファイルに結合します。
ソリューションは目標を達成していますか？
A. はい
B. いいえ
Answer: A
Explanation:
Explanation
Depending on what services and workloads are using the data, a good size to consider for files is 256 MB or greater. If the file sizes cannot be batched when landing in Data Lake Storage Gen1, you can have a separate compaction job that combines these files into larger ones.
Note: POSIX permissions and auditing in Data Lake Storage Gen1 comes with an overhead that becomes apparent when working with numerous small files. As a best practice, you must batch your data into larger files versus writing thousands or millions of small files to Data Lake Storage Gen1. Avoiding small file sizes can have multiple benefits, such as:
Lowering the authentication checks across multiple files
Reduced open file connections
Faster copying/replication
Fewer files to process when updating Data Lake Storage Gen1 POSIX permissions References:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-best-practices

NEW QUESTION: 2
You write the following method (line numbers are included for reference only):

You need to ensure that the method extracts a list of URLs that match the following pattern:
@http://(www\.)?([