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NEW QUESTION: 1
Randall is using OS X Yosemite v10.10 on a MacBook Air (Late 2010). He would like to AirDrop a 7GB file to a colleague. The colleague is using OS X Mountain Lion v10.8.5 on an iMac (Early 2009). Randall cannot locate the colleague's iMac in AirDrop. Which of the following is preventing this transfer?
A. AirDrop does not support files larger than 5GB.
B. OS X Yosemite cannot AirDrop with OS X Mountain Lion.
C. On the MacBook Air, Randall must first click "Don't see who you're looking for?'
D. The iMac (Early 2009) does not support AirDrop.
Answer: C
NEW QUESTION: 2
Find the value of (10) in the ANOVA table. Assume:
A. 12.2
B. 0.005<P<0.01
C. 0.05<P<0.10
D. 0.01<P<0.05
E. 35.4
F. 1.48
G. 16.4
H. 2.82
I. 3.2
J. 0<P<0.005
K. 18.6
L. 0.525
M. 4.54
N. 0.10<P<1
O. 23.2
Answer: O
NEW QUESTION: 3
HDInsightクラスターで毎日のWebトラフィックログの分析を実行するプロセスを管理します。 250のWebサーバーのそれぞれが、毎日約ギガバイト（GB）のログデータを生成します。すべてのログデータは、Microsoft Azure Data Lake Storage Gen 2の単一のフォルダーに保存されます。
プロセスのパフォーマンスを改善する必要があります。
どちらの変更を加える必要がありますか？それぞれの正解は完全な解決策を提示します。
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。
A. ワーカーノードの数を増やす
B. 毎日のログが独自のフォルダーにあるように、ログファイルをフォルダーに移動します
C. hive.tez.container.sizeパラメーターの値を増やします
D. すべてのサーバーの毎日のログファイルを1つのファイルに結合します
E. mapreduce.map.memoryパラメーターの値を増やします
Answer: B,D
Explanation:
A：通常、HDInsightやAzure Data Lake Analyticsなどの分析エンジンには、ファイルごとのオーバーヘッドがあります。データを多くの小さなファイルとして保存すると、パフォーマンスに悪影響を与える可能性があります。一般的に、パフォーマンスを向上させるためにデータを大きなサイズのファイルに整理します（サイズは256MB〜100GB）。一部のエンジンおよびアプリケーションでは、サイズが100GBを超えるファイルを効率的に処理するのに問題がある場合があります。
C：Hiveワークロードの場合、時系列データのパーティションプルーニングは、一部のクエリがデータのサブセットのみを読み取るのに役立ち、パフォーマンスが向上します。
時系列データを取り込むこれらのパイプラインは、多くの場合、ファイルとフォルダーの非常に構造化された名前でファイルを配置します。以下は、日付で構造化されたデータで見られる非常に一般的な例です。
\DataSet\YYYY\MM\DD\datafile_YYYY_MM_DD.tsv
日時情報は、フォルダーとファイル名の両方に表示されることに注意してください。
参照：
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-performance-tuning-guidance