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NEW QUESTION: 1
会社は複数の地域に拠点を持っています。同社はPower AppsとPower Automateに基づくソリューションを開発しています。
実装をサポートする機能を推奨する必要があります。
どのPower Platform機能を推奨しますか?回答するには、適切な機能を正しい要件にドラッグします。各機能は、1回、複数回、またはまったく使用しない場合があります。ペイン間で分割バーをドラッグするか、コンテンツを表示するにはスクロールする必要がある場合があります。
注:それぞれの正しい選択は1ポイントの価値があります。

Answer:
Explanation:

Reference:
https://docs.microsoft.com/en-us/power-platform/admin/environments-overview
https://docs.microsoft.com/en-us/power-platform/admin/control-user-access

NEW QUESTION: 2

A. salting
B. padding
C. hashing
D. trimming
Answer: A,C
Explanation:
Explanation
There are two strategies that you can use to avoid hotspotting:
* Hashing keys
To spread write and insert activity across the cluster, you can randomize sequentially generated keys by hashing the keys, inverting the byte order. Note that these strategies come with trade-offs. Hashing keys, for example, makes table scans for key subranges inefficient, since the subrange is spread across the cluster.
* Salting keys
Instead of hashing the key, you can salt the key by prepending a few bytes of the hash of the key to the actual key.
Note. Salted Apache HBase tables with pre-split is a proven effective HBase solution to provide uniform workload distribution across RegionServers and prevent hot spots during bulk writes. In this design, a row key is made with a logical key plus salt at the beginning. One way of generating salt is by calculating n (number of regions) modulo on the hash code of the logical row key (date, etc).
Reference:
https://blog.cloudera.com/blog/2015/06/how-to-scan-salted-apache-hbase-tables-with-region-specific-key-ranges
http://maprdocs.mapr.com/51/MapR-DB/designing_row_keys_for_mapr_db_binary_tables.html

NEW QUESTION: 3



A. Option B
B. Option A
C. Option C
D. Option D
Answer: B