Questions and Answers: 166
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NEW QUESTION: 1
技術者は、サーバーに追加のNICをインストールするよう求められます。 技術者が次のハードウェアを考慮するのはどれですか？
A. CPUステッピング
B. CASレイテンシ
C. バスの種類と速度
D. 消費電力
Answer: C
NEW QUESTION: 2
シスコ製ルータにはファンの問題があり、温度が上昇して障害が発生する可能性があります。追加のリスクを引き起こすことなく問題を検証するためのトラブルシューティング手順は何ですか？
A. コマンド "logging on"、 "logging buffered 6"を使用してロギングを設定し、 "show logging"を使用してファン障害ログを確認します。
B. コマンド "logging on"、 "logging buffered 4"を使用してロギングを設定し、 "show logging"を使用してファン障害ログを確認します。
C. コマンド "logging on"、 "logging識別子" msglog1 console 7を使用してロギングを設定し、 "show logging"を使用してファン障害ログを確認します。
D. コマンド "logging host 10.11.10.11"、 "logging trap 2"を使用してロギングを設定し、syslogサーバーでファン障害ログを確認します10.11.10.11
Answer: B
NEW QUESTION: 3
Cryptocurrencies have all the same characteristics as fiat currencies?
A. False
B. True
Answer: A
NEW QUESTION: 4
You have a Microsoft Azure SQL data warehouse that has a fact table named FactOrder. FactOrder contains three columns named CustomerID, OrderID, and OrderDateKey. FactOrder is hash distributed on CustomerID. OrderID is the unique identifier for FactOrder. FactOrder contains 3 million rows.
Orders are distributed evenly among different customers from a table named dimCustomers that contains
2 million rows.
You often run queries that join FactOrder and dimCustomers by selecting and grouping by the OrderDateKey column.
You add 7 million rows to FactOrder. Most of the new records have a more recent OrderDateKey value than the previous records.
You need to reduce the execution time of queries that group on OrderDateKey and that join dimCustomers and FactOrder.
What should you do?
A. Update the statistics for the OrderDateKey column
B. Change the distribution for the dimCustomers table to OrderDateKey
C. Change the distribution for the FactOrder table to round robin
D. Change the distribution for the FactOrder table to be based on OrderID
Answer: A
Explanation:
Explanation/Reference:
Updating statistics
One best practice is to update statistics on date columns each day as new dates are added. Each time new rows are loaded into the data warehouse, new load dates or transaction dates are added. These change the data distribution and make the statistics out of date.
References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables- statistics