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Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-600
あなたは湖畔の家を含むFabricテナントを持っています。ビジュアルクエリを使用して2つのテーブルを結合する予定です。
クエリが両方のテーブルに存在するすべての行を返すようにする必要があります。どのタイプの結合を使用すればよいでしょうか?
Correct Answer: B 🗳️
Fabricテナントには、Lakehouse1という名前の湖畔施設が含まれています。Lakehouse1には、8つの列を持つDeltaテーブルがあります。同じ8つの列に加えて2つの列を含む新しいデータを受け取ります。
Spark DataFrameを作成し、そのDataFrameをdfという名前の変数に代入します。DataFrameには新しいデータが含まれています。次の要件を満たすために、新しいデータをDeltaテーブルに追加する必要があります。
* 既存の行をすべて保持します。
* すべての新しいデータがテーブルに追加されていることを確認してください。
コードをどのように完成させればよいでしょうか?回答するには、回答欄で適切な選択肢を選んでください。
Correct Answer:

Explanation:
o add new data to the Delta table while meeting the specified requirements:
You should use the append mode to ensure that all new data is added to the table without affecting the existing rows.
You should set the mergeSchema option to true to allow the schema of the Delta table to be updated with the new columns found in the DataFrame.
The completed code would look like this:
df.write.format( " delta " ).mode( " append " )
option( " mergeSchema " , " true " )
saveAsTable( " Lakehouse1.TableName " )
Fabric のイベントハウス「Eventhousel」には、「Weatherdata」という名前のテーブルが含まれています。Weatherdata に含まれるデータのサンプルを次の表に示します。
あなたはKQLクエリセットを使用してEventhouse1のデータを操作する予定です。結果セットには以下の列が含まれている必要があります。
クエリを作成する必要があります。
どの4つのKQLステートメントを順番に使用すべきでしょうか?回答するには、ステートメントのリストから適切なステートメントを回答欄に移動させ、正しい順序に並べ替えてください。
Correct Answer:

Explanation:
Comprehensive Detailed Explanation
Step 1: Understanding the requirement
We need a KQL query that:
Reads data from Weatherdata.
Orders by Datetime.
Calculates Delta_temperature as the difference between the current row and the preceding row.
Returns the final columns: Datetime, Lat, Long, Temperature, Delta_temperature.
Step 2: Evaluate the provided statements
Weatherdata # Starts the query with the source table.
| sort by Datetime asc # Ensures chronological order, required for prev() to work correctly.
| extend Delta_temperature = Temperature - prev(Temperature) # Computes difference between the current row and the previous row's temperature.
| project Datetime, Lat, Long, Temperature, Delta_temperature # Selects the required output columns.
Step 3: Incorrect choices (to avoid)
next(Temperature,1) # Would calculate the difference with the next row, not the previous.
prev(Temperature,2) # Would skip one row, giving the difference with two rows back, which is not needed.
summarize ... by Datetime # Aggregates the data; not required here since we just need row-level differences.
Step 4: Final Correct Sequence
Weatherdata
| sort by Datetime asc
| extend Delta_temperature = Temperature - prev(Temperature)
| project Datetime, Lat, Long, Temperature, Delta_temperature
References
prev() function in KQL
extend operator in KQL
project operator in KQL
Workspace1 という名前の Fabric ワークスペースがあり、そこには Dataflow1 という名前のデータフローが含まれています。
Dataflow1 には 2,000 行を返すクエリがあります。
次の図に示すように、Power Query でクエリを表示します。
pickupLongitude 列について何がわかりますか?
Correct Answer: C 🗳️
Explanation: Only visible for Pass4guide members. You can sign-up / login (it's free).
Fabricテナントには、Workspace1という名前のワークスペースが含まれています。Workspace1はProライセンスモードを使用しており、Model1という名前のセマンティックモデルが含まれています。Model1がXMLA接続をサポートしていることを確認する必要があります。
どの設定を変更すればよいですか?
Correct Answer: A 🗳️
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