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唯一無二Databricks-Certified-Data-Engineer-Associate認定内容 |最初の試行で簡単に勉強して試験に合格する &信頼できるDatabricks Databricks Certified Data Engineer Associate Exam
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ほとんどの労働者の基準はますます高くなることがわかっているため、Databricks-Certified-Data-Engineer-Associateガイドの質問にも高い目標を設定しています。市場にある他の練習教材とは異なり、当社のトレーニング教材はお客様の関心を他のポイントの前に置き、私たちをずっと高度な学習教材にコミットさせます。これまで、最も複雑なDatabricks-Certified-Data-Engineer-Associateガイドの質問を簡素化し、簡単な操作システムを設計しました。Databricks-Certified-Data-Engineer-Associate試験問題の自然でシームレスなユーザーインターフェイスは、より流fluentに成長しました。使いやすさ。
Databricks認定データエンジニアアソシエイトになるには、Databricksのアーキテクチャ、データモデリング、データ処理、およびデータ統合の知識をテストする厳しい試験に合格する必要があります。この試験は60問の多肢選択問題から構成され、90分以内に受験する必要があります。試験に合格するためには、少なくとも70%のスコアを取得する必要があり、認定を取得することができます。
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今の多くのIT者が参加している試験に、DatabricksのDatabricks-Certified-Data-Engineer-Associate認定試験「Databricks Certified Data Engineer Associate Exam」がとても人気がある一つとして、合格するために豊富な知識と経験が必要です。DatabricksのDatabricks-Certified-Data-Engineer-Associate認定試験に準備する練習ツールや訓練機関に通学しなればまりませんでしょう。Xhs1991は君のもっともよい選択ですよ。多くIT者になりたい方にDatabricksのDatabricks-Certified-Data-Engineer-Associate認定試験に関する問題集を準備しております。君に短い時間に大量のITの専門知識を補充させています。
Databricks Certified Data Engineer Associate Exam 認定 Databricks-Certified-Data-Engineer-Associate 試験問題 (Q89-Q94):
質問 # 89
A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to a data analytics dashboard for a retail use case. The job has a Databricks SQL query that returns the number of store-level records where sales is equal to zero. The data engineer wants their entire team to be notified via a messaging webhook whenever this value is greater than 0.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of stores with $0 in sales is greater than zero?
- A. They can set up an Alert with a new webhook alert destination.
- B. They can set up an Alert without notifications.
- C. They can set up an Alert with a new email alert destination.
- D. They can set up an Alert with a custom template.
- E. They can set up an Alert with one-time notifications.
正解:A
解説:
A webhook alert destination is a notification destination that allows Databricks to send HTTP POST requests to a third-party endpoint when an alert is triggered. This enables the data engineer to integrate Databricks alerts with their preferred messaging or collaboration platform, such as Slack, Microsoft Teams, or PagerDuty.
To set up a webhook alert destination, the data engineer needs to create and configure a webhook connector in their messaging platform, and then add the webhook URL to the Databricks notification destination. After that, the data engineer can create an alert for their Databricks SQL query, and select the webhook alert destination as the notification destination. The alert can be configured with a custom condition, such as when the number of stores with $0 in sales is greater than zero, and a custom message template, such as "Alert:
{number_of_stores} stores have $0 in sales". The alert can also be configured with a recurrence interval, such as every hour, to check the query result periodically. When the alert condition is met, the data engineer and their team will receive a notification via the messaging webhook, with the custom message and a link to the Databricks SQL query. The other options are either not suitable for sending notifications via a messaging webhook (A, B, E), or not suitable for sending recurring notifications . References: Databricks Documentation -Manage notification destinations, Databricks Documentation - Create alerts for Databricks SQL queries, Databricks Documentation - Configure alert conditions and messages.
質問 # 90
Which of the following data lakehouse features results in improved data quality over a traditional data lake?
- A. A data lakehouse stores data in open formats.
- B. A data lakehouse allows the use of SQL queries to examine data.
- C. A data lakehouse enables machine learning and artificial Intelligence workloads.
- D. A data lakehouse provides storage solutions for structured and unstructured data.
- E. A data lakehouse supports ACID-compliant transactions.
正解:B
質問 # 91
A data engineer has created a new database using the following command:
CREATE DATABASE IF NOT EXISTS customer360;
In which of the following locations will the customer360 database be located?
- A. dbfs:/user/hive/warehouse
- B. dbfs:/user/hive/database/customer360
- C. More information is needed to determine the correct response
- D. dbfs:/user/hive/customer360
正解:A
解説:
dbfs:/user/hive/warehouse Thereby showing "dbfs:/user/hive/warehouse/customer360.db The location of the customer360 database depends on the value of the spark.sql.warehouse.dir configuration property, which specifies the default location for managed databases and tables. If the property is not set, the default value is dbfs:/user/hive/warehouse. Therefore, the customer360 database will be located in dbfs:/user/hive/warehouse/customer360.db. However, if the property is set to a different value, such as dbfs:/user/hive/database, then the customer360 database will be located in dbfs:/user/hive/database/customer360.db. Thus, more information is needed to determine the correct response.
Option A is not correct, as dbfs:/user/hive/database/customer360 is not the default location for managed databases and tables, unless the spark.sql.warehouse.dir property is explicitly set to dbfs:/user/hive/database.
Option B is not correct, as dbfs:/user/hive/warehouse is the default location for the root directory of managed databases and tables, not for a specific database. The database name should be appended with .db to the directory path, such as dbfs:/user/hive/warehouse/customer360.db.
Option C is not correct, as dbfs:/user/hive/customer360 is not a valid location for a managed database, as it does not follow the directory structure specified by the spark.sql.warehouse.dir property.
Reference:
Databases and Tables
[Databricks Data Engineer Professional Exam Guide]
質問 # 92
A data engineer runs a statement every day to copy the previous day's sales into the table transactions. Each day's sales are in their own file in the location "/transactions/raw".
Today, the data engineer runs the following command to complete this task:
After running the command today, the data engineer notices that the number of records in table transactions has not changed.
Which of the following describes why the statement might not have copied any new records into the table?
- A. The COPY INTO statement requires the table to be refreshed to view the copied rows.
- B. The previous day's file has already been copied into the table.
- C. The names of the files to be copied were not included with the FILES keyword.
- D. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.
- E. The PARQUET file format does not support COPY INTO.
正解:B
解説:
The COPY INTO statement is an idempotent operation, which means that it will skip any files that have already been loaded into the target table1. This ensures that the data is not duplicated or corrupted by multiple attempts to load the same file. Therefore, if the data engineer runs the same command every day without specifying the names of the files to be copied with the FILES keyword or a glob pattern with the PATTERN keyword, the statement will only copy the first file that matches the source location and ignore the rest. To avoid this problem, the data engineer should either use the FILES or PATTERN keywords to filter the files to be copied based on the date or some other criteria, or delete the files from the source location after they are copied into the table2. References: 1: COPY INTO | Databricks on AWS 2: Get started using COPY INTO to load data | Databricks on AWS
質問 # 93
A data engineer has a Python notebook in Databricks, but they need to use SQL to accomplish a specific task within a cell. They still want all of the other cells to use Python without making any changes to those cells.
Which of the following describes how the data engineer can use SQL within a cell of their Python notebook?
- A. They can change the default language of the notebook to SQL
- B. They can simply write SQL syntax in the cell
- C. They can attach the cell to a SQL endpoint rather than a Databricks cluster
- D. They can add %sql to the first line of the cell
- E. It is not possible to use SQL in a Python notebook
正解:D
質問 # 94
......
Xhs1991のDatabricksのDatabricks-Certified-Data-Engineer-Associate試験トレーニング資料はあなたに時間とエネルギーを節約させます。あなたが何ヶ月でやる必要があることを我々はやってさしあげましたから。あなたがするべきことは、Xhs1991のDatabricksのDatabricks-Certified-Data-Engineer-Associate試験トレーニング資料に受かるのです。あなた自身のために、証明書をもらいます。Xhs1991 はあなたに必要とした知識と経験を提供して、DatabricksのDatabricks-Certified-Data-Engineer-Associate試験の目標を作ってあげました。Xhs1991を利用したら、試験に合格しないことは絶対ないです。
Databricks-Certified-Data-Engineer-Associate復習攻略問題: https://www.xhs1991.com/Databricks-Certified-Data-Engineer-Associate.html
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