DATABRICKS DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE RELIABLE BRAINDUMPS SHEET | VALID DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE EXAM QUESTIONS

Databricks Databricks-Certified-Data-Engineer-Associate Reliable Braindumps Sheet | Valid Databricks-Certified-Data-Engineer-Associate Exam Questions

Databricks Databricks-Certified-Data-Engineer-Associate Reliable Braindumps Sheet | Valid Databricks-Certified-Data-Engineer-Associate Exam Questions

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In today's rapid economic development, society has also put forward higher and higher requirements for us. In addition to the necessary theoretical knowledge, we need more skills. Our Databricks-Certified-Data-Engineer-Associate exam simulation is a great tool to improve our competitiveness. After we use our Databricks-Certified-Data-Engineer-Associate Study Materials, we can get the Databricks-Certified-Data-Engineer-Associate certification faster. And at the same time, we can do a better job since we have learned more knowledge on the subject.

The Databricks Certified Data Engineer Associate Exam certification exam focuses on various topics related to data engineering, including data ingestion, data processing, data warehousing, and data analytics. It also covers the fundamentals of big data processing and distributed computing, making it an ideal certification for professionals who want to work with large-scale data sets.

The GAQM Databricks-Certified-Data-Engineer-Associate exam is an essential certification for data engineers looking to demonstrate their expertise in working with the Databricks platform. It is recognized globally and is a highly versatile qualification that can be applied to a range of different roles and industries. With the right preparation and training, candidates can pass the exam and take their careers to the next level in the field of big data and analytics.

The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) certification exam is a credential that certifies individuals in their ability to design, develop, and manage data pipelines using Databricks. It is a globally recognized certification that validates the skills and knowledge required to work with big data processing and analytics using Databricks.

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q80-Q85):

NEW QUESTION # 80
A data engineer is using the following code block as part of a batch ingestion pipeline to read from a composable table:

Which of the following changes needs to be made so this code block will work when the transactions table is a stream source?

  • A. Replace schema(schema) with option ("maxFilesPerTrigger", 1)
  • B. Replace format("delta") with format("stream")
  • C. Replace "transactions" with the path to the location of the Delta table
  • D. Replace predict with a stream-friendly prediction function
  • E. Replace spark.read with spark.readStream

Answer: E

Explanation:
To read from a stream source, the data engineer needs to use the spark.readStream method instead of the spark.read method. The spark.readStream method returns a DataStreamReader object that can be used to specify the details of the input source, such as the format, the schema, the path, and the options. The spark.read method is only suitable for batch processing, not streaming processing. The other changes are not necessary or correct for reading from a stream source. References: Structured Streaming Programming Guide, Read a stream, Databricks Data Sources


NEW QUESTION # 81
A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following commands could the data engineering team use to access sales in PySpark?

  • A. spark.table("sales")
  • B. spark.sql("sales")
  • C. There is no way to share data between PySpark and SQL.
  • D. SELECT * FROM sales
  • E. spark.delta.table("sales")

Answer: A

Explanation:
Explanation
https://spark.apache.org/docs/3.2.1/api/python/reference/api/pyspark.sql.SparkSession.table.html


NEW QUESTION # 82
A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to an ELT job. The ELT job has its Databricks SQL query that returns the number of input records containing unexpected NULL values. The data engineer wants their entire team to be notified via a messaging webhook whenever this value reaches 100.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of NULL values reaches 100?

  • A. They can set up an Alert with one-time notifications.
  • B. They can set up an Alert with a new email alert destination.
  • C. They can set up an Alert without notifications.
  • D. They can set up an Alert with a new webhook alert destination.
  • E. They can set up an Alert with a custom template.

Answer: D

Explanation:
A webhook alert destination is a way to send notifications to external applications or services via HTTP requests. A data engineer can use a webhook alert destination to notify their entire team via a messaging webhook, such as Slack or Microsoft Teams, whenever the number of NULL values in the input data reaches
100. To set up a webhook alert destination, the data engineer needs to do the following steps:
* In the Databricks SQL workspace, navigate to the Settings gear icon and select SQL Admin Console.
* Click Alert Destinations and click Add New Alert Destination.
* Select Webhook and enter the webhook URL and the optional custom template for the notification message.
* Click Create to save the webhook alert destination.
* In the Databricks SQL editor, create or open the query that returns the number of input records containing unexpected NULL values.
* Click the Create Alert icon above the editor window and configure the alert criteria, such as the value column, the condition, and the threshold.
* In the Notification section, select the webhook alert destination that was created earlier and click Create Alert. References: What are Databricks SQL alerts?, Monitor alerts, Monitoring Your Business with Alerts, Using Automation Runbook Webhooks To Alert on Databricks Status Updates.


NEW QUESTION # 83
A data engineer needs to use a Delta table as part of a data pipeline, but they do not know if they have the appropriate permissions.
In which of the following locations can the data engineer review their permissions on the table?

  • A. Jobs
  • B. Data Explorer
  • C. Dashboards
  • D. Databricks Filesystem
  • E. Repos

Answer: B

Explanation:
Data Explorer is a graphical interface that allows you to browse, create, and manage data objects such as databases, tables, and views in your workspace. You can also review and modify the permissions on these data objects using Data Explorer. To access Data Explorer, you can click on the Data icon in the sidebar, or use the %sql magic command in a notebook. You can then select a database and a table, and click on the Permissions tab to view and edit the access control lists (ACLs) for the table. You can also use SQL commands such as SHOW GRANT and GRANT to query and modify the permissions on a Delta table. Reference:
Data Explorer
Access control for Delta tables
SHOW GRANT
[GRANT]


NEW QUESTION # 84
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.
The code block used by the data engineer is below:

If the data engineer only wants the query to process all of the available data in as many batches as required, which of the following lines of code should the data engineer use to fill in the blank?

  • A. trigger(continuous="once")
  • B. trigger(parallelBatch=True)
  • C. trigger(processingTime="once")
  • D. processingTime(1)
  • E. trigger(availableNow=True)

Answer: E

Explanation:
https://spark.apache.org/docs/latest/api/python/reference/pyspark.ss/api/pyspark.sql.streaming.DataStreamWriter.trigger.html


NEW QUESTION # 85
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