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[Hardware] Get Updated New Databricks-Certified-Data-Engineer-Associate Test Pattern and Pa

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【Hardware】 Get Updated New Databricks-Certified-Data-Engineer-Associate Test Pattern and Pa

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Databricks Certified Data Engineer Associate certification is essential for individuals who want to work with big data and build scalable data pipelines. Databricks Certified Data Engineer Associate Exam certification exam covers a range of topics, including data modeling, data ingestion, data transformation, data storage, and data processing. Candidates will also be tested on their knowledge of Apache Spark, a popular open-source data processing engine, and Databricks Unified Analytics Platform.
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Databricks Certified Data Engineer Associate Exam Sample Questions (Q34-Q39):NEW QUESTION # 34
A data engineer at a company that uses Databricks with Unity Catalog needs to share a collection of tables with an external partner who also uses a Databricks workspace enabled for Unity Catalog. The data engineer decides to use Delta Sharing to accomplish this.
What is the first piece of information the data engineer should request from the external partner to set up Delta Sharing?
  • A. The sharing identifier of their Unity Catalog metastore
  • B. The IP address of their Databricks workspace
  • C. Their Databricks account password
  • D. The name of their Databricks cluster
Answer: A

NEW QUESTION # 35
A data architect has determined that a table of the following format is necessary:

Which of the following code blocks uses SQL DDL commands to create an empty Delta table in the above format regardless of whether a table already exists with this name?

  • A. Option E
  • B. Option A
  • C. Option D
  • D. Option B
  • E. Option C
Answer: A
Explanation:
References: Create a table using SQL | Databricks on AWS, Create a table using SQL - Azure Databricks, Delta Lake Quickstart - Azure Databricks

NEW QUESTION # 36
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. processingTime(1)
  • C. trigger(parallelBatch=True)
  • D. trigger(processingTime="once")
  • E. trigger(availableNow=True)
Answer: E
Explanation:
https://spark.apache.org/docs/la ... ng.DataStreamWriter

NEW QUESTION # 37
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 cade block used by the data engineer is below:

If the data engineer only wants the query to execute a micro-batch to process data every 5 seconds, which of the following lines of code should the data engineer use to fill in the blank?
  • A. trigger(processingTime="5 seconds")
  • B. trigger(once="5 seconds")
  • C. trigger()
  • D. trigger(continuous="5 seconds")
  • E. trigger("5 seconds")
Answer: A
Explanation:
The processingTime option specifies a time-based trigger interval for fixed interval micro-batches. This means that the query will execute a micro-batch to process data every 5 seconds, regardless of how much data is available. This option is suitable for near-real time processing workloads that require low latency and consistent processing frequency. The other options are either invalid syntax (A, C), default behavior (B), or experimental feature (E). References: Databricks Documentation - Configure Structured Streaming trigger intervals, Databricks Documentation - Trigger.

NEW QUESTION # 38
Which of the following must be specified when creating a new Delta Live Tables pipeline?
  • A. A key-value pair configuration
  • B. At least one notebook library to be executed
  • C. A path to cloud storage location for the written data
  • D. The preferred DBU/hour cost
  • E. A location of a target database for the written data
Answer: B
Explanation:
Option E is the correct answer because it is the only mandatory requirement when creating a new Delta Live Tables pipeline. A pipeline is a data processing workflow that contains materialized views and streaming tables declared in Python or SQL source files. Delta Live Tables infers the dependencies between these tables and ensures updates occur in the correct order. To create a pipeline, you need to specify at least one notebook library to be executed, which contains the Delta Live Tables syntax. You can also specify multiple libraries of different languages within your pipeline. The other options are optional or not applicable for creating a pipeline. Option A is not required, but you can optionally provide a key-value pair configuration to customize the pipeline settings, such as the storage location, the target schema, the notifications, and the pipeline mode.
Option B is not applicable, as the DBU/hour cost is determined by the cluster configuration, not the pipeline creation. Option C is not required, but you can optionally specify a storage location for the output data from the pipeline. If you leave it empty, the system uses a default location. Option D is not required, but you can optionally specify a location of a target database for the written data, either in the Hive metastore or the Unity Catalog.
Tutorial: Run your first Delta Live Tables pipeline, What is Delta Live Tables?, Create a pipeline, Pipeline configuration.

NEW QUESTION # 39
......
The Databricks Certified Data Engineer Associate Exam (Databricks-Certified-Data-Engineer-Associate) certification exam is one of the top-rated and career-oriented certificates that are designed to validate an Databricks professional's skills and knowledge level. These Databricks Certified Data Engineer Associate Exam (Databricks-Certified-Data-Engineer-Associate) practice questions have been inspiring those who want to prove their expertise with the industrial-recognized credential. By cracking it you can gain several personal and professional benefits.
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