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  1. Home
  2. Databricks Certification
  3. Databricks-Certified-Professional-Data-Engineer Exam
  4. Databricks.Databricks-Certified-Professional-Data-Engineer.v2025-10-27.q109 Dumps
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Question 31

A transactions table has been liquid clustered on the columns product_id, user_id, and event_date.
Which operation lacks support for cluster on write?

Correct Answer: A
Delta Lake'sLiquid Clusteringis an advanced feature that improves query performance by dynamically clustering data without requiring costly compaction steps like traditional Z-ordering.
When performing writes to aLiquid Clusteredtable, some write operations automatically maintain clustering, while othersdo not.
Explanation of Each Option:
* (A) spark.writestream.format('delta').mode('append') (Correct Answer)
* Reason:Streaming writes (writestream) donotsupportLiquid Clusteringbecause streaming data arrives in micro-batches.
* Since Liquid Clustering needs efficient global reorganization of files, streaming append operations don't provide sufficient data volume at a time to be effectively clustered.
* Delta Lake documentation states that Liquid Clustering is only supported for batch writes.
* (B) CTAS and RTAS statements
* Reason:CREATE TABLE AS SELECT (CTAS) and REPLACE TABLE AS SELECT (RTAS) are batch operationsand can enforce Liquid Clustering.
* These operations create or replace a table based on a query result, and since they are batch-based, Liquid Clustering applies.
* (C) INSERT INTO operations
* Reason:INSERT INTOis supportedfor Liquid Clustering because it is a batch operation.
* While it may not be as efficient as MERGE or COPY INTO, clustering is applied upon execution.
* (D) spark.write.format('delta').mode('append')
* Reason:Batch append operationsare supportedfor Liquid Clustering.
* Unlike streaming append, batch writes allow the optimizer to re-cluster data efficiently.
Conclusion:
Sincestreaming append operations do not support Liquid Clustering, option(A)is the correct answer.
References:
* Liquid Clustering in Delta Lake - Databricks Documentation
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Question 32

The Databricks CLI is use to trigger a run of an existing job by passing the job_id parameter. The response that the job run request has been submitted successfully includes a filed run_id.
Which statement describes what the number alongside this field represents?

Correct Answer: D
When triggering a job run using the Databricks CLI, the run_id field in the response represents a globally unique identifier for that particular run of the job. This run_id is distinct from the job_id. While the job_id identifies the job definition and is constant across all runs of that job, the run_id is unique to each execution and is used to track and query the status of that specific job run within the Databricks environment. This distinction allows users to manage and reference individual executions of a job directly.
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Question 33

Which of the following SQL keywords can be used to append new rows to an existing Delta table?

Correct Answer: D
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Question 34

Question-26. There are 5000 different color balls, out of which 1200 are pink color. What is the maximum
likelihood estimate for the proportion of "pink" items in the test set of color balls?

Correct Answer: C
Explanation
Given no additional information, the MLE for the probability of an item in the test set is exactly its frequency
in the training set. The method of maximum likelihood corresponds to many well-known estimation methods
in statistics. For example, one may be interested in the heights of adult female penguins, but be unable to
measure the height of every single penguin in a population due to cost or time constraints. Assuming that the
heights are normally (Gaussian) distributed with some unknown mean and variance, the mean and variance
can be estimated with MLE while only knowing the heights of some sample of the overall population. MLE
would accomplish this by taking the mean and variance as parameters and finding particular parametric values
that make the observed results the most probable (given the model).
In general, for a fixed set of data and underlying statistical model the method of maximum likelihood selects
the set of values of the model parameters that maximizes the likelihood function. Intuitively, this maximizes
the "agreement" of the selected model with the observed data, and for discrete random variables it indeed
maximizes the probability of the observed data under the resulting distribution. Maximum-likelihood
estimation gives a unified approach to estimation, which is well-defined in the case of the normal distribution
and many other problems. However in some complicated problems, difficulties do occur: in such problems,
maximum-likelihood estimators are unsuitable or do not exist.
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Question 35

A newly joined team member John Smith in the Marketing team who currently does not have any access to the data requires read access to customers table, which of the following statements can be used to grant access.

Correct Answer: C
Explanation
The answer is GRANT SELECT, USAGE ON TABLE customers TO [email protected] Data object privileges - Azure Databricks | Microsoft Docs
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