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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

Section	Weight	Objectives
Data Modeling and Storage	20%	- Data Modeling - File Formats - Storage Optimization
Monitoring and Troubleshooting	16%	- Monitoring - Troubleshooting - Performance Optimization
Data Quality and Governance	12%	- Governance - Data Quality - Data Lineage
Data Processing	28%	- Spark SQL - Structured Streaming - Data Transformation - ETL Pipelines
Databricks Lakehouse Platform	24%	- Delta Lake - Data Management - Lakehouse Architecture - Unity Catalog

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최신 Databricks Certification Databricks-Certified-Data-Engineer-Professional 무료샘플문제 (Q165-Q170):

질문 # 165
The data governance team is reviewing code used for deleting records for compliance with GDPR. They note the following logic is used to delete records from the Delta Lake table named users.

Assuming that user_id is a unique identifying key and that delete_requests contains all users that have requested deletion, which statement describes whether successfully executing the above logic guarantees that the records to be deleted are no longer accessible and why?

A. Yes; the Delta cache immediately updates to reflect the latest data files recorded to disk.
B. No; the Delta Lake delete command only provides ACID guarantees when combined with the merge into command.
C. No; files containing deleted records may still be accessible with time travel until a vacuum command is used to remove invalidated data files.
D. No; the Delta cache may return records from previous versions of the table until the cluster is restarted.
E. Yes; Delta Lake ACID guarantees provide assurance that the delete command succeeded fully and permanently purged these records.

정답：C

설명：
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from Explanation:
The code uses the DELETE FROM command to delete records from the users table that match a condition based on a join with another table called delete_requests, which contains all users that have requested deletion. The DELETE FROM command deletes records from a Delta Lake table by creating a new version of the table that does not contain the deleted records. However, this does not guarantee that the records to be deleted are no longer accessible, because Delta Lake supports time travel, which allows querying previous versions of the table using a timestamp or version number. Therefore, files containing deleted records may still be accessible with time travel until a vacuum command is used to remove invalidated data files from physical storage.

질문 # 166
A view is registered with the following code:

Both users and orders are Delta Lake tables.
Which statement describes the results of querying recent_orders?

A. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
B. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
C. All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.
D. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.

정답：B

질문 # 167
A table is registered with the following code:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from

Both users and orders are Delta Lake tables. Which statement describes the results of querying recent_orders?

A. Results will be computed and cached when the table is defined; these cached results will incrementally update as new records are inserted into source tables.
B. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
C. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
D. All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.
E. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.

정답：D

설명：
Table is created and data of join will be stored on DBFS and it will be returned on query time.

질문 # 168
A Data Engineer is building a fraud detection pipeline that calls out to Open AI, via a Python library, and needs to include an access token when using the API. Which Databricks CLI command should the Data Engineer use to create the secret?

A. databricks tokens put-token KEY SCOPE; dbutils.secrets.get (KEY, SCOPE)
B. databricks secrets put-secret KEY SCOPE; dbutils.secrets.get (KEY, SCOPE)
C. databricks secrets put-secret SCOPE KEY; dbutils.secrets.get (SCOPE, KEY)
D. databricks tokens put-token SCOPE KEY; dbutils.tokens.get (SCOPE, KEY)

정답：C

설명：
The Databricks CLI command databricks secrets put-secret <scope> <key> is used to securely store sensitive values such as API access tokens in a secret scope. The secret can then be retrieved at runtime using dbutils.secrets.get(scope, key), ensuring credentials are not hard- coded and remain protected.

질문 # 169
A Delta Lake table was created with the below query:

Realizing that the original query had a typographical error, the below code was executed:
ALTER TABLE prod.sales_by_stor RENAME TO prod.sales_by_store
Which result will occur after running the second command?

A. The table reference in the metastore is updated and all data files are moved.
B. A new Delta transaction log Is created for the renamed table.
C. The table name change is recorded in the Delta transaction log.
D. All related files and metadata are dropped and recreated in a single ACID transaction.
E. The table reference in the metastore is updated and no data is changed.

정답：E

설명：
The query uses the CREATE TABLE USING DELTA syntax to create a Delta Lake table from an existing Parquet file stored in DBFS. The query also uses the LOCATION keyword to specify the path to the Parquet file as /mnt/finance_eda_bucket/tx_sales.parquet. By using the LOCATION keyword, the query creates an external table, which is a table that is stored outside of the default warehouse directory and whose metadata is not managed by Databricks. An external table can be created from an existing directory in a cloud storage system, such as DBFS or S3, that contains data files in a supported format, such as Parquet or CSV.
The result that will occur after running the second command is that the table reference in the metastore is updated and no data is changed. The metastore is a service that stores metadata about tables, such as their schema, location, properties, and partitions. The metastore allows users to access tables using SQL commands or Spark APIs without knowing their physical location or format. When renaming an external table using the ALTER TABLE RENAME TO command, only the table reference in the metastore is updated with the new name; no data files or directories are moved or changed in the storage system. The table will still point to the same location and use the same format as before. However, if renaming a managed table, which is a table whose metadata and data are both managed by Databricks, both the table reference in the metastore and the data files in the default warehouse directory are moved and renamed accordingly.

질문 # 170
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