Databricks-Certified-Data-Engineer-Professional無料問題集「Databricks Certified Data Engineer Professional」

質問 1

The data governance team has instituted a requirement that all tables containing Personal Identifiable Information (PH) must be clearly annotated. This includes adding column comments, table comments, and setting the custom table property "contains_pii" = true.
The following SQL DDL statement is executed to create a new table:
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Which command allows manual confirmation that these three requirements have been met?

（A）DESCRIBE EXTENDED dev.pii test

（B）SHOW TBLPROPERTIES dev.pii test

（C）DESCRIBE DETAIL dev.pii test

（D）DESCRIBE HISTORY dev.pii test

（E）SHOW TABLES dev

正解：A 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 2

The data engineer team is configuring environment for development testing, and production before beginning migration on a new data pipeline. The team requires extensive testing on both the code and data resulting from code execution, and the team want to develop and test against similar production data as possible.
A junior data engineer suggests that production data can be mounted to the development testing environments, allowing pre production code to execute against production data. Because all users have Admin privileges in the development environment, the junior data engineer has offered to configure permissions and mount this data for the team.
Which statement captures best practices for this situation?

（A）In environments where interactive code will be executed, production data should only be accessible with read permissions; creating isolated databases for each environment further reduces risks.

（B）Because delta Lake versions all data and supports time travel, it is not possible for user error or malicious actors to permanently delete production data, as such it is generally safe to mount production data anywhere.

（C）All developer, testing and production code and data should exist in a single unified workspace; creating separate environments for testing and development further reduces risks.

（D）Because access to production data will always be verified using passthrough credentials it is safe to mount data to any Databricks development environment.

正解：A 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 3

A junior member of the data engineering team is exploring the language interoperability of Databricks notebooks. The intended outcome of the below code is to register a view of all sales that occurred in countries on the continent of Africa that appear in the geo_lookup table.
Before executing the code, running SHOW TABLES on the current database indicates the database contains only two tables: geo_lookup and sales.
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Which statement correctly describes the outcome of executing these command cells in order in an interactive notebook?

（A）Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable representing a PySpark DataFrame.

（B）Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable containing a list of strings.

（C）Both commands will succeed. Executing show tables will show that countries at and sales at have been registered as views.

（D）Both commands will fail. No new variables, tables, or views will be created.

（E）Cmd 1 will succeed. Cmd 2 will search all accessible databases for a table or view named countries af: if this entity exists, Cmd 2 will succeed.

正解：B 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 4

A junior data engineer is migrating a workload from a relational database system to the Databricks Lakehouse. The source system uses a star schema, leveraging foreign key constrains and multi-table inserts to validate records on write.
Which consideration will impact the decisions made by the engineer while migrating this workload?

（A）Databricks supports Spark SQL and JDBC; all logic can be directly migrated from the source system without refactoring.

（B）Committing to multiple tables simultaneously requires taking out multiple table locks and can lead to a state of deadlock.

（C）All Delta Lake transactions are ACID compliance against a single table, and Databricks does not enforce foreign key constraints.

（D）Databricks only allows foreign key constraints on hashed identifiers, which avoid collisions in highly-parallel writes.

（E）Foreign keys must reference a primary key field; multi-table inserts must leverage Delta Lake's upsert functionality.

正解：C 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 5

The data science team has requested assistance in accelerating queries on free form text from user reviews. The data is currently stored in Parquet with the below schema:
item_id INT, user_id INT, review_id INT, rating FLOAT, review STRING
The review column contains the full text of the review left by the user. Specifically, the data science team is looking to identify if any of 30 key words exist in this field.
A junior data engineer suggests converting this data to Delta Lake will improve query performance.
Which response to the junior data engineer s suggestion is correct?

（A）Text data cannot be stored with Delta Lake.

（B）Delta Lake statistics are only collected on the first 4 columns in a table.

（C）The Delta log creates a term matrix for free text fields to support selective filtering.

（D）ZORDER ON review will need to be run to see performance gains.

（E）Delta Lake statistics are not optimized for free text fields with high cardinality.

正解：E 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 6

A data pipeline uses Structured Streaming to ingest data from kafka to Delta Lake. Data is being stored in a bronze table, and includes the Kafka_generated timesamp, key, and value. Three months after the pipeline is deployed the data engineering team has noticed some latency issued during certain times of the day.
A senior data engineer updates the Delta Table's schema and ingestion logic to include the current timestamp (as recoded by Apache Spark) as well the Kafka topic and partition. The team plans to use the additional metadata fields to diagnose the transient processing delays.
Which limitation will the team face while diagnosing this problem?

（A）New fields cannot be added to a production Delta table.

（B）Updating the table schema will invalidate the Delta transaction log metadata.

（C）New fields not be computed for historic records.

（D）Updating the table schema requires a default value provided for each file added.
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（E）Spark cannot capture the topic partition fields from the kafka source.

正解：C 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 7

The marketing team is looking to share data in an aggregate table with the sales organization, but the field names used by the teams do not match, and a number of marketing specific fields have not been approval for the sales org.
Which of the following solutions addresses the situation while emphasizing simplicity?

（A）Use a CTAS statement to create a derivative table from the marketing table configure a production jon to propagation changes.

（B）Add a parallel table write to the current production pipeline, updating a new sales table that varies Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from as required from marketing table.

（C）Instruct the marketing team to download results as a CSV and email them to the sales organization.

（D）Create a new table with the required schema and use Delta Lake's DEEP CLONE functionality to sync up changes committed to one table to the corresponding table.

（E）Create a view on the marketing table selecting only these fields approved for the sales team alias the names of any fields that should be standardized to the sales naming conventions.

正解：E 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 8

A Delta Lake table was created with the below query:

Consider the following query:
DROP TABLE prod.sales_by_store
If this statement is executed by a workspace admin, which result will occur?

（A）The table will be removed from the catalog and the data will be deleted.

（B）An error will occur because Delta Lake prevents the deletion of production data.

（C）Nothing will occur until a COMMIT command is executed.

（D）Data will be marked as deleted but still recoverable with Time Travel.

（E）The table will be removed from the catalog but the data will remain in storage.

正解：A 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 9

Assuming that the Databricks CLI has been installed and configured correctly, which Databricks CLI command can be used to upload a custom Python Wheel to object storage mounted with the DBFS for use with a production job?

正解：D 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 10

Which statement describes Delta Lake Auto Compaction?

（A）Data is queued in a messaging bus instead of committing data directly to memory; all data is committed from the messaging bus in one batch once the job is complete.

（B）Before a Jobs cluster terminates, optimize is executed on all tables modified during the most recent job.
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（C）Optimized writes use logical partitions instead of directory partitions; because partition boundaries are only represented in metadata, fewer small files are written.

（D）An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 128 MB.

（E）An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 1 GB.

正解：D 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

Databricks-Certified-Data-Engineer-Professional 無料問題集「Databricks Certified Data Engineer Professional」

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