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質問 1：
A junior data engineer is working to implement logic for a Lakehouse table named silver_device_recordings.
The source data contains 100 unique fields in a highly nested JSON structure.
The silver_device_recordings table will be used downstream for highly selective joins on a number of fields, and will also be leveraged by the machine learning team to filter on a handful of relevant fields, in total, 15 fields have been identified that will often be used for filter and join logic.
The data engineer is trying to determine the best approach for dealing with these nested fields before declaring the table schema.
Which of the following accurately presents information about Delta Lake and Databricks that may Impact their decision-making process?
A. Tungsten encoding used by Databricks is optimized for storing string data: newly-added native support for querying JSON strings means that string types are always most efficient.
B. By default Delta Lake collects statistics on the first 32 columns in a table; these statistics are leveraged for data skipping when executing selective queries.
C. Schema inference and evolution on Databricks ensure that inferred types will always accurately match the data types used by downstream systems.
D. Because Delta Lake uses Parquet for data storage, Dremel encoding information for nesting can be directly referenced by the Delta transaction log.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
質問 2：
An upstream system is emitting change data capture (CDC) logs that are being written to a cloud object storage directory. Each record in the log indicates the change type (insert, update, or delete) and the values for each field after the change. The source table has a primary key identified by the field pk_id.
For auditing purposes, the data governance team wishes to maintain a full record of all values that have ever been valid in the source system. For analytical purposes, only the most recent value for each record needs to be recorded. The Databricks job to ingest these records occurs once per hour, but each individual record may have changed multiple times over the course of an hour.
Which solution meets these requirements?
A. Use merge into to insert, update, or delete the most recent entry for each pk_id into a bronze table, then propagate all changes throughout the system.
B. Iterate through an ordered set of changes to the table, applying each in turn; rely on Delta Lake's versioning ability to create an audit log.
C. Create a separate history table for each pk_id resolve the current state of the table by running a union all filtering the history tables for the most recent state.
D. Ingest all log information into a bronze table; use merge into to insert, update, or delete the most recent entry for each pk_id into a silver table to recreate the current table state.
E. Use Delta Lake's change data feed to automatically process CDC data from an external system, propagating all changes to all dependent tables in the Lakehouse.
正解：A
解説: (Pass4Test メンバーにのみ表示されます)
質問 3：
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. The Delta log creates a term matrix for free text fields to support selective filtering.
B. Text data cannot be stored with Delta Lake.
C. ZORDER ON review will need to be run to see performance gains.
D. Delta Lake statistics are only collected on the first 4 columns in a table.
E. Delta Lake statistics are not optimized for free text fields with high cardinality.
正解：E
解説: (Pass4Test メンバーにのみ表示されます)
質問 4：
The security team is exploring whether or not the Databricks secrets module can be leveraged for connecting to an external database.
After testing the code with all Python variables being defined with strings, they upload the password to the secrets module and configure the correct permissions for the currently active user. They then modify their code to the following (leaving all other variables unchanged).
Which statement describes what will happen when the above code is executed?
A. The connection to the external table will fail; the string "redacted" will be printed.
B. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the encoded password will be saved to DBFS.
C. The connection to the external table will succeed; the string "redacted" will be printed.
D. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the password will be printed in plain text.
E. The connection to the external table will succeed; the string value of password will be printed in plain text.
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 5：
A distributed team of data analysts share computing resources on an interactive cluster with autoscaling configured. In order to better manage costs and query throughput, the workspace administrator is hoping to evaluate whether cluster upscaling is caused by many concurrent users or resource-intensive queries.
In which location can one review the timeline for cluster resizing events?
A. Executor's log file
B. Ganglia
C. Workspace audit logs
D. Driver's log file
E. Cluster Event Log
正解：B
質問 6：
The data engineer team has been tasked with configured connections to an external database that does not have a supported native connector with Databricks. The external database already has data security configured by group membership. These groups map directly to user group already created in Databricks that represent various teams within the company.
A new login credential has been created for each group in the external database. The Databricks Utilities Secrets module will be used to make these credentials available to Databricks users.
Assuming that all the credentials are configured correctly on the external database and group membership is properly configured on Databricks, which statement describes how teams can be granted the minimum necessary access to using these credentials?
A. ''Read'' permissions should be set on a secret key mapped to those credentials that will be used by a given team.
B. "Manage" permission should be set on a secret scope containing only those credentials that will be used by a given team.
C. No additional configuration is necessary as long as all users are configured as administrators in the workspace where secrets have been added.
D. "Read" permissions should be set on a secret scope containing only those credentials that will be used by a given team.
正解：D
A junior data engineer is working to implement logic for a Lakehouse table named silver_device_recordings.
The source data contains 100 unique fields in a highly nested JSON structure.
The silver_device_recordings table will be used downstream for highly selective joins on a number of fields, and will also be leveraged by the machine learning team to filter on a handful of relevant fields, in total, 15 fields have been identified that will often be used for filter and join logic.
The data engineer is trying to determine the best approach for dealing with these nested fields before declaring the table schema.
Which of the following accurately presents information about Delta Lake and Databricks that may Impact their decision-making process?
A. Tungsten encoding used by Databricks is optimized for storing string data: newly-added native support for querying JSON strings means that string types are always most efficient.
B. By default Delta Lake collects statistics on the first 32 columns in a table; these statistics are leveraged for data skipping when executing selective queries.
C. Schema inference and evolution on Databricks ensure that inferred types will always accurately match the data types used by downstream systems.
D. Because Delta Lake uses Parquet for data storage, Dremel encoding information for nesting can be directly referenced by the Delta transaction log.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
質問 2：
An upstream system is emitting change data capture (CDC) logs that are being written to a cloud object storage directory. Each record in the log indicates the change type (insert, update, or delete) and the values for each field after the change. The source table has a primary key identified by the field pk_id.
For auditing purposes, the data governance team wishes to maintain a full record of all values that have ever been valid in the source system. For analytical purposes, only the most recent value for each record needs to be recorded. The Databricks job to ingest these records occurs once per hour, but each individual record may have changed multiple times over the course of an hour.
Which solution meets these requirements?
A. Use merge into to insert, update, or delete the most recent entry for each pk_id into a bronze table, then propagate all changes throughout the system.
B. Iterate through an ordered set of changes to the table, applying each in turn; rely on Delta Lake's versioning ability to create an audit log.
C. Create a separate history table for each pk_id resolve the current state of the table by running a union all filtering the history tables for the most recent state.
D. Ingest all log information into a bronze table; use merge into to insert, update, or delete the most recent entry for each pk_id into a silver table to recreate the current table state.
E. Use Delta Lake's change data feed to automatically process CDC data from an external system, propagating all changes to all dependent tables in the Lakehouse.
正解：A
解説: (Pass4Test メンバーにのみ表示されます)
質問 3：
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. The Delta log creates a term matrix for free text fields to support selective filtering.
B. Text data cannot be stored with Delta Lake.
C. ZORDER ON review will need to be run to see performance gains.
D. Delta Lake statistics are only collected on the first 4 columns in a table.
E. Delta Lake statistics are not optimized for free text fields with high cardinality.
正解：E
解説: (Pass4Test メンバーにのみ表示されます)
質問 4：
The security team is exploring whether or not the Databricks secrets module can be leveraged for connecting to an external database.
After testing the code with all Python variables being defined with strings, they upload the password to the secrets module and configure the correct permissions for the currently active user. They then modify their code to the following (leaving all other variables unchanged).
Which statement describes what will happen when the above code is executed?
A. The connection to the external table will fail; the string "redacted" will be printed.
B. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the encoded password will be saved to DBFS.
C. The connection to the external table will succeed; the string "redacted" will be printed.
D. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the password will be printed in plain text.
E. The connection to the external table will succeed; the string value of password will be printed in plain text.
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 5：
A distributed team of data analysts share computing resources on an interactive cluster with autoscaling configured. In order to better manage costs and query throughput, the workspace administrator is hoping to evaluate whether cluster upscaling is caused by many concurrent users or resource-intensive queries.
In which location can one review the timeline for cluster resizing events?
A. Executor's log file
B. Ganglia
C. Workspace audit logs
D. Driver's log file
E. Cluster Event Log
正解：B
質問 6：
The data engineer team has been tasked with configured connections to an external database that does not have a supported native connector with Databricks. The external database already has data security configured by group membership. These groups map directly to user group already created in Databricks that represent various teams within the company.
A new login credential has been created for each group in the external database. The Databricks Utilities Secrets module will be used to make these credentials available to Databricks users.
Assuming that all the credentials are configured correctly on the external database and group membership is properly configured on Databricks, which statement describes how teams can be granted the minimum necessary access to using these credentials?
A. ''Read'' permissions should be set on a secret key mapped to those credentials that will be used by a given team.
B. "Manage" permission should be set on a secret scope containing only those credentials that will be used by a given team.
C. No additional configuration is necessary as long as all users are configured as administrators in the workspace where secrets have been added.
D. "Read" permissions should be set on a secret scope containing only those credentials that will be used by a given team.
正解：D
小川** -
きっちりと情報がまとまっているし読みやすいです。Databricks-Certified-Professional-Data-Engineer知識も経験も無しにいきなりこの試験から受けるという方はいないでしょうし、これで十分だとは思いますが。