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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q87-Q92):

NEW QUESTION # 87
What are characteristics of the use of transactions in Snowflake? (Select TWO).

A. A transaction can be started explicitly by executing a begin work statement and end explicitly by executing a commit work statement.
B. A transaction can be started explicitly by executing a begin transaction statement and end explicitly by executing an end transaction statement.
C. Explicit transactions should contain only DML statements and query statements. All DDL statements implicitly commit active transactions.
D. Explicit transactions can contain DDL, DML, and query statements.
E. The autocommit setting can be changed inside a stored procedure.

Answer: A,D

Explanation:
A: Snowflake's transactions can indeed include DDL (Data Definition Language), DML (Data Manipulation Language), and query statements. When executed within a transaction block, they all contribute to the atomicity of the transaction-either all of them commit together or none at all.
C: Snowflake supports explicit transaction control through the use of the BEGIN TRANSACTION (or simply BEGIN) and COMMIT statements. Alternatively, the BEGIN WORK and COMMIT WORK syntax is also supported, which is a standard SQL syntax for initiating and ending transactions, respectively.
Note: The END TRANSACTION statement is not used in Snowflake to end a transaction; the correct statement is COMMIT or COMMIT WORK.

NEW QUESTION # 88
This privilege applies to only shared databases. It grants ability to enable roles other than the owning role to access a shared database.
Which is that role?

A. IMPORT SHARE
B. IMPORTED PRIVILEGES
C. SHARED PRIVILEGES

Answer: B

NEW QUESTION # 89
The IT Security team has identified that there is an ongoing credential stuffing attack on many of their organization's system.
What is the BEST way to find recent and ongoing login attempts to Snowflake?

A. View the Users section in the Account tab in the Snowflake UI and review the last login column.
B. View the History tab in the Snowflake UI and set up a filter for SQL text that contains the text "LOGIN".
C. Query the LOGIN_HISTORY view in the ACCOUNT_USAGE schema in the SNOWFLAKE database.
D. Call the LOGIN_HISTORY Information Schema table function.

Answer: C

Explanation:
This view can be used to query login attempts by Snowflake users within the last 365 days (1 year). It provides information such as the event timestamp, the user name, the client IP, the authentication method, the success or failure status, and the error code or message if the login attempt was unsuccessful. By querying this view, the IT Security team can identify any suspicious or malicious login attempts to Snowflake and take appropriate actions to prevent credential stuffing attacks1. The other options are not the best ways to find recent and ongoing login attempts to Snowflake. Option A is incorrect because the LOGIN_HISTORY Information Schema table function only returns login events within the last 7 days, which may not be sufficient to detect credential stuffing attacks that span a longer period of time2. Option C is incorrect because the History tab in the Snowflake UI only shows the queries executed by the current user or role, not the login events of other users or roles3. Option D is incorrect because the Users section in the Account tab in the Snowflake UI only shows the last login time for each user, not the details of the login attempts or the failures.

NEW QUESTION # 90
Following objects can be cloned in snowflake

A. Transient table
B. Permanent table
C. External tables
D. Internal stages
E. Temporary table

Answer: A,B,C

Explanation:
* Snowflake supports cloning of various objects, such as databases, schemas, tables, stages, file formats, sequences, streams, tasks, and roles. Cloning creates a copy of an existing object in the system without copying the data or metadata. Cloning is also known as zero-copy cloning1.
* Among the objects listed in the question, the following ones can be cloned in Snowflake:
* Permanent table: A permanent table is a type of table that has a Fail-safe period and a Time Travel retention period of up to 90 days. A permanent table can be cloned using the CREATE TABLE ...
CLONE command2. Therefore, option A is correct.
* Transient table: A transient table is a type of table that does not have a Fail-safe period and can have a Time Travel retention period of either 0 or 1 day. A transient table can also be cloned using the CREATE TABLE ... CLONE command2. Therefore, option B is correct.
* External table: An external table is a type of table that references data files stored in an external location, such as Amazon S3, Google Cloud Storage, or Microsoft Azure Blob Storage. An external table can be cloned using the CREATE EXTERNAL TABLE ... CLONE command3.
Therefore, option D is correct.
* The following objects listed in the question cannot be cloned in Snowflake:
* Temporary table: A temporary table is a type of table that is automatically dropped when the session ends or the current user logs out. Temporary tables do not support cloning4. Therefore, option C is incorrect.
* Internal stage: An internal stage is a type of stage that is managed by Snowflake and stores files in Snowflake's internal cloud storage. Internal stages do not support cloning5. Therefore, option E is
* incorrect.
References: : Cloning Considerations : CREATE TABLE ... CLONE : CREATE EXTERNAL TABLE ...
CLONE : Temporary Tables : Internal Stages

NEW QUESTION # 91
When using the Snowflake Connector for Kafka, what data formats are supported for the messages? (Choose two.)

A. Avro
B. Parquet
C. CSV
D. XML
E. JSON

Answer: A,E

Explanation:
Explanation
The data formats that are supported for the messages when using the Snowflake Connector for Kafka are Avro and JSON. These are the two formats that the connector can parse and convert into Snowflake table rows. The connector supports both schemaless and schematized JSON, as well as Avro with or without a schema registry1. The other options are incorrect because they are not supported data formats for the messages. CSV, XML, and Parquet are not formats that the connector can parse and convert into Snowflake table rows. If the messages are in these formats, the connector will load them as VARIANT data type and store them as raw strings in the table2. References: Snowflake Connector for Kafka | Snowflake Documentation, Loading Protobuf Data using the Snowflake Connector for Kafka | Snowflake Documentation

NEW QUESTION # 92
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