ARA-C01 Unterlagen mit echte Prüfungsfragen der Snowflake Zertifizierung

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Snowflake ARA-C01 Exam Syllabus Topics:

Section	Objectives
Data Architecture and Design	- Data modeling and schema design 1. Star and snowflake schema concepts 2. Semi-structured data modeling - Design scalable Snowflake architectures 1. Multi-cluster virtual warehouse design 2. Account and environment strategy
Data Pipelines and Data Engineering	- Data orchestration 1. Pipeline design patterns 2. Tasks and Streams usage - Data ingestion and transformation 1. Snowpipe and continuous data loading 2. Batch and streaming ingestion
Data Sharing and Collaboration	- Secure data sharing 1. Data marketplace concepts 2. Cross-account data sharing
Security, Governance, and Compliance	- Access control and security model 1. Role-based access control (RBAC) 2. Network security and authentication - Data governance 1. Audit and compliance features 2. Data classification and masking policies
Performance and Optimization	- Query performance tuning 1. Warehouse sizing and scaling 2. Query profiling and optimization techniques - Cost optimization 1. Storage and compute efficiency 2. Resource monitoring and cost control

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Snowflake SnowPro Advanced Architect Certification ARA-C01 Prüfungsfragen mit Lösungen (Q199-Q204):

199. Frage
What are some of the characteristics of result set caches? (Choose three.)

A. Each time persisted results for a query are used, a 24-hour retention period is reset.
B. Time Travel queries can be executed against the result set cache.
C. Snowflake persists the data results for 24 hours.
D. The data stored in the result cache will contribute to storage costs.
E. The retention period can be reset for a maximum of 31 days.
F. The result set cache is not shared between warehouses.

Antwort: A,C,F

Begründung:
In Snowflake, the characteristics of result set caches include persistence of data results for 24 hours (B), each use of persisted results resets the 24-hour retention period (C), and result set caches are not shared between different warehouses (F). The result set cache is specifically designed to avoid repeated execution of the same query within this timeframe, reducing computational overhead and speeding up query responses. These caches do not contribute to storage costs, and their retention period cannot be extended beyond the default duration nor up to 31 days, as might be misconstrued.
References:Snowflake Documentation on Result Set Caching.

200. Frage
A new table and streams are created with the following commands:
CREATE OR REPLACE TABLE LETTERS (ID INT, LETTER STRING) ;
CREATE OR REPLACE STREAM STREAM_1 ON TABLE LETTERS;
CREATE OR REPLACE STREAM STREAM_2 ON TABLE LETTERS APPEND_ONLY = TRUE;
The following operations are processed on the newly created table:
INSERT INTO LETTERS VALUES (1, 'A');
INSERT INTO LETTERS VALUES (2, 'B');
INSERT INTO LETTERS VALUES (3, 'C');
TRUNCATE TABLE LETTERS;
INSERT INTO LETTERS VALUES (4, 'D');
INSERT INTO LETTERS VALUES (5, 'E');
INSERT INTO LETTERS VALUES (6, 'F');
DELETE FROM LETTERS WHERE ID = 6;
What would be the output of the following SQL commands, in order?
SELECT COUNT (*) FROM STREAM_1;
SELECT COUNT (*) FROM STREAM_2;

A. 4 & 6
B. 2 & 3
C. 4 & 3
D. 2 & 6

Antwort: C

Begründung:
In Snowflake, a stream records data manipulation language (DML) changes to its base table since the stream was created or last consumed. STREAM_1 will show all changes including the TRUNCATE operation, while STREAM_2, being APPEND_ONLY, will not show deletions like TRUNCATE. Therefore, STREAM_1 will count the three inserts, the TRUNCATE (counted as a single operation), and the subsequent two inserts before the delete, totaling 4. STREAM_2 will only count the three initial inserts and the two after the TRUNCATE, totaling 3, as it does not count the TRUNCATE or the delete operation.

201. Frage
An Architect uses COPY INTO with the ON_ERROR=SKIP_FILE option to bulk load CSV files into a table called TABLEA, using its table stage. One file named file5.csv fails to load. The Architect fixes the file and re-loads it to the stage with the exact same file name it had previously.
Which commands should the Architect use to load only file5.csv file from the stage? (Choose two.)

A. COPY INTO tablea FROM @%tablea RETURN_FAILED_ONLY = TRUE;
B. COPY INTO tablea FROM @%tablea NEW_FILES_ONLY = TRUE;
C. COPY INTO tablea FROM @%tablea FILES = ('file5.csv');
D. COPY INTO tablea FROM @%tablea FORCE = TRUE;
E. COPY INTO tablea FROM @%tablea;
F. COPY INTO tablea FROM @%tablea MERGE = TRUE;

Antwort: C,E

Begründung:
* Option A (RETURN_FAILED_ONLY) will only load files that previously failed to load. Since file5.csv already exists in the stage with the same name, it will not be considered a new file and will not be loaded.
* Option D (FORCE) will overwrite any existing data in the table. This is not desired as we only want to load the data from file5.csv.
* Option E (NEW_FILES_ONLY) will only load files that have been added to the stage since the last COPY command. This will not work because file5.csv was already in the stage before it was fixed.
* Option F (MERGE) is used to merge data from a stage into an existing table, creating new rows for any data not already present. This is not needed in this case as we simply want to load the data from file5.csv.
Therefore, the architect can use either COPY INTO tablea FROM @%tablea or COPY INTO tablea FROM
@%tablea FILES = ('file5.csv') to load only file5.csv from the stage. Both options will load the data from the specified file without overwriting any existing data or requiring additional configuration

202. Frage
An Architect needs to design a Snowflake account and database strategy to store and analyze large amounts of structured and semi-structured data. There are many business units and departments within the company. The requirements are scalability, security, and cost efficiency.
What design should be used?

A. Set up separate Snowflake accounts and databases for each department or business unit, to ensure data isolation and security.
B. Use Snowflake's data lake functionality to store and analyze all data in a central location, without the need for structured schemas or indexes
C. Create a single Snowflake account and database for all data storage and analysis needs, regardless of data volume or complexity.
D. Use a centralized Snowflake database for core business data, and use separate databases for departmental or project-specific data.

Antwort: D

Begründung:
The best design to store and analyze large amounts of structured and semi-structured data for different business units and departments is to use a centralized Snowflake database for core business data, and use separate databases for departmental or project-specific data. This design allows for scalability, security, and cost efficiency by leveraging Snowflake's features such as:
Database cloning: Cloning a database creates a zero-copy clone that shares the same data files as the original database, but can be modified independently. This reduces storage costs and enables fast and consistent data replication for different purposes.
Database sharing: Sharing a database allows granting secure and governed access to a subset of data in a database to other Snowflake accounts or consumers. This enables data collaboration and monetization across different business units or external partners.
Warehouse scaling: Scaling a warehouse allows adjusting the size and concurrency of a warehouse to match the performance and cost requirements of different workloads. This enables optimal resource utilization and flexibility for different data analysis needs. References: Snowflake Documentation: Database Cloning, Snowflake Documentation: Database Sharing, [Snowflake Documentation: Warehouse Scaling]

203. Frage
A user named USER_01 needs access to create a materialized view on a schema EDW. STG_SCHEMA. How can this access be provided?

A. GRANT ROLE NEW_ROLE TO USER USER_01;
GRANT CREATE MATERIALIZED VIEW ON SCHEMA ECW.STG_SCHEKA TO NEW_ROLE;
B. GRANT ROLE NEW_ROLE TO USER_01;
GRANT CREATE MATERIALIZED VIEW ON EDW.STG_SCHEMA TO NEW_ROLE;
C. GRANT CREATE MATERIALIZED VIEW ON SCHEMA EDW.STG_SCHEMA TO USER USER_01;
D. GRANT CREATE MATERIALIZED VIEW ON DATABASE EDW TO USER USERJD1;

Antwort: C

Begründung:
The correct answer is A because it grants the specific privilege to create a materialized view on the schema EDW.STG_SCHEMA to the user USER_01 directly.
Option B is incorrect because it grants the privilege to create a materialized view on the entire database EDW, which is too broad and unnecessary. Also, there is a typo in the user name (USERJD1 instead of USER_01).
Option C is incorrect because it grants the privilege to create a materialized view on a different schema (ECW.STG_SCHEKA instead of EDW.STG_SCHEMA). Also, there is no need to create a new role for this purpose.
Option D is incorrect because it grants the privilege to create a materialized view on an invalid object (EDW.STG_SCHEMA is not a valid schema name, it should be EDW.STG_SCHEMA). Also, there is no need to create a new role for this purpose. Reference:
Snowflake Documentation: CREATE MATERIALIZED VIEW
Snowflake Documentation: Working with Materialized Views
[Snowflake Documentation: GRANT Privileges on a Schema]

204. Frage
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