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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Engineering | 25% | - Data Transformation
|
| Topic 2: Snowflake Architecture | 30% | - Storage and Compute Design
|
| Topic 3: Performance Optimization | 20% | - Cost and Resource Optimization
|
| Topic 4: Accounts and Security | 25% | - Governance and Compliance
|
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NEW QUESTION # 136
How can an Architect enable optimal clustering to enhance performance for different access paths on a given table?
Answer: D
Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, the best way to enable optimal clustering to enhance performance for different access paths on a given table is to create multiple materialized views with different cluster keys. A materialized view is a pre-computed result set that is derived from a query on one or more base tables. A materialized view can be clustered by specifying a clustering key, which is a subset of columns or expressions that determines how the data in the materialized view is co-located in micro-partitions. By creating multiple materialized views with different cluster keys, an Architect can optimize the performance of queries that use different access paths on the same base table. For example, if a base table has columns A, B, C, and D, and there are queries that filter on A and B, or on C and D, or on A and C, the Architect can create three materialized views, each with a different cluster key: (A, B), (C, D), and (A, C). This way, each query can leverage the optimal clustering of the corresponding materialized view and achieve faster scan efficiency and better compression.
References:
* Snowflake Documentation: Materialized Views
* Snowflake Learning: Materialized Views
https://www.snowflake.com/blog/using-materialized-views-to-solve-multi-clustering-performance-problems/
NEW QUESTION # 137
Which statements describe characteristics of the use of materialized views in Snowflake? (Choose two.)
Answer: C,E
Explanation:
According to the Snowflake documentation, materialized views have some limitations on the query specification that defines them. One of these limitations is that they cannot include nested subqueries, such as subqueries in the FROM clause or scalar subqueries in the SELECT list. Another limitation is that they cannot include ORDER BY clauses, context functions (such as CURRENT_TIME()), or outer joins. However, materialized views can support MIN and MAX aggregates, as well as other aggregate functions, such as SUM, COUNT, and AVG.
Reference:
Limitations on Creating Materialized Views | Snowflake Documentation
Working with Materialized Views | Snowflake Documentation
NEW QUESTION # 138
An Architect is designing a pipeline to stream event data into Snowflake using the Snowflake Kafka connector. The Architect's highest priority is to configure the connector to stream data in the MOST cost-effective manner.
Which of the following is recommended for optimizing the cost associated with the Snowflake Kafka connector?
Answer: C
Explanation:
The minimum value supported for the buffer.flush.time property is 1 (in seconds). For higher average data flow rates, we suggest that you decrease the default value for improved latency. If cost is a greater concern than latency, you could increase the buffer flush time. Be careful to flush the Kafka memory buffer before it becomes full to avoid out of memory exceptions.
https://docs.snowflake.com/en/user-guide/data-load-snowpipe-streaming-kafka
NEW QUESTION # 139
There are two databases in an account, named fin_db and hr_db which contain payroll and employee data, respectively. Accountants and Analysts in the company require different permissions on the objects in these databases to perform their jobs. Accountants need read-write access to fin_db but only require read-only access to hr_db because the database is maintained by human resources personnel.
An Architect needs to create a read-only role for certain employees working in the human resources department.
Which permission sets must be granted to this role?
Answer: D
NEW QUESTION # 140 
Based on the architecture in the image, how can the data from DB1 be copied into TBL2? (Select TWO).
Answer: C,D
Explanation:
* The architecture in the image shows a Snowflake data platform with two databases, DB1 and DB2, and two schemas, SH1 and SH2. DB1 contains a table TBL1 and a stage STAGE1. DB2 contains a table TBL2. The image also shows a snippet of code written in SQL language that copies data from STAGE1 to TBL2 using a file format FF PIPE 1.
* To copy data from DB1 to TBL2, there are two possible options among the choices given:
* Option B: Use a named external stage that references STAGE1. This option requires creating an external stage object in DB2.SH2 that points to the same location as STAGE1 in DB1.SH1. The external stage can be created using the CREATE STAGE command with the URL parameter specifying the location of STAGE11. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
use database DB2;
use schema SH2;
create stage EXT_STAGE1
url = @DB1.SH1.STAGE1;
* Then, the data can be copied from the external stage to TBL2 using the COPY INTO command with the FROM parameter specifying the external stage name and the FILE FORMAT parameter specifying the file format name2. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
copy into TBL2
from @EXT_STAGE1
file format = (format name = DB1.SH1.FF PIPE 1);
* Option E: Use a cross-database query to select data from TBL1 and insert into TBL2. This option requires using the INSERT INTO command with the SELECT clause to query data from TBL1 in DB1.SH1 and insert it into TBL2 in DB2.SH2. The query must use the fully-qualified names of the tables, including the database and schema names3. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
use database DB2;
use schema SH2;
insert into TBL2
select * from DB1.SH1.TBL1;
* The other options are not valid because:
* Option A: It uses an invalid syntax for the COPY INTO command. The FROM parameter cannot specify a table name, only a stage name or a file location2.
* Option C: It uses an invalid syntax for the COPY INTO command. The FILE FORMAT parameter cannot specify a stage name, only a file format name or options2.
* Option D: It uses an invalid syntax for the CREATE STAGE command. The URL parameter cannot specify a table name, only a file location1.
References:
* 1: CREATE STAGE | Snowflake Documentation
* 2: COPY INTO table | Snowflake Documentation
* 3: Cross-database Queries | Snowflake Documentation
NEW QUESTION # 141
......
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