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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Engineering | 25% | - Data Transformation
|
| Topic 2: Accounts and Security | 25% | - Governance and Compliance
|
| Topic 3: Snowflake Architecture | 30% | - Storage and Compute Design
|
| Topic 4: Performance Optimization | 20% | - Query Performance
|
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NEW QUESTION # 176
A user is executing the following command sequentially within a timeframe of 10 minutes from start to finish:
What would be the output of this query?
Answer: B
Explanation:
The query is executing a clone operation on an existing table t_sales with an offset to account for the retention time. The syntax used is correct for cloning a table in Snowflake, and the use of the at(offset => -60*30) clause is valid. This specifies that the clone should be based on the state of the table 30 minutes prior (60 seconds * 30). Assuming the table t_sales exists and has been modified within the last 30 minutes, and considering the data_retention_time_in_days is set to 1 day (which enables time travel queries for the past 24 hours), the table t_sales_clone would be successfully created based on the state of t_sales 30 minutes before the clone command was issued.
NEW QUESTION # 177
What transformations are supported in the below SQL statement? (Select THREE).
CREATE PIPE ... AS COPY ... FROM (...)
Answer: A,B,F
Explanation:
The SQL statement is a command for creating a pipe in Snowflake, which is an object that defines the COPY INTO <table> statement used by Snowpipe to load data from an ingestion queue into tables1. The statement uses a subquery in the FROM clause to transform the data from the staged files before loading it into the table2.
The transformations supported in the subquery are as follows2:
Data can be filtered by an optional WHERE clause, which specifies a condition that must be satisfied by the rows returned by the subquery. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable
from (
select * from @mystage
where col1 = 'A' and col2 > 10
);
Columns can be reordered, which means changing the order of the columns in the subquery to match the order of the columns in the target table. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2, col3)
from (
select col3, col1, col2 from @mystage
);
Columns can be omitted, which means excluding some columns from the subquery that are not needed in the target table. For example:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2)
from (
select col1, col2 from @mystage
);
The other options are not supported in the subquery because2:
Type casts are not supported, which means changing the data type of a column in the subquery. For example, the following statement will cause an error:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2)
from (
select col1::date, col2 from @mystage
);
Incoming data can not be joined with other tables, which means combining the data from the staged files with the data from another table in the subquery. For example, the following statement will cause an error:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable (col1, col2, col3)
from (
select s.col1, s.col2, t.col3 from @mystage s
join othertable t on s.col1 = t.col1
);
The ON ERROR - ABORT statement command can not be used, which means aborting the entire load operation if any error occurs. This command can only be used in the COPY INTO <table> statement, not in the subquery. For example, the following statement will cause an error:
SQLAI-generated code. Review and use carefully. More info on FAQ.
create pipe mypipe as
copy into mytable
from (
select * from @mystage
on error abort
);
Reference:
1: CREATE PIPE | Snowflake Documentation
2: Transforming Data During a Load | Snowflake Documentation
NEW QUESTION # 178
A company is using Snowflake in Azure in the Netherlands. The company analyst team also has data in JSON format that is stored in an Amazon S3 bucket in the AWS Singapore region that the team wants to analyze.
The Architect has been given the following requirements:
1. Provide access to frequently changing data
2. Keep egress costs to a minimum
3. Maintain low latency
How can these requirements be met with the LEAST amount of operational overhead?
Answer: D
NEW QUESTION # 179
Validation mode can take the below options
Answer: B,C,D
NEW QUESTION # 180
A new user user_01 is created within Snowflake. The following two commands are executed:
Command 1-> show grants to user user_01;
Command 2 ~> show grants on user user 01;
What inferences can be made about these commands?
Answer: B
Explanation:
The SHOW GRANTS command in Snowflake can be used to list all the access control privileges that have been explicitly granted to roles, users, and shares. The syntax and the output of the command vary depending on the object type and the grantee type specified in the command1. In this question, the two commands have the following meanings:
* Command 1: show grants to user user_01; This command lists all the roles granted to the user user_01.
The output includes the role name, the grantee name, and the granted by role name for each grant. This command is equivalent to show grants to user current_user if user_01 is the current user1.
* Command 2: show grants on user user_01; This command lists all the privileges that have been granted on the user object user_01. The output includes the privilege name, the grantee name, and the granted by role name for each grant. This command shows which role owns the user object user_01, as the owner role has the privilege to modify or drop the user object2.
Therefore, the correct inference is that command 1 defines all the grants which are given to user_01, and command 2 defines which role owns user_01.
References:
* SHOW GRANTS
* Understanding Access Control in Snowflake
NEW QUESTION # 181
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