ARA-C01 Exam Dumps : SnowPro Advanced: Architect Certification Exam

These two configuration options can enhance the performance of the workload that consists of a huge number of concurrent queries that are smaller and faster.

Enabling a multi-clustered virtual warehouse in maximized mode allows the warehouse to scale out automatically by adding more clusters as soon as the current cluster is fully loaded, regardless of the number of queries in the queue. This can improve the concurrency and throughput of the workload by minimizing or preventing queuing. The maximized mode is suitable for workloads that require high performance and low latency, and are less sensitive to credit consumption1.

Setting the MAX_CONCURRENCY_LEVEL to a higher value than its default value of 8 at the virtual warehouse level allows the warehouse to run more queries concurrently on each cluster. This can improve the utilization and efficiency of the warehouse resources, especially for smaller and faster queries that do not require a lot of processing power. The MAX_CONCURRENCY_LEVEL parameter can be set when creating or modifying a warehouse, and it can be changed at any time2.

Snowflake Documentation: Scaling Policy for Multi-cluster Warehouses

Snowflake Documentation: MAX_CONCURRENCY_LEVEL

The SQL statement is a command for creating a pipe in Snowflake, which is an object that defines the COPY INTO

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.

createpipe mypipeas

copyintomytable

from(

select*from@mystage

wherecol1='A'andcol2>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.

createpipe mypipeas

copyintomytable (col1, col2, col3)

from(

selectcol3, col1, col2from@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.

createpipe mypipeas

copyintomytable (col1, col2)

from(

selectcol1, col2from@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.

createpipe mypipeas

copyintomytable (col1, col2)

from(

selectcol1::date, col2from@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.

createpipe mypipeas

copyintomytable (col1, col2, col3)

from(

selects.col1, s.col2, t.col3from@mystages

joinothertable tons.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

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.

createpipe mypipeas

copyintomytable

from(

select*from@mystage

onerror abort

);

1: CREATE PIPE | Snowflake Documentation

2: Transforming Data During a Load | Snowflake Documentation

Question 3

Role A has the following permissions:

. USAGE on db1

. USAGE and CREATE VIEW on schemal in db1

. SELECT on tablel in schemal

Role B has the following permissions:

. USAGE on db2

. USAGE and CREATE VIEW on schema2 in db2

. SELECT on table2 in schema2

A user has Role A set as the primary role and Role B as a secondary role.

What command will fail for this user?

Options:

A.

use database db1;use schema schemal;create view v1 as select * from db2.schema2.table2;

B.

use database db2;use schema schema2;create view v2 as select * from dbl.schemal. tablel;

C.

use database db2;use schema schema2;select * from db1.schemal.tablel union select * from table2;

D.

use database db1;use schema schemal;select * from db2.schema2.table2;

Show Answer

Answer:

B

Explanation:

This command will fail because while the user has USAGE permission ondb2andschema2through Role B, and can create a view inschema2, they do not have SELECT permission ondb1.schemal.table1with Role B. Since Role A, which has SELECT permission ondb1.schemal.table1, is not the currently active role when the viewv2is being created indb2.schema2, the user does not have the necessary permissions to read fromdb1.schemal.table1to create the view. Snowflake’s security model requires that the active role have all necessary permissions to execute the command.

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