100% PASS ARA-C01 - THE BEST VISUAL SNOWPRO ADVANCED ARCHITECT CERTIFICATION CERT TEST

100% Pass ARA-C01 - The Best Visual SnowPro Advanced Architect Certification Cert Test

100% Pass ARA-C01 - The Best Visual SnowPro Advanced Architect Certification Cert Test

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Snowflake ARA-C01 (SnowPro Advanced Architect Certification) Certification Exam is designed to test the ability of experienced Snowflake architects to design and implement complex Snowflake solutions. SnowPro Advanced Architect Certification certification exam is intended for professionals who have extensive experience in architecting Snowflake solutions and want to demonstrate their expertise and proficiency. ARA-C01 Exam assesses the candidate's ability to design, plan, and implement Snowflake solutions in a variety of scenarios.

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Snowflake SnowPro Advanced Architect Certification Sample Questions (Q114-Q119):

NEW QUESTION # 114
A company's daily Snowflake workload consists of a huge number of concurrent queries triggered between 9pm and 11pm. At the individual level, these queries are smaller statements that get completed within a short time period.
What configuration can the company's Architect implement to enhance the performance of this workload? (Choose two.)

  • A. Set the connection timeout to a higher value than its default.
  • B. Increase the size of the virtual warehouse to size X-Large.
  • C. Enable a multi-clustered virtual warehouse in maximized mode during the workload duration.
  • D. Set the MAX_CONCURRENCY_LEVEL to a higher value than its default value of 8 at the virtual warehouse level.
  • E. Reduce the amount of data that is being processed through this workload.

Answer: C,D

Explanation:
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.
Reference:
Snowflake Documentation: Scaling Policy for Multi-cluster Warehouses
Snowflake Documentation: MAX_CONCURRENCY_LEVEL


NEW QUESTION # 115
What is a characteristic of event notifications in Snowpipe?

  • A. When a pipe Is paused, event messages received for the pipe enter a limited retention period.
  • B. The load history is stored In the metadata of the target table.
  • C. Snowflake can process all older notifications when a paused pipe Is resumed.
  • D. Notifications identify the cloud storage event and the actual data in the files.

Answer: A

Explanation:
Event notifications in Snowpipe are messages sent by cloud storage providers to notify Snowflake of new or modified files in a stage. Snowpipe uses these notifications to trigger data loading from the stage to the target table. When a pipe is paused, event messages received for the pipe enter a limited retention period, which varies depending on the cloud storage provider. If the pipe is not resumed within the retention period, the event messages will be discarded and the data will not be loaded automatically. To load the data, the pipe must be resumed and the COPY command must be executed manually. This is a characteristic of event notifications in Snowpipe that distinguishes them from other options. References: Snowflake Documentation: Using Snowpipe, Snowflake Documentation: Pausing and Resuming a Pipe


NEW QUESTION # 116
What transformations are supported in the below SQL statement? (Select THREE).
CREATE PIPE ... AS COPY ... FROM (...)

  • A. Columns can be omitted.
  • B. Columns can be reordered.
  • C. Data can be filtered by an optional where clause.
  • D. Incoming data can be joined with other tables.
  • E. The ON ERROR - ABORT statement command can be used.
  • F. Type casts are supported.

Answer: A,B,C

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.
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 <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.
createpipe mypipeas
copyintomytable
from(
select*from@mystage
onerror abort
);
1: CREATE PIPE | Snowflake Documentation
2: Transforming Data During a Load | Snowflake Documentation


NEW QUESTION # 117
A company is storing large numbers of small JSON files (ranging from 1-4 bytes) that are received from IoT devices and sent to a cloud provider. In any given hour, 100,000 files are added to the cloud provider.
What is the MOST cost-effective way to bring this data into a Snowflake table?

  • A. An external table
  • B. A copy command at regular intervals
  • C. A pipe
  • D. A stream

Answer: C

Explanation:
A pipe is a Snowflake object that continuously loads data from files in a stage (internal or external) into a table. A pipe can be configured to use auto-ingest, which means that Snowflake automatically detects new or modified files in the stage and loads them into the table without any manual intervention1.
A pipe is the most cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it minimizes the number of COPY commands executed and the number of micro-partitions created. A pipe can use file aggregation, which means that it can combine multiple small files into a single larger file before loading them into the table. This reduces the load time and the storage cost of the data2.
An external table is a Snowflake object that references data files stored in an external location, such as Amazon S3, Google Cloud Storage, or Microsoft Azure Blob Storage. An external table does not store the data in Snowflake, but only provides a view of the data for querying. An external table is not a cost-effective way to bring data into a Snowflake table, because it does not support file aggregation, and it requires additional network bandwidth and compute resources to query the external data3.
A stream is a Snowflake object that records the history of changes (inserts, updates, and deletes) made to a table. A stream can be used to consume the changes from a table and apply them to another table or a task. A stream is not a way to bring data into a Snowflake table, but a way to process the data after it is loaded into a table4.
A copy command is a Snowflake command that loads data from files in a stage into a table. A copy command can be executed manually or scheduled using a task. A copy command is not a cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it does not support file aggregation, and it may create many micro-partitions that increase the storage cost of the data5.


NEW QUESTION # 118
A DevOps team has a requirement for recovery of staging tables used in a complex set of data pipelines. The staging tables are all located in the same staging schema. One of the requirements is to have online recovery of data on a rolling 7-day basis.
After setting up the DATA_RETENTION_TIME_IN_DAYS at the database level, certain tables remain unrecoverable past 1 day.
What would cause this to occur? (Choose two.)

  • A. The tables exceed the 1 TB limit for data recovery.
  • B. The staging schema has not been setup for MANAGED ACCESS.
  • C. The DATA_RETENTION_TIME_IN_DAYS for the staging schema has been set to 1 day.
  • D. The DevOps role should be granted ALLOW_RECOVERY privilege on the staging schema.
  • E. The staging tables are of the TRANSIENT type.

Answer: C,E

Explanation:
* The DATA_RETENTION_TIME_IN_DAYS parameter controls the Time Travel retention period for an object (database, schema, or table) in Snowflake. This parameter specifies the number of days for
* which historical data is preserved and can be accessed using Time Travel operations (SELECT, CREATE ... CLONE, UNDROP)1.
* The requirement for recovery of staging tables on a rolling 7-day basis means that the DATA_RETENTION_TIME_IN_DAYS parameter should be set to 7 at the database level. However, this parameter can be overridden at the lower levels (schema or table) if they have a different value1.
* Therefore, one possible cause for certain tables to remain unrecoverable past 1 day is that the DATA_RETENTION_TIME_IN_DAYS for the staging schema has been set to 1 day. This would override the database level setting and limit the Time Travel retention period for all the tables in the schema to 1 day. To fix this, the parameter should be unset or set to 7 at the schema level1. Therefore, option B is correct.
* Another possible cause for certain tables to remain unrecoverable past 1 day is that the staging tables are of the TRANSIENT type. Transient tables are tables that do not have a Fail-safe period and can have a Time Travel retention period of either 0 or 1 day. Transient tables are suitable for temporary or intermediate data that can be easily reproduced or replicated2. To fix this, the tables should be created as permanent tables, which can have a Time Travel retention period of up to 90 days1. Therefore, option D is correct.
* Option A is incorrect because the MANAGED ACCESS feature is not related to the data recovery requirement. MANAGED ACCESS is a feature that allows granting access privileges to objects without explicitly granting the privileges to roles. It does not affect the Time Travel retention period or the data availability3.
* Option C is incorrect because there is no 1 TB limit for data recovery in Snowflake. The data storage size does not affect the Time Travel retention period or the data availability4.
* Option E is incorrect because there is no ALLOW_RECOVERY privilege in Snowflake. The privilege required to perform Time Travel operations is SELECT, which allows querying historical data in tables5.
References: : Understanding & Using Time Travel : Transient Tables : Managed Access : Understanding Storage Cost : Table Privileges


NEW QUESTION # 119
......

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