Free SnowPro Advanced: Data Engineer Certification Exam Practice Questions

A.  

Snowflake automatically handles leading spaces by trimming implicitly & removes the quotation marks enclosing each field.

B.  

field_optionally_enclosed_by option along with TRIM_IF function in COPY INTO statement can be used to handle this scenario successfully.

C.  

Snowflake reads the leading space rather than the opening quotation character as the beginning of the field and the quotation characters are interpreted as string data.

(Correct)

D.  

COPY command trims the leading space and removes the quotation marks enclosing each field

1.copy into SFtable

2.from @%SFtable

3.file_format = (type = csv trim_space=true field_optionally_enclosed_by = '0x22');

A.  

1.select *

2.from table(information_schema.task_history(

3.scheduled_time_range_start=>dateadd('hour',-1,current_timestamp()),

4.result_limit => 10,

5.task_name=>'MYTASK') WHERE query_id IS NOT NULL);

B.  

1.select *

2.from table(information_schema.task_history(

3.scheduled_time_range_start=>dateadd('hour',-1,current_timestamp()),

4.result_limit => 11,

5.task_name=>'MYTASK') WHERE query_id IS NOT NULL);

C.  

1.select *

2.from table(information_schema.task_history(

3.scheduled_time_range_start=>dateadd('hour',-1,current_timestamp()),

4.result_limit => 10,query_id IS NOT NULL

5.task_name=>'MYTASK'));

D.  

1.select *

2.from table(information_schema.task_history(

3.scheduled_time_range_start=>dateadd('hour',-1,current_timestamp()),

4.result_limit => 10,

5.task_name=>'MYTASK'));

A.  

Single Value

B.  

A Set of Rows

C.  

Scaler or Tabular depend on input SQL expression

D.  

Regex

A.  

Data pipelines would be created to first load data into internal stages & then into Per-manent table with SCD Type 2 transformation.

B.  

Direct Querying External tables on top of existing data stored in external cloud storage for analysis without first loading it into Snowflake.

C.  

Unload data into SnowFlake Internal data storage using PUT command.

D.  

Snowpipe can be leveraged with streams to load data in micro batch fashion with CDC streams that capture most recent data only.

E.  

External tables with Materialized views can be created in Snowflake.

A.  

TRUE

B.  

FALSE

A.  

TRUE

B.  

FALSE

A.  

For streams on views, change tracking must be enabled explicitly for the view and un-derlying tables to add the hidden columns to these tables.

B.  

The CDC records returned when querying a stream rely on a combination of the offset stored in the stream and the change tracking metadata stored in the table.

C.  

Views with GROUP BY & LIMIT Clause are supported by Snowflake.

D.  

As an alternative to streams, Snowflake supports querying change tracking metadata for views using the CHANGES clause for SELECT statements.

E.  

Enabling change tracking adds a pair of hidden columns to the table and begins storing change tracking metadata. The values in these hidden CDC data columns provide the input for the stream metadata columns. The columns consume a small amount of stor-age.

A.  

Multi-cluster warehouses are designed specifically for handling queuing and perfor-mance issues related to large numbers of concurrent users and/or queries.

B.  

Unless you have a specific requirement for running in Maximized mode, multi-cluster warehouses should be configured to run in Auto-scale mode, which enables Snowflake to automatically start and stop clusters as needed.

C.  

When choosing the minimum number of clusters for a multi-cluster warehouse keep the default value as 1.

D.  

Multi-cluster warehouses generally improve query performance, particularly for larger, more complex queries.

E.  

When choosing the maximum number of clusters for a multi-cluster warehouse set its value as large as possible.

A.  

Regular views do not cache data, and therefore cannot improve performance by cach-ing.

B.  

As with non-materialized views, a materialized view automatically inherits the privileges of its base table.

C.  

Cached Query Results: Used only if data has not changed and if query only uses de-terministic functions (e.g. not CURRENT_DATE).

D.  

Materialized views are faster than tables because of their “cache” (i.e. the query results for the view); in addition, if data has changed, they can use their “cache” for data that hasn’t changed and use the base table for any data that has changed.

E.  

Both materialized views and regular views enhance data security by allowing data to be exposed or hidden at the row level or column level.

A.  

SQL

B.  

JAVA

C.  

JAVASCRIPT

D.  

PYTHON