Handling Large Data Sets in Snowflake: Expert-Level Quiz

This expert-level quiz is designed for experienced users who work with Snowflake for data warehousing and big data management. It covers various topics, including best practices for large data handling, Snowflake's unique architecture, scaling and performance optimization, and SQL-based data manipulation within Snowflake.

1 / 20

Time Travel in Snowflake allows viewing historical data without restoring from backup.

False

True

2 / 20

In Snowflake, which syntax is correct for defining a clustering key on a table?

SET CLUSTER KEY ON tablename(column);

ALTER TABLE tablename SET CLUSTER BY(column);

ALTER TABLE tablename CLUSTERING KEY (column);

CREATE CLUSTERING KEY (column) ON tablename;

3 / 20

What type of storage model does Snowflake use to manage large-scale data effectively?

Hierarchical

On-premise block storage

Hybrid cloud

Shared-disk architecture

4 / 20

Snowflake supports primary keys and foreign key constraints that enforce referential integrity during data loading.

True

False

5 / 20

Using the AUTO_SCALE setting, Snowflake dynamically adjusts the warehouse size based on workload.

True

False

6 / 20

Snowflake’s AUTO_SUSPEND parameter suspends a virtual warehouse when it reaches a specified workload threshold.

True

False

7 / 20

Which Snowflake data type is suitable for efficiently storing large numeric data, such as sales figures with two decimal places?

DECIMAL(10,2)

BOOLEAN

STRING

FLOAT

8 / 20

What does the following Snowflake command do? ALTER WAREHOUSE my_warehouse SET MIN_CLUSTER_COUNT = 1;

Sets the minimum memory allocated per cluster

Deactivates clustering

Ensures the warehouse has a minimum of one cluster always running

Forces warehouse to use only one cluster

9 / 20

Snowflake can store data across multiple cloud providers, but computing must reside in the same region as storage.

True

False

10 / 20

Snowflake does not support User-Defined Functions (UDFs) for SQL code.

True

False

11 / 20

Snowflake uses Hadoop to store underlying distributed data.

True

False

12 / 20

To load data from an external S3 bucket into a Snowflake table, which of the following commands is correct?

COPY DATA FROM S3://mybucket/data.csv INTO my_table FILE_FORMAT = 'CSV';

COPY INTO my_table FROM 's3://mybucket/data.csv' CREDENTIALS = (AWS_KEY_ID='key' AWS_SECRET_KEY='secret');

COPY INTO my_table FROM @my_stage/data.csv FILE_FORMAT = (TYPE = 'CSV');

COPY DATA FROM S3 INTO my_table CREDENTIALS = (AWS_ACCESS_KEY='key' AWS_SECRET_KEY='secret');

13 / 20

Which file format in Snowflake is generally best for handling large data sets due to compression benefits and efficient querying?

CSV

XML

JSON

Parquet

14 / 20

External tables in Snowflake can directly reference data stored in Amazon S3 but cannot reference data in Azure Blob Storage.

True

False

15 / 20

If you want to retrieve only rows from the last 3 months in the transactions table, which query is correct?

SELECT * FROM transactions WHERE order_date IN LAST 3 MONTHS;

SELECT * FROM transactions WHERE order_date = DATEADD(MONTH, -3, CURRENT_DATE);

SELECT * FROM transactions WHERE order_date BETWEEN DATEADD(MONTH, -3, CURRENT_DATE) AND CURRENT_DATE;

SELECT * FROM transactions WHERE order_date > DATEADD(month, -3, CURRENT_DATE);

16 / 20

Snowflake’s micro-partition storage model is optimized for fast access to small data sets.

False

True

17 / 20

What Snowflake feature allows for automatically managed large table data partitioning based on frequent query patterns?

A) Indexing
B) Clustering
C) Sharding
D) Data mining

Indexing

Data mining

Sharding

Clustering

18 / 20

Snowflake automatically scales out resources for larger data queries when enabling multi-cluster warehouses.

True

False

19 / 20

Which Snowflake statement is used to load large data files into a Snowflake table from an external S3 bucket?

A) LOAD DATA INFILE
B) IMPORT INTO TABLE
C) COPY INTO table FROM @stage
D) MOVE INTO table FROM S3

MOVE INTO table FROM S3

LOAD DATA INFILE

COPY INTO table FROM @stage

IMPORT INTO TABLE

20 / 20

Which command will correctly define a clustering key for the sales_data table to optimize queries by date?

ALTER TABLE sales_data SET CLUSTERING KEY (order_date);

ALTER TABLE sales_data SET CLUSTER BY LINEAR (order_date);

ALTER TABLE sales_data CLUSTER ON order_date;

ALTER TABLE sales_data CLUSTER BY (order_date);

Your score is

The average score is 0%

Handling large data sets in Snowflake requires a deep understanding of its advanced features and techniques. Snowflake lets you manage, analyze, and optimize large data sets efficiently because of its powerful cloud-based data warehousing platform.

In this expert-level quiz, you will explore advanced concepts that will test your professional knowledge of large data in Snowflake.

This quiz will challenge you to apply your skills and improve your data management capabilities to new heights.

Good luck.