Snowflake Interview Questions Part-1

What is Snowflake?

Snowflake is a cloud data warehouse providing as a software-as-a-service (SaaS). It consists of unique architecture to handle several aspects of data and analytics. Snowflake sets itself apart from all other traditional data warehouse solutions with advanced capabilities like improved performance, effortlessness, high concurrency and cost-effectiveness. Snowflake’s shared data architecture physically separates the computation and storage which is not possible by the traditional offerings. It streamlines the process for businesses to store and analyze massive volumes of data using cloud-based tools.

What are the layers present in Snowflake?

There are three layers present in snowflake

1. Cloud Services /Metadata Layer

2. Virtual Warehouse / Compute Layer

3. Storage Layer

Explain the Data Storage Layer in snowflake?

Whenever the data gets loaded into Snowflake it positions the data into optimized, compressed and columnar format. After this process, the data gets optimized and then stored in cloud storage.

Snowflake looks after how the data gets stored which include data organization, compression, structure, file size, statistics, metadata, and many other aspects related to data storage. All the data objects stored in Snowflake are invisible and inaccessible.

What is Virtual Warehouse or Query Processing Layer in Snowflake? and What it will do?

All the query executions are performed in this processing/Compute layer. Snowflake uses “virtual warehouses to process queries. Each virtual warehouse is an MPP (massively parallel processing) compute cluster which consists of multiple nodes allotted by snowflake from a cloud provider. Each virtual warehouse in the query processing layer is independent and does not share its computational resources with any other virtual warehouses. This makes each virtual warehouse independent and shows no impact on the other virtual warehouses in case of any failover.

Virtual warehouses provided Multi-Cluster Warehouses as well to scale up/down automatically servers.

What is Unique about Snowflake Architecture?

Snowflake has come up with an advanced and unique architecture that is a combination of shared-disk and shared-nothing architectures. It uses a central data repository to store data consistently and makes it available to access from all compute nodes in the platform.

Snowflake unique architecture consists of three layers which are database storage, Query processing, and Cloud services.

How data compression works in Snowflake?

All the data entered into snowflake gets compressed automatically. Snowflake uses advanced data compression algorithms to compress and store data. The customers need to pay for the compressed data, not for the actual data.

What is the execution process in Snowflake Architecture?

Name the types of Cache available in Snowflake?

• Query Results Caching
• Metadata Cache
• Virtual Warehouse Local Disk Caching

How Snowflake Caching will work?

Snowflake has automatic caching for queries run more than once in 24 hours. In addition, Snowflake doesn’t re-run a query but delivers the answer set immediately.

Example: if you could have an original query that takes five minutes to run because it delivers a huge answer set, but the next time it is run, it only takes a second because of the caching.

The cache will spoil if the underlying data has any inserts, updates, or deletes. However, other users in the same warehouse who run the same query will also take advantage of the Snowflake caching feature.

What is Time Travel in Snowflake?

Snowflake Time Travel tool permits you to access historical data at any given point within a defined time period. Using this We can see the data that has been deleted or changed. Using this tool, we can achieve the below tasks:

• Restore data-related objects (Schemas, tables, and databases) that might have lost accidentally.
• To examine data usage and changes made to data with a time period
• Backing up and duplicating data from key points in the past.