Snowflake Interview Questions and Answers: Mastering Cloud Data Warehousing
Snowflake Interview Questions
Organizations look for solutions to cope with big data and related difficulties as a result of the continuous growth and velocity of data. The management and storage of data are now essential components of modern company operations. But the real query is, what choice does an organisation make first? Simple: Use a cloud-based strategy that offers great performance, scalability, and flexibility. Here comes snowflakes, a platform for cloud-based data warehouses that is gaining popularity due to its capabilities, compatibility for multi-cloud architecture setups, and effectiveness.
What is Snowflake:
To provide businesses with adaptable, scalable storage solutions while also hosting BI (Business Intelligence) solutions, Snowflake is essentially a Saa2.S (Software as a Service) based data warehouse (DWH) platform that is built on top of AWS (Amazon Web Services), Microsoft Azure, and Google Cloud infrastructures. It functions as a centralised platform for real-time and shared data sharing and consumption, data lakes, data engineering, data applications development, and data science. The data warehousing sector was completely transformed by Snowflake, which offered a single system to combine all data. Data warehouse management may be made simpler with Snowflake without compromising functionalities.
Interview Questions for Freshers
- What are some Snowflake features that help data transformation?
Between departments, regions, or partners, Snowflake’s secure data exchange eliminates the need for data extraction or transformation. Snowflake works with a variety of data integration partners to load main data sources, and users can select either ETL or post-load data transformation (ELT).
- Explain Snowflake Architecture.?
The architecture of Snowflake is a cross between the conventional shared-disk and shared-nothing database designs. Snowflake uses a central data repository for persisting data that is accessible from all compute nodes in the platform, much as shared-disk systems.
The Snowflake architecture is divided into three key layers as shown below:
Snowflake has 3 different layers: Storage Layer. Compute Layer. Cloud Services Layer.
- What do you mean by virtual warehouse?
The virtual warehouse in Snowflake contains a cluster of computing resources. It offers resources, like as memory, temporary storage, and CPU, to carry out operations like DML and SQL execution.
- How do I access Snowflake cloud data warehouse?
Snowflake Data Warehousing Tutorials: See the Difference First Hand
Navigate the Snowflake UI.
Create a database and compute resources.
Load data into Snowflake.
Run queries on the loaded data.
Explore cool features including zero-copy cloning and time travel.
- What is the difference between Snowflake and Redshift?
Redshift mixes computing and storage together, whereas Snowflake separates them in their pricing model. Concurrency scaling is automatically included with all Snowflake editions, while Redshift gives users a set daily concurrency scaling allowance and charges by the second after usage surpasses it.
- What are stages in Snowflake?
Internal Named Stages are Storage Location Objects in the context of a Snowflake Database/Schema. They are subject to the same security permissions as other database objects since they are database objects. These Stages do not automatically build themselves, in contrast to User and Table Stages.
- Explain Snowpipe?
As soon as files are available in a stage, Snowpipe allows for the loading of data from them. This means that rather than manually performing COPY statements on a schedule to load larger batches of data, you may load data from files in micro-batches and make it available to users in only a few minutes.
Advantages of Snowpipe –
By eliminating roadblocks, Snowpipe facilitates real-time analytics.
It is cost-effective.
It is simple to use.
There is no management required.
It provides flexibility, resilience, and so on.
- What do you mean by Snowflake Computing?
In comparison to conventional services, Snowflake’s data storage, processing, and analytic solutions are far quicker, simpler to use, and much more versatile. No current database technology or “big data” software platforms like Hadoop are used to build the Snowflake data platform.
- Which cloud platforms does Snowflake currently support?
A Snowflake account can be hosted on any of the following cloud platforms:
Amazon Web Services (AWS)
Google Cloud Platform (GCP)
Microsoft Azure (Azure)
- How data is secured in Snowflake?
All ingested data is protected with AES-256 strong encryption before being saved in Snowflake tables. Using AES-256 strong encryption, all files kept in internal stages for data loading and unloading are automatically encrypted.
- Is Snowflake an ETL (Extract, Transform, and Load) tool?
Either after loading (ETL) or during transformation are supported by Snowflake (ELT). Numerous data integration solutions, such as Informatica, Talend, Fivetran, Matillion, and others, are compatible with Snowflake.
- Which ETL tools are compatible with Snowflake?
Snowflake is compatible with the following ETL tools:
Matillion
Blendo
Hevo Data
StreamSets
Etleap
Apache Airflow, etc.
- What do you mean by Horizontal and Vertical Scaling?
Vertical scaling entails adding additional power (CPU, RAM) to an existing system, whereas horizontal scaling entails adding more machines to your pool of resources.
- Is snowflake OLTP (Online Transactional Processing) or OLAP (Online Analytical Processing)?
Snowflake operates as a single, regulated, and instantly queryable source for your data by utilising OLAP as a fundamental component of its database structure. The platform enables seamless interfaces with well-known business intelligence and analytics products in addition to its built-in analytics functions.
- Snowflake is what kind of database?
Built on top of SQL (Structured Query Language) databases are all of Snowflake’s features. This relational database system uses columns to store data and is interoperable with other programmes like Excel and Tableau. Snowflake has a query tool, enables multi-statement transactions, offers role-based security, etc. as a SQL database.
- Explain in short about Snowflake Clustering.?
When reclustering, Snowflake rearranges the column data in such a way that similar records are moved to the same micro-partition using the clustering key for the clustered table. Using the clustering key as a guide, the impacted records are deleted and then reinserted.
Snowflake Interview Questions for Experienced
- How is data stored in Snowflake? Explain Columnar Database.
Within the storage layer, Snowflake optimises and saves data in a columnar format that is arranged into databases in accordance with the user’s specifications. flexibly as resource requirements alter. Virtual warehouses automatically and transparently cache data from the database storage layer when they run queries.
18.Explain Schema in Snowflake.?
An expansion of a star schema, a snowflake schema is a multi-dimensional data model where subdimensions are divided into dimension tables. For business intelligence and reporting in OLAP data warehouses, data marts, and relational databases, snowflake schemas are frequently employed.
- State difference between Star Schema and Snowflake Schema.?
Dimension and fact tables can both be found in a star schema. Dimensional, factual, and sub-dimensional tables can all be found in a snowflake schema. The model type is top-down. Bottom-up modelling is the type used.
- Explain what is Snowflake Time travel and Data Retention Period?
All Snowflake accounts have the standard retention duration of one day (24 hours) enabled by default: At the account and object levels of Snowflake Standard Edition, the retention period can be adjusted to 0 (or unset back to the default of 1 day) (i.e. databases, schemas, and tables).
- What is Fail-safe period in Snowflake?
A (non-configurable) 7-day window is provided by fail-safe within which Snowflake may be able to recover prior data. This time begins immediately following the expiration of the Time Travel retention period.
- How does Snowflake differ from AWS?
Snowflake is distinct from AWS in that it does not offer a full range of services. Data can be kept in Snowflake, a relational database management system (RDBMS). The extensive range of services offered by AWS, on the other hand, includes computation, storage, networking, and applications.
- Can AWS Glue be related to Snowflake?
The Snowflake Connector for AWS Glue makes it easier to connect AWS Glue jobs so that they can load data into Snowflake and extract data from Snowflake.
- How does data compression works in Snowflake?
As soon as data is loaded into Snowflake, the software rearranges it into a columnar, optimized, and compressed format. This streamlined data is kept by Snowflake in cloud storage.
- What is Snowflake caching?
Every query’s results from the previous 24 hours are stored in the result cache. The query results returned to one user are accessible to any other user on the system who conducts the same query because these are available across virtual warehouses, provided the underlying data has not changed.
- What are different editions in Snowflake?
Popular cloud-based platform Snowflake Data Cloud is offered in four editions: Standard, Enterprise, Business-Critical, and Virtual Private Snowflake.
Detailed explanation :
Snowflake’s cloud-based data platform is available in several editions, including:
Standard Edition: The Snowflake standard edition includes core features such as a data warehouse, data lake, and data exchange.
Enterprise Edition: This edition includes all of the features of the Standard Edition, plus data cloning, data lake housekeeping, and data governance.
Virtual Private Snowflake (VPS): This edition is intended for organisations that require additional data security and control. It includes all of the features of the Enterprise Edition as well as the ability to create a fully isolated and dedicated environment for data storage and processing.
Snowflake on Azure: This edition is designed specifically for Microsoft Azure and includes all of the features of the Standard Edition.
Snowflake on AWS: This edition is specifically designed for Amazon Web Services (AWS) and includes all of the Standard Edition’s features.
Snowflake on Google Cloud: This edition is specifically designed for use on Google Cloud and includes all of the Standard Edition’s features.
- What is zero copy cloning in Snowflake?
Create duplicate databases, schemas, or tables. Normally, we would copy a database’s entire structure, including its metadata, primary keys, and schema, but utilising the clone function in Snowflake makes this task incredibly simple. With just one command, we can copy all the data, information, and structure.
Detailed explanation :
Zero copy cloning is a feature in Snowflake that allows you to make a copy of an existing database, table, or view without physically copying the data. Instead, the clone refers to the same data as the original object, implying that the clone and original share the same data. Because it avoids the overhead of reading and writing data to and from storage, this can be more efficient than physically copying the data, especially for large datasets.
In Snowflake, use the CREATE OR REPLACE object type> AS SELECT * FROM original object> statement to create a zero copy clone. To make a zero copy clone of a table called original table, for example, use the following statement:
CREATE OR REPLACE TABLE clone_table AS SELECT * FROM original_table;
It should be noted that zero copy cloning is available only for databases, tables, and views. Other types of objects, such as procedures or functions, are not supported.
- Explain what do you mean by data shares in Snowflake?
Through shares, which are established by data producers and “imported” by data consumers, Snowflake makes it possible to exchange databases. Every shared database object across accounts is read-only (i.e. the objects cannot be modified or deleted, including adding or modifying table data).
29 What do we need to do to create temporary tables?
In the CREATE TABLE DDL, specify the TEMPORARY keyword (or the TEMP abbreviation) to create a temporary table
Detailed explanation :
The CREATE TEMPORARY TABLE statement in Snowflake can be used to create a temporary table.
The basic syntax for creating a temporary table in Snowflake is as follows:
— Example 1: Create a temporary table with two columns, “id” and “name”
CREATE TEMPORARY TABLE temp_table (
id INTEGER,
name VARCHAR(50)
);
— Example 2: Create a temporary table with a primary key constraint
CREATE TEMPORARY TABLE temp_table (
id INTEGER PRIMARY KEY,
name VARCHAR(50)
);
— Example 3: Create a temporary table with a foreign key constraint
CREATE TEMPORARY TABLE temp_table (
id INTEGER,
name VARCHAR(50),
FOREIGN KEY (id) REFERENCES other_table(id)
);
Temporary tables are only visible to the session that created them, and they are automatically removed when the session terminates. Instead, use the CREATE TABLE statement to create a table that is visible to all users and persists beyond the current session.
- What is a transient table in Snowflake?
Permanent Tables and Snowflake Transient Tables are analogous, but Snowflake Transient Tables lack a fail-safe period. Transient Tables are therefore intended for transient data that must be retained after each session but do not necessitate the same level of data protection and recovery as Permanent Tables.
Detailed explanation :
A transient table in Snowflake is a temporary table that exists only for the duration of a user session. Transient tables can be used to store intermediate results or data that must be processed or transformed in some way. They are frequently used in conjunction with stored procedures or other types of Snowflake code that necessitate temporary data storage.
The CREATE TRANSIENT TABLE statement in Snowflake can be used to create a transient table. As an example:
CREATE TRANSIENT TABLE my_table (
col1 INT,
col2 VARCHAR(50)
);
This will generate a transient table named my table with two columns: col1, an integer, and col2, a string with a maximum length of 50 characters.
After you’ve created a transient table, you can load data into it, query it, and modify it using standard SQL statements. When you exit Snowflake, the transient table and all of its data are automatically deleted.
Conclusion
Due to its cutting-edge features, like separating computation from storage, allowing data sharing and cleaning, and supporting well-known programming languages like Java, Go,.Net, Python, etc., Snowflake is one of the top cloud data warehouse options. Several well-known IT companies are leveraging the Snowflake platform to create data-intensive applications, including Adobe Systems, Amazon Web Services, Informatica, Logitech, and Looker. Thus, demand for snowflake experts is constant.
