Boost your Career with Snowflake. Snowflake is one of the ultimate cloud data warehouse solutions with innovative capabilities like data sharing, data cleansing, compute and storage isolation. It supports programming languages like .Net, Java, Python and Go language.
Selecting the right career opportunity in the right organization is one of the critical steps you have to take in this competitive IT world. So to help you in your preparation for the advancement of your career, HKR is providing you with the most frequently asked Snowflake interview questions. In this blog, we have divided the frequently asked interview questions into three levels: Basic level, Intermediate level and Experienced level. Let's start with our basic level interview questions.
Let's get started!
It is a cloud data-based warehouse that is used as a software as a service. It is made up of unique architecture for dealing with multiple aspects of data and analysis. Snowflake differs from any other traditional data warehouse solutions with advanced features such as simplicity, improved performance, high concurrency and profitability. The shared data architecture of Snowflake physically separates calculation and storage, which traditional offerings do not allow. It simplifies the process by allowing companies to store and analyze huge amounts of data with cloud tools. Snowflake transformed the data warehousing industry by allowing all data to be consolidated into one centralized system.
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Snowflake has a unique and advanced architecture. It is a mixture of shared-nothing and shared-disk architectures. It utilizes a central data repository for storing data in a consistent manner and makes it accessible from all the computing nodes of the platform. Like the shared-nothing architecture, Snowflake uses massively parallel processing computed clusters to run queries. With shared-disk architecture, data management is simplified. It provides improved performance and scalability.
Snowflake architecture is made up of three layers:
Query processing: In this layer, the virtual warehouses processes the queries.
Data Storage: Here, the data is arranged in columnar, internal optimized format.
Cloud Services: It is responsible for the coordination and management of all the associated activities in snowflake. It is also responsible for and delivers the best results when it comes to metadata management, infrastructure management, authentication, query analysis, and access control.
The usual ways to access Snowflake's data warehouse are:
Snowflake is natively designed for the cloud and deals with a number of problems that are not solved by conventional warehouse systems. Here are our top 5 benefits from using the Snowflake data platform:
Data security is a top priority of every organization. Snowflake meets the industry's highest safety standards for encrypting and securing data stored and customer accounts in Snowflake. It provides the best key management features without additional charge.
The following are the security measures that Snowflake uses to protect client data:
By default, all the data is compressed in Snowflake. Snowflake selects the top compression algorithms and cannot be configured by end-users. The best thing about Snowflake is that after compressing the data, Snowflake charges the customer according to the final size of the compressed data.
Benefits of data compression in snowflake:
Snowflake stores the data cache in the SSD along with the result cache to enhance the performance of SQL queries. It captures the result of each query that you execute, and each time a new query is submitted. It will check it with the previously executed queries to find out a match. If any related query is available, it utilizes a cached result set rather than running the query. It reduces the amount of time spent on queries and retrieves the results directly from the cache.
Various kinds of caching in Snowflake:
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The Snowflake Time Travel tool provides us with access to past data at any time during the specified period. This enables us to see which data we can edit or delete. This tool is used to accomplish the following tasks:
It is an advanced functionality available in Snowflake for ensuring data security. It is an essential part of the snowflake data protection lifecycle. It even offers additional seven days of storage even after the completion of the travel period.
Some of Snowflake's outstanding features include:
Snowflake has various editions which will assist the clients according to needs. They are as follows:
Standard Edition: This edition is perfect for beginners and is called the Introductory Level offering of Snowflake. It offers users limitless access to standard features.
Enterprise Edition: It comes with standard editing features and services and includes some of the extra f features needed for large Enterprises.
Business-critical edition: It is also referred to as an enterprise for sensitive data. business-critical edition offers high-level data protection support to protect sensitive data for meeting the needs of the organization.
Virtual Private Snowflake: It is responsible for providing a high level of security for organizations that handle financial activities.
A virtual warehouse is one or more clusters that approve users for carrying out operations such as data loading, queries, and other DML operations. Virtual warehouses endorse users with the required resources such as CPU, temporary storage to perform various snowflake operations.
To reduce the risk factor, DBA typically performs complete and incremental data backups on a regular basis. This process consumes more storage space and can sometimes be double or triple. In addition, the process of recovering data is expensive, takes time, requires a company downtime, and even more.
The snowflake data sharing option enables users to share data objects safely in a database of your account with other snowflake accounts. All database objects shared among snowflake accounts are readable and cannot be modified. Database objects that are shareable in Snowflake are external tables, secure views, tables, Secure materialized views and Secure UDFs.
There are three kinds of data sharing:
It is an implementation that enables us to create a copy of tables, schemas and databases without actually copying the data. For performing zero-copy in Snowflake, we must use a keyword named CLONE. This option allows you to obtain real-time data from production and carry out several actions.
Related Article: Snowflake Vs Redshift
Snowpipe is a constant and cost-effective service which we use to load the data into Snowflake. Systematically Snowpipe loads the file data as soon as it is feasible on the stage. Snowpipe makes the data loading process easier by loading the data into micro-batches and shaping the data to be analyzed. Some of the advantages of Snowpipe are:
Horizontal scaling enhances concurrency. When we need to support extra users, then we can increase the number of Virtual warehouses using auto-scaling to support and deal with more user requests instantly.
Vertical Scaling reduces processing times. When we have enormous workloads and want to optimize them and get them working faster, we can think about choosing a larger virtual warehouse size.
Each time the data is loaded into Snowflake, it organizes the data in a compressed, optimized, and columnar format. Following this process, the data is optimised and stored in the cloud. Following this process, the data is optimised and stored in the cloud. Snowflake is responsible for the way data is stored, including data organization, structure, compression, file size, metadata, statistics and many other aspects related to data storage. Any data objects stored in Snowflake are hidden and not accessible. Data objects can only be accessed by carrying out SQL query operations.
All the queries are executed on this processing layer. Snowflake utilizes "virtual warehouses for processing queries. Every virtual warehouse is a Massively Parallel Processing computing cluster consisting of several nodes assigned by snowflake’s cloud provider. In the query processing layer, every Virtual warehouse will not share its computational resources with other virtual warehouses. Each virtual warehouse is thus independent and does not have an impact on the other virtual warehouses in the event of a failover.
The Cloud Services layer is a collection of services which will coordinate several tasks on the Snowflake platform. All these services are linked and work with good coordination to deal with user requests, from sign in to query dispatch. This layer carries out the calculation of instances assigned by Snowflake’s cloud manager. The various services administered under this layer include:
A materialized view is a pre-computed dataset that is derived from query specification. Since the data is pre-computed, it becomes much easier to query the materialized view compared to a non-materialized view from the base table of the view. In plain language, materialized views are designed to improve the query performance of common and repetitive query models. Materialized views are the main database objects and accelerate projection, selection operations and expensive aggregation for queries that execute on larger datasets.
Schemas and databases used for the arrangement of the stored data. It is a logical grouping of database objects like views, tables, etc. The advantages of Snowflake diagrams are that they provide structured data and use limited disk space.
Some of the best ETL tools of Snowflake's are:
Snowflake supports various programming languages such as Go, C, . NET, Java, Python, Node.js, etc.
Related Article: Snowflake Vs BigQuery
It is a subset of columns in a table which helps us to co-locate the data inside the table. It is best suited to situations in which tables are extended; the sequence was not perfect because of DML.
The Stage acts like the central area we use to upload the files. Snowpipe discovers the files when they reach the staging area and loads them systematically into the snowflake.
Stages supported by snowflake are as follows:
Snowflake is developed as an OLAP(Online Analytical Processing) database system. Depending on the use, we may also use it as online transaction processing (OLTP).
Stored procedures enable us to create modular code that includes complex business logic by adding different SQL statements with procedure logic. Following are the steps to execute the Snowflake procedure:
The columnar database as opposed to traditional databases. It stores data in columns instead of rows, facilitates the analytical query processing method, and provides more incredible database performance. The Columnar database makes the analysis process easier and represents the future of business intelligence.
All the above are some of the frequently asked interview questions in the topmost companies. We trust this Frequently Asked Questions has been helpful to you. We are attempting to include more frequently asked questions that will help you get ready for your interview. Keep an eye out for HKR Trainings blogs for more questions.
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