Cloud technology has revolutionized how the business landscape works. Today, companies have no hassle retrieving and storing valuable data regarding their employees, customers, and products. Using this information, such firms can make critical business decisions and predict trends to stay ahead of their competitors. The sheer size of data generated by companies has led to the emergence of the term data warehousing. Snowflake Multi Cluster is one such data warehouse.
In simple terms, a data warehouse is a system used to store a company’s operational database and other external sources. One of the most significant advantages of data warehouses is storing historical information. This way, concerned parties can analyze data from a period of their choosing. Snowflake is a big market player in this field, which brings us to the core purpose of this post- snowflake Multi cluster Warehouses. By the end of this post, you should have understood what Snowflake is, its features, and what Snowflake Multi cluster warehouses are. Take a read below.
Table of Contents
What is Snowflake?
In simple terms, Snowflake is a SaaS-based data warehouse platform built over AWS infrastructure. One of the features behind this software’s popularity with businesses worldwide is its scalability, making it cost-effective. The architecture involves virtual compute instances and efficient storage buckets that run solely on the cloud.
Key features of Snowflake
Below are some of the key features of snowflake:
- Standard and Extended SQL Support- Since Snowflake is an SQL-based platform, it supports all standard and extended SQL commands.
- Web-based graphical user interface- Snowflake offers users an interactive dashboard to connect with the cloud. Using the tool, you can monitor system usage and query data.
- Command-line client- This comes as a separate downloadable tool you can install for querying data and other functions. It is built using Python and is a great way to interact with the data warehouse.
- Extensive Integration Features- Snowflake supports integration with a wide array of third-party tools such as Google Cloud.
Learn more about Snowflake.
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What are Snowflake Multi Cluster Warehouses?
In Snowflake, you need a computer resource to run any task. This is nothing more than a virtual warehouse that is simply referred to as a warehouse. What is it? In simple terms, it is a cluster of computing resources. This can be a combination of CPU, memory, and temporary storage that all work in tandem to accomplish an assigned task. It is also worth noting that these warehouses come in various sizes and an increase in size translates to an increase in allocated computing resources.
Interestingly, Snowflake warehouses come in T-shirt sizes. For instance, X-small has one server per cluster and 3-X Large has 64 servers per cluster. This is where scaling a server up and down comes into play. Simply put, this is increasing the number of servers per cluster and can be used to improve query performance for larger and more complex queries. With all this information in mind, what are Snowflake Multi Cluster warehouses? Read on to find out.
In a normal Snowflake situation, the size of the virtual warehouse would determine the computing resources allocated. This means the bigger the warehouse, the more the computing resources. As queries are submitted to a warehouse, it allocates resources to query and starts the execution process. In a scenario where the computing resources are insufficient, the warehouse queues the unexecuted queries until the resources are available.
With Snowflake Multi Cluster warehouses, you can scale computing resources to manage the query needs in time and accommodate the changes. This is especially useful when the queries come in waves during peak and off-hours.
You need to specify the following properties when creating a Snowflake Multi Cluster warehouse:
- The max number of warehouses should be greater than one and less than 10.
- The minimum number of warehouses should be equal to or less than the maximum. It is also worth noting that Snowflake Multi Cluster warehouses have the same functionality as single warehouses.
Furthermore, you have the option of running your Snowflake Multi Cluster warehouse in either of the following modes:
Snowflake Multi Cluster modes: Maximized
You specify the same number of warehouses for both the maximum and the minimum warehouses in this mode. Hence, Snowflake starts all the warehouses when the multicluster warehouse is started. It is ideal if you have a steady flow of large queries or user sessions. The lack of fluctuations ensures the maximum warehouses and their resources are utilized.
Snowflake Multi Cluster modes: AutoScale
Contrary to maximized, you specify different values for both the minimum and the maximum values of warehouses. This way, Snowflake allocated warehouses as needed, where it dynamically manages the load on the warehouse.
When the number of queries increases such that the ones with insufficient resources are queued, Snowflake starts additional warehouses up to the maximum user-defined value. Similarly, when the number of queries reduces, Snowflake automatically shuts down warehouses to reduce resource usage, reducing the number of credits used.
For each hour, the number of credits consumed depends on the number of warehouses running during each hour the multi-cluster warehouse is on.
Benefits of Snowflake Multi Cluster Warehouses
The benefits of a Snowflake Multi Cluster warehouse depend on the mode in which the warehouse is running. For instance, in autoscale mode, you do not need to resize the warehouse to accommodate fluctuating queries as you would in a regular warehouse. Snowflake will handle this process for you. Furthermore, you can control the multicluster warehouse capacity in maximized mode as needed. In summary, Multi-cluster warehouses automate the query management process for users.
In this post, you got acquainted with Snowflake and understood its features. Moreover, you got a thorough introduction to multicluster warehouses and saw the different modes you can run them in. Lastly, you understood what makes these warehouses better than regular ones and why you should implement them.
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