What is scale up and scale out in Snowflake?
Snowflake supports two ways to scale warehouses: Scale up by resizing a warehouse. Scale out by adding clusters to a multi-cluster warehouse (requires Snowflake Enterprise Edition or higher).
Scaling Out is the process of adding more clusters to an existing warehouse. This will assist when there are a large number of concurrent queries being executed in the same warehouse. Scaling Out will allow for those queued queries to be executed on the new provisioned cluster.
Scale down the amount of data processed or the resources needed to perform the processing; Scale up the computing resources on a node, via parallel processing and faster memory/storage technologies; and. Scale out the computing to distributed nodes in a cluster/cloud or at the edge where the data resides.
Horizontal scaling means that you scale by adding more machines into your pool of resources whereas Vertical scaling means that you scale by adding more power (CPU, RAM) to an existing machine.
Stages in Snowflake are locations used to store data. If the data that needs to be loaded into Snowflake is stored in other cloud regions like AWS S3 or Azure or GCP then these are called External stages whereas if the data is stored inside Snowflake then these are called Internal stages.
Creates a copy of an existing object in the system. This command is primarily used for creating zero-copy clones of databases, schemas, and tables; however, it can also be used to quickly/easily create clones of other schema objects (i.e. external stages, file formats, and sequences).
Scaling up is adding further resources, like hard drives and memory, to increase the computing capacity of physical servers. Whereas scaling out is adding more servers to your architecture to spread the workload across more machines.
While scaling out involves adding more discrete units to a system in order to add capacity, scaling up involves building existing units by integrating resources into them.
: an increase according to a fixed ratio.
The main difference between scaling up and scaling out is that horizontal scaling simply adds more machine resources to your existing machine infrastructure. Vertical scaling adds power to your existing machine infrastructure by increasing power from CPU or RAM to existing machines.
What are the two scaling policies supported by Snowflake?
Snowflake supports two ways to scale warehouses: Scale up by resizing a warehouse. Scale out by adding clusters to a multi-cluster warehouse (requires Snowflake Enterprise Edition or higher).
While horizontal scaling refers to adding additional nodes, vertical scaling describes adding more power to your current machines. For instance, if your server requires more processing power, vertical scaling would mean upgrading the CPUs. You can also vertically scale the memory, storage, or network speed.
The Snowflake cloud architecture separates data warehousing into three distinct functions: compute resources (implemented as virtual warehouses), data storage, and cloud services. The costs associated with using Snowflake are based on your usage of each of these functions.
As previously noted, Snowflake's virtual data warehouses are deployed on clusters of fixed shape sizes of 1, 2, 4, 8, 16, 32, 64, or 128 nodes. Each node is equivalent to 4 cores per Snowflake virtual data warehouse.
A size-8 (Large) warehouse will always start and provision 8 nodes. Never just one, two, or less than 8.
A materialized view is a pre-computed data set derived from a query specification (the SELECT in the view definition) and stored for later use. Because the data is pre-computed, querying a materialized view is faster than executing a query against the base table of the view.
1) Internal Stages
In Internal Stages of Snowflake Stages basically, the data is stored internally. There are 3 types of Internal Stages: Each user's Personal Storage Area is called the User Stage. These Stages are personal to the user, which means no one else can see them.
Together, a database and schema comprise a namespace in Snowflake. When performing any operations on database objects in Snowflake, the namespace is inferred from the current database and schema in use for the session.
Cloning in Snowflake is much faster than cloning in other databases. Depending on the size of the source item, it could take several minutes. Until you make any changes, snowflake copying shares the same storage. However, as soon as you make adjustments, it begins its own lifetime for partition changes.
Fail-safe provides a (non-configurable) 7-day period during which historical data may be recoverable by Snowflake. This period starts immediately after the Time Travel retention period ends.
What is variant in Snowflake?
In a Snowflake OBJECT, each key is a VARCHAR, and each value is a VARIANT. Because VARIANT can store any other data type, different values (in different key-value pairs) can have different underlying data types. For example, an OBJECT can hold a person's name as a VARCHAR and a person's age as an INTEGER.
Scale out is a growth architecture or method that focuses on horizontal growth, or the addition of new resources instead of increasing the capacity of current resources (known as scaling up).
To scale out is the process of selling off portions of total shares held while the price increases. To scale out, or scaling out, means to exit a position by selling in increments as the price of the stock climbs.
A startup is considered “a company that is newly established as a necessity in the market, generally in the technology field, with growth potential,” whereas a scale-up is “a relatively young, rapidly emerging, innovation-driven company” that's experienced a high level of growth over the past three years.
Performance. While scale-up allows you to increase the performance of existing hardware, as well as extending its lifecycle, scale-out enables you to take advantage of newer server technologies in running fault tolerance, system monitoring, and minimize downtime.
To scale horizontally (scaling in or out), you add more resources like servers to your system to spread out the workload across machines, which in turn increases performance and storage capacity. Horizontal scaling is especially important for businesses with high availability services requiring minimal downtime.
Scaling out, or horizontal scaling, involves adding servers for parallel computing. The scale out technique is a long-term solution, as more and more servers may be added when needed. But going from one monolithic system to this type of cluster may be a difficult, although extremely effective solution.
While horizontal scaling refers to adding additional nodes, vertical scaling describes adding more power to your current machines. For instance, if your server requires more processing power, vertical scaling would mean upgrading the CPUs. You can also vertically scale the memory, storage, or network speed.
A clustering key is a subset of columns in a table (or expressions on a table) that are explicitly designated to co-locate the data in the table in the same micro-partitions.
Zero-Copy Cloning (sometimes called simply "cloning") is a Snowflake feature that makes a copy of a database without duplicating the data it contains. The clone operation takes a snapshot of the source data when the clone is created, and makes this data available to the cloned object.