Which activities are included in the Cloud Sen/ices layer? (Select TWO).
Data storage
Dynamic data masking
Partition scanning
User authentication
Infrastructure management
The Cloud Services layer in Snowflake includes activities such as user authentication and infrastructure management. This layer coordinates activities across Snowflake, including security enforcement, query compilation and optimization, and more
User INQUISITIVE_PERSON has been granted the role DATA_SCIENCE. The role DATA_SCIENCE has privileges OWNERSHIP on the schema MARKETING of the database ANALYTICS_DW.
Which command will show all privileges granted to that schema?
SHOW GRANTS ON ROLE DATA_SCIENCE
SHOW GRANTS ON SCHEMA ANALYTICS_DW.MARKETING
SHOW GRANTS TO USER INQUISITIVE_PERSON
SHOW GRANTS OF ROLE DATA_SCIENCE
To show all privileges granted to a specific schema, the command SHOW GRANTS ON SCHEMA
Which Snowflake URL type allows users or applications to download or access files directly from Snowflake stage without authentication?
Directory
File
Pre-signed
Scoped
The pre-signed URL type allows users or applications to download or access files directly from a Snowflake stage without authentication. This URL type is open and can be used without needing to authenticate into Snowflake or pass an authorization token.
Which data type can store more than one type of data structure?
JSON
BINARY
VARCHAR
VARIANT
The VARIANT data type in Snowflake can store multiple types of data structures, as it is designed to hold semi-structured data. It can contain any other data type, including OBJECT and ARRAY, which allows it to represent various data structures
Where is Snowflake metadata stored?
Within the data files
In the virtual warehouse layer
In the cloud services layer
In the remote storage layer
Snowflake’s architecture is divided into three layers: database storage, query processing, and cloud services. The metadata, which includes information about the structure of the data, the SQL operations performed, and the service-level policies, is stored in the cloud services layer. This layer acts as the brain of the Snowflake environment, managing metadata, query optimization, and transaction coordination.
Which Snowflake object helps evaluate virtual warehouse performance impacted by query queuing?
Resource monitor
Account_usage. query_history
Information_schema.warehouse_load_history
Information schema.warehouse metering history
The Snowflake object that helps evaluate virtual warehouse performance impacted by query queuing is the Information_schema.warehouse_load_history. This view provides historical data about the load on a warehouse, including the average number of queries that were running or queued within a specific interval, which can be used to assess performance and identify potential issues with query queuing3.
A materialized view should be created when which of the following occurs? (Choose two.)
There is minimal cost associated with running the query.
The query consumes many compute resources every time it runs.
The base table gets updated frequently.
The query is highly optimized and does not consume many compute resources.
The results of the query do not change often and are used frequently.
A materialized view is beneficial when the query consumes many compute resources every time it runs (B), and when the results of the query do not change often and are used frequently (E). This is because materialized views store pre-computed data, which can speed up query performance for workloads that are run frequently or are complex
Query parsing and compilation occurs in which architecture layer of the Snowflake Cloud Data Platform?
Cloud services layer
Compute layer
Storage layer
Cloud agnostic layer
Query parsing and compilation in Snowflake occur within the cloud services layer. This layer is responsible for various management tasks, including query compilation and optimization
Which operations are handled in the Cloud Services layer of Snowflake? (Select TWO).
Security
Data storage
Data visualization
Query computation
Metadata management
The Cloud Services layer in Snowflake is responsible for various services, including security (like authentication and authorization) and metadata management (like query parsing and optimization). References: Based on general cloud architecture knowledge as of 2021.
Which of the following are considerations when using a directory table when working with unstructured data? (Choose two.)
A directory table is a separate database object.
Directory tables store data file metadata.
A directory table will be automatically added to a stage.
Directory tables do not have their own grantable privileges.
Directory table data can not be refreshed manually.
Directory tables in Snowflake are used to store metadata about data files in a stage. They are not separate database objects but are conceptually similar to external tables. Directory tables do not have grantable privileges of their own
What is a characteristic of the Snowflake Query Profile?
It can provide statistics on a maximum number of 100 queries per week.
It provides a graphic representation of the main components of the query processing.
It provides detailed statistics about which queries are using the greatest number of compute resources.
It can be used by third-party software using the Query Profile API.
The Snowflake Query Profile provides a graphic representation of the main components of the query processing. This visual aid helps users understand the execution details and performance characteristics of their queries4.
How can a Snowflake user optimize query performance in Snowflake? (Select TWO).
Create a view.
Cluster a table.
Enable the search optimization service.
Enable Time Travel.
Index a table.
To optimize query performance in Snowflake, users can cluster a table, which organizes the data in a way that minimizes the amount of data scanned during queries. Additionally, enabling the searchoptimization service can improve the performance of selective point lookup queries on large tables34.
Which of the following can be used when unloading data from Snowflake? (Choose two.)
When unloading semi-structured data, it is recommended that the STRIP_OUTER_ARRAY option be used.
Use the ENCODING file format option to change the encoding from the default UTF-8.
The OBJECT_CONSTRUCT function can be used to convert relational data to semi-structured data.
By using the SINGLE = TRUE parameter, a single file up to 5 GB in size can be exported to the storage layer.
Use the PARSE_JSON function to ensure structured data will be unloaded into the VARIANT data type.
The OBJECT_CONSTRUCT function is used in Snowflake to create a JSON object from relational data, which is useful when unloading semi-structured data. The SINGLE = TRUE parameter is used when unloading data to ensure that the data is exported as a single file, which can be up to 5 GB in size. References: [COF-C02] SnowPro Core Certification Exam Study Guide
How many resource monitors can be assigned at the account level?
1
2
3
4
Snowflake allows for only one resource monitor to be assigned at the account level. This monitor oversees the credit usage of all the warehouses in the account. References: Snowflake Documentation
How can a data provider ensure that a data consumer is going to have access to the required objects?
Enable the data sharing feature in the account and validate the view.
Use the CURRENT_ROLE and CURRENT_USER functions to validate secure views.
Use the CURRENT_ function to authorize users from a specific account to access rows in a base table.
Set the SIMULATED DATA SHARING CONSUMER session parameter to the name of the consumer account for which access is being simulated.
To ensure a data consumer has access to the required objects, a data provider can enable the data sharing feature and validate that the consumer can access the views or tables shared with them. References: Based on general data sharing practices in cloud services as of 2021.
What can a Snowflake user do in the Activity section in Snowsight?
Create dashboards.
Write and run SQL queries.
Explore databases and objects.
Explore executed query performance.
In the Activity section in Snowsight, Snowflake users can explore the performance of executed queries. This includes monitoring queries, viewing details about queries, including performance data, and exploring each step of an executed query in the query profile1.
Which pages are included in the Activity area of Snowsight? (Select TWO).
Contacts
Sharing settings
Copy History
Query History
Automatic Clustering History
The Activity area of Snowsight includes the Query History page, which allows users to monitor and view details about queries executed in their account, including performance data1. It also includes the Automatic Clustering History, which provides insights into the automatic clustering operations performed on tables2.
Which file format will keep floating-point numbers from being truncated when data is unloaded?
CSV
JSON
ORC
Parquet
The Parquet file format is known for preserving the precision of floating-point numbers when data is unloaded, preventing truncation of the values3.
Which kind of Snowflake table stores file-level metadata for each file in a stage?
Directory
External
Temporary
Transient
The kind of Snowflake table that stores file-level metadata for each file in a stage is a directory table. A directory table is an implicit object layered on a stage and stores file-level metadata about the data files in the stage3.
When unloading data to an external stage, what is the MAXIMUM file size supported?
1 GB
5 GB
10 GB
16 GB
When unloading data to an external stage, the maximum file size supported is 5 GB. This limit ensures efficient data transfer and management within Snowflake’s architecture
Two users share a virtual warehouse named wh dev 01. When one of the users loads data, the other one experiences performance issues while querying data.
How does Snowflake recommend resolving this issue?
Scale up the existing warehouse.
Create separate warehouses for each user.
Create separate warehouses for each workload.
Stop loading and querying data at the same time.
Snowflake recommends creating separate warehouses for each workload to resolve performance issues caused by shared virtual warehouses. This ensures that the resources are not being overutilized by one user’s activities, thereby affecting the performance of another user’s activities4.
When would Snowsight automatically detect if a target account is in a different region and enable cross-cloud auto-fulfillment?
When using a paid listing on the Snowflake Marketplace
When using a private listing on the Snowflake Marketplace
When using a personalized listing on the Snowflake Marketplace
When using a Direct Share with another account
Snowsight automatically detects if a target account is in a different region and enables cross-cloud auto-fulfillment when using a paid listing on the Snowflake Marketplace. This feature allows Snowflake to manage the replication of data products to consumer regions as needed, without manual intervention1.
If a virtual warehouse runs for 61 seconds, shuts down, and then restarts and runs for 30 seconds, for how many seconds is it billed?
60
91
120
121
Snowflake’s billing for virtual warehouses is per-second, with a minimum of 60 seconds for each time the warehouse is started or resumed. Therefore, if a warehouse runs for 61 seconds, it is billed for 61 seconds. If it is then shut down and restarted, running for an additional 30 seconds, it is billed for another 60 seconds (the minimum charge for a restart), totaling 121 seconds2
Which feature allows a user the ability to control the organization of data in a micro-partition?
Range Partitioning
Search Optimization Service
Automatic Clustering
Horizontal Partitioning
Automatic Clustering is a feature that allows users to control the organization of data within micro-partitions in Snowflake. By defining clustering keys, Snowflake can automatically reorganize the data in micro-partitions to optimize query performance1.
A user has a standard multi-cluster warehouse auto-scaling policy in place.
Which condition will trigger a cluster to shut-down?
When after 2-3 consecutive checks the system determines that the load on the most-loaded cluster could be redistributed.
When after 5-6 consecutive checks the system determines that the load on the most-loaded cluster could be redistributed.
When after 5-6 consecutive checks the system determines that the load on the least-loaded cluster could be redistributed.
When after 2-3 consecutive checks the system determines that the load on the least-loaded cluster could be redistributed.
In a standard multi-cluster warehouse with auto-scaling, a cluster will shut down when, after 2-3 consecutive checks, the system determines that the load on the least-loaded cluster could be redistributed to other clusters. This ensures efficient resource utilization and cost management. References: [COF-C02] SnowPro Core Certification Exam Study Guide
What is a responsibility of Snowflake’s virtual warehouses?
Infrastructure management
Metadata management
Query execution
Query parsing and optimization
Permanent storage of micro-partitions
Snowflake’s virtual warehouses are responsible for query execution. They are clusters of compute resources that execute SQL statements, perform DML operations, and load data into tables
What is used to diagnose and troubleshoot network connections to Snowflake?
SnowCD
Snowpark
Snowsight
SnowSQL
SnowCD (Snowflake Connectivity Diagnostic Tool) is used to diagnose and troubleshoot network connections to Snowflake. It runs a series of connection checks to evaluate the network connection to Snowflake
Which features could be used to improve the performance of queries that return a small subset of rows from a large table? (Select TWO).
Search optimization service
Automatic clustering
Row access policies
Multi-cluster virtual warehouses
Secure views
The search optimization service and automatic clustering are features that can improve the performance of queries returning a small subset of rows from a large table. The search optimization service is designed for low-latency point lookup queries, while automatic clustering organizes data in micro-partitions based on specific dimensions to reduce the amount of data scanned during queries.
Which statements reflect key functionalities of a Snowflake Data Exchange? (Choose two.)
If an account is enrolled with a Data Exchange, it will lose its access to the Snowflake Marketplace.
A Data Exchange allows groups of accounts to share data privately among the accounts.
A Data Exchange allows accounts to share data with third, non-Snowflake parties.
Data Exchange functionality is available by default in accounts using the Enterprise edition or higher.
The sharing of data in a Data Exchange is bidirectional. An account can be a provider for some datasets and a consumer for others.
A Snowflake Data Exchange allows groups of accounts to share data privately among the accounts (B), and it supports bidirectional sharing, meaning an account can be both a provider and a consumer of data (E). This facilitates secure and governed data collaboration within a selected group3.
How often are the Account and Table master keys automatically rotated by Snowflake?
30 Days
60 Days
90 Days
365 Days.
Snowflake automatically rotates the Account and Table master keys when they are more than 30 days old. Active keys are retired, and new keys are created, ensuring robust security through frequent key changes1
Which of the following statements describes a schema in Snowflake?
A logical grouping of objects that belongs to a single database
A logical grouping of objects that belongs to multiple databases
A named Snowflake object that includes all the information required to share a database
A uniquely identified Snowflake account within a business entity
A schema in Snowflake is a logical grouping of database objects, such as tables and views, that belongs to a single database. Each schema is part of a namespace in Snowflake, which is inferred from the current database and schema in use for the session5
What MINIMUM privilege is required on the external stage for any role in the GET REST API to access unstructured data files using a file URL?
READ
OWNERSHIP
USAGK
WRTTF
The minimum privilege required on an external stage for any role to access unstructured data files using a file URL in the GET REST API is READ. This allows the role to retrieve or download data files from the stage.
What can a Snowflake user do in the Admin area of Snowsight?
Analyze query performance.
Write queries and execute them.
Provide an overview of the listings in the Snowflake Marketplace.
Connect to Snowflake partners to explore extended functionality.
In the Admin area of Snowsight, users can analyze query performance, manage Snowflake warehouses, set up and view details about resource monitors, manage users and roles, and administer Snowflake accounts in their organization2.
Which Snowflake URL type is used by directory tables?
File
Pre-signed
Scoped
Virtual-hosted style
The Snowflake URL type used by directory tables is the scoped URL. This type of URL provides access to files in a stage with metadata, such as the Snowflake file URL, for each file
If a virtual warehouse is suspended, what happens to the warehouse cache?
The cache is dropped when the warehouse is suspended and is no longer available upon restart.
The warehouse cache persists for as long the warehouse exists, regardless of its suspension status.
The cache is maintained for up to two hours and can be restored If the warehouse Is restarted within this limit.
The cache is maintained for the auto suspend duration and can be restored it the warehouse 15 restarted within this limit.
When a virtual warehouse in Snowflake is suspended,the cache is dropped and is no longer available upon restart. This means that all cached data, including results and temporary data, are cleared from memory. The purpose of this behavior is to conserve resources while the warehouse is not active. Upon restarting the warehouse, it will need to reload any data required for queries from storage, which may result in a slower initial performance until the cache is repopulated. This is a critical consideration for managing performance and cost in Snowflake.
What are the main differences between the account usage views and the information schema views? (Select TWO).
No active warehouse to needed to query account usage views but one is needed to query information schema views.
Account usage views do not contain data about tables but information schema views do.
Account issue views contain dropped objects but information schema views do not.
Data retention for account usage views is 1 year but is 7 days to 6 months for information schema views, depending on the view.
Information schema views are read-only but account usage views are not.
The account usage views in Snowflake provide historical usage data about the Snowflake account, and they retain this data for a period of up to 1 year. These views include information about dropped objects, enabling audit and tracking activities. On the other hand, information schema views provide metadata about database objects currently in use, such as tables and views, but do not include dropped objects. The retention of data in information schema views varies, but it is generally shorter than the retention for account usage views, ranging from 7 daysto a maximum of 6 months, depending on the specific view.References:Snowflake Documentation on Account Usage and Information Schema
Snowflake's access control framework combines which models for securing data? (Select TWO).
Attribute-based Access Control (ABAC 1
Discretionary Access Control (DAC)
Access Control List (ACL)
Role-based Access Control (RBAC)
Rule-based Access Control (RuBAC)
Snowflake's access control framework utilizes a combination of Discretionary Access Control (DAC) and Role-based Access Control (RBAC). DAC in Snowflake allows the object owner to grant access privileges to other roles. RBAC involves assigning roles to users and then granting privileges to those roles. Through roles, Snowflake manages which users have access to specific objects and what actions they can perform, which is central to security and governance in the Snowflake environment.References:Snowflake Documentation on Access Control,
In the Data Exchange, who can get or request data from the listings? (Select TWO).
Users with ACCOUNTADMIN role
Users with sysadmin role
Users with ORGADMIN role
Users with import share privilege
Users with manage grants privilege
In the Snowflake Data Exchange, the ability to get or request data from listings is generally controlled by specific roles and privileges:
A. Users with ACCOUNTADMIN role: This role typically has the highest level of access within a Snowflake account, including the ability to manage and access all features and functions. Users with this role can access data listings within the Data Exchange.
D. Users with import share privilege: This specific privilege is necessary for users who need to import shared data from the Data Exchange. This privilege allows them to request and access data listings explicitly shared with them.
What is the MINIMUM size of a table for which Snowflake recommends considering adding a clustering key?
1 Kilobyte (KB)
1 Megabyte (MB)
1 Gigabyte (GB)
1 Terabyte (TB)
Snowflake recommends considering adding a clustering key to a table when its size reaches1 Terabyte (TB)or larger. Clustering keys help optimize the storage and query performance by organizing the data in a table based on the specified columns. This is particularly beneficial for large tables where data retrieval can become inefficient without proper clustering.
Why Clustering Keys Are Important:Clustering keys ensure that data stored in Snowflake is physically ordered in a way that aligns with the most frequent accesspatterns, thereby reducing the amount of scanned data during queries and improving performance.
Recommendation Basis:The recommendation for tables of size 1 TB or larger is based on the observation that smaller tables generally do not benefit as much from clustering, given Snowflake's architecture. However, as tables grow in size, the benefits of clustering become more pronounced.
Implementing Clustering Keys:
To set a clustering key for a table, you can use theCLUSTER BYclause during table creation or alter an existing table to add it:
CREATETABLEmy_table (... ) CLUSTERBY(column1, column2);
Or for an existing table:
ALTERTABLEmy_table CLUSTERBY(column1, column2);
Who can activate a network policy for users in a Snowflake account? (Select TWO)
ACCOUNTADMIN
USERADMIN
PUBLIC
SYSADMIN
Any role that has the global ATTACH POLICY privilege
Network policies in Snowflake are used to control access to Snowflake accounts based on IP address ranges. These policies can be activated by specific roles that have the necessary privileges.
Role: ACCOUNTADMIN:
The ACCOUNTADMIN role has full administrative rights across the Snowflake account.
This role can manage all aspects of the Snowflake environment, including network policies.
Role with Global ATTACH POLICY Privilege:
Any role that has been granted the global ATTACH POLICY privilege can activate network policies.
This privilege allows the role to attach policies that control network access to the account.
References:
Snowflake Documentation: Network Policies
How can an administrator check for updates (for example, SCIM API requests) sent to Snowflake by the identity provider?
ACCESS_HISTORY
LOAD_HISTORY
QUERY_HISTORY
REST EVENT HISTORY
To monitor updates, such as SCIM API requests sent to Snowflake by the identity provider, an administrator can use theREST EVENT HISTORYfeature. This feature allows administrators to query historical data about REST API calls made to Snowflake, including those related to user and role management through SCIM (System for Cross-domain Identity Management).
TheREST EVENT HISTORYtable function returns information about REST API calls made over a specified period. It is particularly useful for auditing and monitoring purposes, especially when integrating Snowflake with third-party identity providers that use SCIM for automated user provisioning and deprovisioning.
An example query to check for SCIM API requests might look like this:
SELECT*FROMTABLE(information_schema.rest_event_history(date_range_start=>dateadd('hours',-1,current_timestamp())))WHERErequest_type ='SCIM';
This query returns details on SCIM API requests made in the last hour, including the request type, the identity provider's details, and the outcome of each request.
At what level is the MIN_DATA_RETENSION_TIME_IN_DAYS parameter set?
Account
Database
Schema
Table
TheMIN_DATA_RETENTION_TIME_IN_DAYSparameter is set at theAccountlevel in Snowflake. This parameter specifies the minimum number of days Snowflake retains the historical data for time travel, which allows users to access and query data as it existed at previous points in time.
Here's how to understand and adjust this parameter:
Purpose of MIN_DATA_RETENTION_TIME_IN_DAYS:This parameter is crucial for managing data lifecycle and compliance requirements within Snowflake. It determines the minimum time frame for which you can perform operations like restoring deleted objects or accessing historical versions of data.
Setting the Parameter:Only account administrators can set or modify this parameter. It is done at the account level, impacting all databases and schemas within the account. The setting can be adjusted based on the organization's data retention policy.
Adjusting the Parameter:
To view the current setting, use:
SHOWPARAMETERSLIKE'MIN_DATA_RETENTION_TIME_IN_DAYS';
To change the setting, an account administrator can execute:
ALTERACCOUNTSETMIN_DATA_RETENTION_TIME_IN_DAYS =
What are potential impacts of storing non-native values like dates and timestamps in a variant column in Snowflake?
Faster query performance and increased storage consumption
Slower query performance and increased storage consumption
Faster query performance and decreased storage consumption
Slower query performance and decreased storage consumption
Storing non-native values, such as dates and timestamps, in a VARIANT column in Snowflake can lead to slower query performance and increased storage consumption. VARIANT is a semi-structured data type that allows storing JSON, AVRO, ORC, Parquet, or XML data in a single column. When non-native data types are stored as VARIANT, Snowflake must perform implicit conversion to process these values, which can slow down query execution. Additionally, because the VARIANT data type is designed to accommodate a wide variety of data formats, it often requires more storage spacecompared to storing data in native, strongly-typed columns that are optimized for specific data types.
The performance impact arises from the need to parse and interpret the semi-structured data on the fly during query execution, as opposed to directly accessing and operating on optimally stored data in its native format. Furthermore, the increased storage consumption is a result of the overhead associated with storing data in a format that is less space-efficient than the native formats optimized for specific types of data.
References:
Snowflake Documentation on Semi-Structured Data: Semi-Structured Data
Use of which file function allows a user to share unstructured data from an internal stage with an external reporting tool that does not have access to Snowflake">
BUILD_SCOPED_FILE_URL
GET_PRESIGNED_URL
BUILD_STAGE_FILE_URL
GET_STAGE_LOCATION
TheGET_PRESIGNED_URLfunction in Snowflake generates a pre-signed URL for a file in an internal stage. This URL can be shared with external tools or users who do not have direct access to Snowflake, allowing them to download the file.
Generate Pre-Signed URL:
SELECT GET_PRESIGNED_URL(@my_stage/file.txt);
Share the URL:The generated URL can be shared with external users or applications, enabling them to access the file directly.
References:
Snowflake Documentation: GET_PRESIGNED_URL
Snowflake Documentation: Working with Stages
Which command will unload data from a table into an external stage?
PUT
INSERT
COPY INTO
GET
In Snowflake, theCOPY INTO <location>command is used to unload (export) data from a Snowflake table to an external stage, such as an S3 bucket, Azure Blob Storage, or Google Cloud Storage. This command allows users to specify the format, file size, and other options for the data being unloaded, making it a flexible solution for exporting data from Snowflake to external storage solutions for further use or analysis.References:Snowflake Documentation on Data Unloading
Which roles can make grant decisions to objects within a managed access schema? (Select TWO)
ACCOUNTADMIN
SECURITYADMIN
SYSTEMADMIN
ORGADMIN
USERADMIN
Managed Access Schemas:These are a special type of schema designed for fine-grained access control in Snowflake.
Roles with Grant Authority:
ACCOUNTADMIN: The top-level administrative role can grant object privileges on all objects within the account, including managed access schemas.
SECURITYADMIN: Can grant and revoke privileges on objects within the account, including managed access schemas.
Important Note:The ORGADMIN role focuses on organization-level management, not object access control.
Which function can be used to convert semi-structured data into rows and columns?
TABLE
FLATTEN
PARSE_JSON
JSON EXTRACT PATH TEXT
To convert semi-structured data into rows and columns in Snowflake, theFLATTENfunction is utilized.
FLATTEN Function: This function takes semi-structured data (e.g., JSON) and transforms it into a relational table format by breaking down nested structures into individual rows. This process is essential for querying and analyzing semi-structured data using standard SQL operations.
Example Usage:
SELECT
f.value:attribute1 AS attribute1,
f.value:attribute2 AS attribute2
FROM
my_table,
LATERAL FLATTEN(input => my_table.semi_structured_column) f;
References:
Snowflake Documentation on FLATTEN
While running a query on a virtual warehouse in auto-scale mode, additional clusters are stated immediately if which setting is configured?
A)
B)
C)
D)
Option A
Option B
Option C
Option D
In Snowflake, auto-scaling allows virtual warehouses to automatically start additional clusters to handle increasing query loads. The setting that triggers the immediate startof additional clusters when a warehouse is running in auto-scale mode is:A. MAX_CLUSTER_COUNT is increased and new_max_clusters is greater than running_clusters: When the maximum number of clusters (MAX_CLUSTER_COUNT) is increased and the new maximum is higher than the number of clusters currently running (running_clusters), additional clusters will start immediately if required by the workload. This configuration ensures that performance scales with demand by allowing more compute resources to be provisioned as needed.
This behavior is designed to maintain performance by dynamically adjusting the compute resources without manual intervention, ensuring that queries are executed with minimal delay, even under varying workloads. It aligns with the principles of elasticity and scalability in cloud computing, particularly within Snowflake's architecture.
Which function can be used with the copy into
FLATTEN
OBJECT_AS
OBJECT_CONSTRUCT
TO VARIANT
The correct function to use with theCOPY INTO <location>statement to convert rows from a relational table into a single variant column and to unload rows into a JSON file isTO VARIANT. TheTO VARIANTfunction is used to explicitly convert a value of any supported data type into a VARIANT data type. This is particularly useful when needing to aggregate multiple columns or complex data structures into a single JSON-formatted string, which can then be unloaded into a file.
In the context of unloading data, theCOPY INTO <location>statement combined withTO VARIANTenables the conversion of structured data from Snowflake tables into a semi-structured VARIANT format, typically JSON, which can then be efficiently exported and stored. This approach is often utilized for data integration scenarios, backups, or when data needs to be shared in a format that is easily consumed by various applications or services that support JSON.
References:
Snowflake Documentation on Data Unloading: Unloading Data
Snowflake Documentation on VARIANT Data Type: Working with JSON
What can be used to process unstructured data?
External tables
The copy into