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NEW QUESTION # 56
When unloading from a snowflake table to an internal or external stage, the COPY INTO command supports which of the below ones?
Answer: A,B,C,D,E
NEW QUESTION # 57
You have created a TASK in snowflake.
How will you resume it?
Answer: B
NEW QUESTION # 58
How is the change of local time due to daylight savings time handled in Snowflake tasks? (Choose two.)
Answer: A,C
Explanation:
According to the Snowflake documentation1 and the web search results2, these two statements are true about how the change of local time due to daylight savings time is handled in Snowflake tasks. A task is a feature that allows scheduling and executing SQL statements or stored procedures in Snowflake. A task can be scheduled using a cron expression that specifies the frequency and time zone of the task execution.
* A task scheduled in a UTC-based schedule will have no issues with the time changes. UTC is a universal time standard that does not observe daylight savings time. Therefore, a task that uses UTC as the time zone will run at the same time throughout the year, regardless of the local time changes1.
* Task schedules can be designed to follow specified or local time zones to accommodate the time changes. Snowflake supports using any valid IANA time zone identifier in the cron expression for a task. This allows the task to run according to the local time of the specified time zone, which may include daylight savings time adjustments. For example, a task that uses Europe/London as the time zone will run one hour earlier or later when the local time switches between GMT and BST12.
References:
* Snowflake Documentation: Scheduling Tasks
* Snowflake Community: Do the timezones used in scheduling tasks in Snowflake adhere to daylight savings?
NEW QUESTION # 59
Which of the below privileges are required for search optimization?
Answer: A,C
NEW QUESTION # 60
A company is storing large numbers of small JSON files (ranging from 1-4 bytes) that are received from IoT devices and sent to a cloud provider. In any given hour, 100,000 files are added to the cloud provider.
What is the MOST cost-effective way to bring this data into a Snowflake table?
Answer: C
Explanation:
* A pipe is a Snowflake object that continuously loads data from files in a stage (internal or external) into a table. A pipe can be configured to use auto-ingest, which means that Snowflake automatically detects new or modified files in the stage and loads them into the table without any manual intervention1.
* A pipe is the most cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it minimizes the number of COPY commands executed and the number of micro-partitions created. A pipe can use file aggregation, which means that it can combine multiple small files into a single larger file before loading them into the table. This reduces the load time and the storage cost of the data2.
* An external table is a Snowflake object that references data files stored in an external location, such as Amazon S3, Google Cloud Storage, or Microsoft Azure Blob Storage. An external table does not store the data in Snowflake, but only provides a view of the data for querying. An external table is not a cost-effective way to bring data into a Snowflake table, because it does not support file aggregation, and it requires additional network bandwidth and compute resources to query the external data3.
* A stream is a Snowflake object that records the history of changes (inserts, updates, and deletes) made to a table. A stream can be used to consume the changes from a table and apply them to another table or a task. A stream is not a way to bring data into a Snowflake table, but a way to process the data after it is loaded into a table4.
* A copy command is a Snowflake command that loads data from files in a stage into a table. A copy command can be executed manually or scheduled using a task. A copy command is not a cost-effective way to bring large numbers of small JSON files into a Snowflake table, because it does not support file aggregation, and it may create many micro-partitions that increase the storage cost of the data5.
References: : Pipes : Loading Data Using Snowpipe : External Tables : Streams : COPY INTO <table>
NEW QUESTION # 61
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