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A Data Engineer needs to load JSON output from some software into Snowflake using Snowpipe. Which recommendations apply to this scenario? (Choose three.)
A.
Load large files (1 GB or larger).
B.
Ensure that data files are 100-250 MB (or larger) in size, compressed.
C.
Load a single huge array containing multiple records into a single table row.
D.
Verify each value of each unique element stores a single native data type (string or number).
E.
Extract semi-structured data elements containing null values into relational columns before loading.
F.
Create data files that are less than 100 MB and stage them in cloud storage at a sequence greater than once each minute.
A - incorrect as size too large; C - incorrect as not good practice for any data platform;
F - Quote from Snowflake:
Creating smaller data files and staging them in cloud storage more often than once per minute has the following disadvantages:
- A reduction in latency between staging and loading the data cannot be guaranteed.
- An overhead to manage files in the internal load queue is included in the utilization costs charged for Snowpipe. This overhead increases in relation to the number of files queued for loading.
Loading data files roughly 100-250 MB in size or larger reduces the overhead charge relative to the amount of total data loaded to the point where the overhead cost is immaterial.
https://docs.snowflake.com/en/user-guide/data-load-considerations-prepare#label-snowpipe-file-size
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