A company is trying to Ingest 10 TB of CSV data into a Snowflake table using Snowpipe as part of Its migration from a legacy database platform. The records need to be ingested in the MOST performant a

The correct answer is D. Use on error = SKIP_FILE in the copy into command.. For ingesting a large volume of CSV data into Snowflake using Snowpipe, especially for a substantial amount like 10 TB, the on error = SKIP_FILE option in the COPY INTO command can be highly effective. This approach allows Snowpipe to skip over files that cause errors during the

Performance Optimization

Question

A company is trying to Ingest 10 TB of CSV data into a Snowflake table using Snowpipe as part of Its migration from a legacy database platform. The records need to be ingested in the MOST performant and cost-effective way. How can these requirements be met?

Options

AUse ON_ERROR = continue in the copy into command.
BUse purge = TRUE in the copy into command.
CUse FURGE = FALSE in the copy into command.
DUse on error = SKIP_FILE in the copy into command.

How the community answered

(35 responses)

A
6% (2)
B
3% (1)
C
14% (5)
D
77% (27)

Explanation

For ingesting a large volume of CSV data into Snowflake using Snowpipe, especially for a substantial amount like 10 TB, the on error = SKIP_FILE option in the COPY INTO command can be highly effective. This approach allows Snowpipe to skip over files that cause errors during the ingestion process, thereby not halting or significantly slowing down the overall data load. It helps in maintaining performance and cost-effectiveness by avoiding the reprocessing of problematic files and continuing with the ingestion of other data.

Topics

#Snowpipe#COPY INTO#Error Handling#Performance Optimization

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