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?
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.
Larae
17 days agoVernell
25 days agoErick
26 days agoJacquelyne
4 days agoLeonor
16 days agoTonja
28 days agoJulieta
29 days agoValentin
1 months agoCordie
13 days agoChristoper
16 days agoTonja
1 months agoThaddeus
1 months agoMalika
16 days agoCaprice
17 days agoMargo
25 days ago