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
2 months agoVelda
12 days agoBrynn
13 days agoLenna
16 days agoSunshine
20 days agoJessenia
23 days agoLing
28 days agoLeslee
1 months agoShayne
1 months agoVernell
3 months agoErick
3 months agoGeraldine
2 months agoJacquelyne
2 months agoLeonor
2 months agoTonja
3 months agoJulieta
3 months agoValentin
3 months agoElise
2 months agoCordie
2 months agoChristoper
2 months agoTonja
3 months agoThaddeus
3 months agoMalika
2 months agoCaprice
2 months agoMargo
3 months ago