18345987. SCHEMA EVOLUTION simplified abstract (Snowflake Inc.)

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SCHEMA EVOLUTION

Organization Name

Snowflake Inc.

Inventor(s)

Istvan Cseri of Seattle WA (US)

Benoit Dageville of San Mateo CA (US)

Ganeshan Ramachandran Iyer of Redmond WA (US)

Yucan Liu of Bellevue WA (US)

Jiaqi Yan of Menlo Park CA (US)

SCHEMA EVOLUTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18345987 titled 'SCHEMA EVOLUTION

Simplified Explanation

Abstract

Techniques for detecting and handling schema mismatches in data uploading are disclosed. The schema of the data to be uploaded is compared with the schema of the source table. If a mismatch is found, the schema of the source table can be modified to accommodate the new data without losing any existing data.

Bullet Points

  • The patent application describes techniques for detecting and handling schema mismatches during data uploading.
  • It involves comparing the schema of the data to be uploaded with the schema of the source table.
  • If a mismatch is detected, the schema of the source table can be modified to accommodate the new data.
  • This allows the upload process to continue without any loss of existing data.

Potential Applications

  • Database management systems
  • Data integration platforms
  • E-commerce platforms
  • Data warehousing systems

Problems Solved

  • Schema mismatches during data uploading can cause data loss or errors.
  • Modifying the schema of the source table manually can be time-consuming and error-prone.
  • Existing solutions may not handle schema evolution efficiently.

Benefits

  • Prevents data loss during data uploading by detecting and handling schema mismatches.
  • Automates the modification of the source table schema to accommodate new data.
  • Saves time and reduces errors by eliminating the need for manual schema modifications.
  • Enables efficient schema evolution in database management systems.


Original Abstract Submitted

Techniques for schema mismatch detection and evolution are described. When data is being uploaded into a source table, schema of the data to be uploaded can be compared with the schema for the source table. If a schema mismatch is detected, the schema of the source table can be modified, and the upload can be continued without data loss.