Document Store Export Normalization for Import Consistency
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Solution Overview
Problem
The challenge lies in exporting data from a source document store to a target system, where unique file identifiers and timestamps in the source system can conflict with or be incompatible with those in the target system, leading to data inconsistencies and import issues.
Innovation Solution
A normalization process is applied to the binary files from the source document store, modifying file identifiers and commit timestamps, and generating new files as needed, to ensure compatibility with the target system, thereby facilitating seamless import and maintaining data consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If direct export of binary files from source document store is performed, then data transfer efficiency is improved, but identifier and timestamp conflicts arise causing import inconsistencies
Solution Approach 1:
The patent applies preliminary action by normalizing file identifiers and commit timestamps in the exported binary files before they are imported into the target document store. This pre-processing step modifies the source system's identifiers and timestamps to be compatible with the target system's format, preventing conflicts during import while maintaining efficient data transfer. The normalization process occurs during the export operation itself, ensuring that the data is ready for immediate import without requiring post-processing or re-exporting.
2Adaptability or versatility
If file identifiers and timestamps are modified during export, then compatibility with target system is improved, but additional processing steps are required
Solution Approach 1:
The patent applies self-service by implementing the normalization logic within the export process itself, allowing the source document store system to automatically adapt its binary files for target system compatibility. The export mechanism includes built-in functionality to detect and transform identifiers and timestamps, eliminating the need for separate manual normalization steps or external processing tools. This self-contained approach reduces overall process complexity while maintaining high adaptability between different document store systems.
Data Source
AI summary
Provided are systems and methods to acquire a manifest data file and a binary copy of a document store slice log having a first filename and comprising a plurality of entries, each of the plurality of entries associated with a respective database transaction and a commit identifier, and the manifest data file indicating one or more data partitions and one or more slices of each of the one or more data partitions, acquire a partition log for one of the indicated one or more data partitions, the generated partition log comprising a log entry associated with a transaction to create a slice and including a second filename associated with the slice, sort the plurality of entries of the document store slice log based on their associated commit identifiers, change the commit identifiers of each of the plurality of entries to a same commit identifier, and store the sorted and changed entries in a second document store slice log having the second filename.