Storage Metadata Pre-Storage Operation Association
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Solution Overview
Problem
Current storage systems lack the ability to efficiently associate and perform pre-storage operations on data, leading to suboptimal storage resource utilization and compression results, as well as increased I/O exchanges in distributed systems.
Innovation Solution
A storage system that allows users to associate pre-storage operations with sets of data prior to storage, using storage metadata to determine the appropriate operations based on data type, granularity, and precedence, enabling efficient compression, encryption, and error correction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If pre-storage operations are not associated with data sets, then the storage system is simpler to operate, but compression performance and storage resource utilization deteriorate
Solution Approach 1:
The storage system automatically determines and applies appropriate pre-storage operations to data sets based on their characteristics without requiring manual configuration. The system self-manages the association between data sets and operations by examining data types, granularities, and precedence rules, eliminating the need for users to manually configure compression settings while achieving optimal compression performance.
Solution Approach 2:
The system changes operational parameters dynamically based on data characteristics. By declaring directives that specify data types, granularities, and precedence levels, the system adapts the pre-storage operations applied to different data sets, transforming a static storage system into one that automatically optimizes compression parameters based on the specific characteristics of each data set.
2Manufacturing precision
If pre-storage operations are manually configured for each data object, then compression results improve, but the complexity of the system increases
Solution Approach 1:
The patent creates a universal framework for pre-storage operations that can handle multiple data types, granularities, and operation kinds through a single declarative directive system. Rather than requiring separate manual configurations for each data object, the system defines operations at higher levels (data types, granularities) that automatically apply to multiple data objects, reducing system complexity while maintaining optimal compression results.
Solution Approach 2:
The system performs preliminary configuration by declaring directives that establish pre-storage operations for categories of data (data types, granularities) before actual data storage occurs. This preliminary action creates a template system where future data objects automatically inherit appropriate operations based on their classification, eliminating the need for manual configuration of each individual data object while maintaining high compression results.
3Quantity of substance
If pre-storage operations are applied to all data, then storage resource utilization improves, but I/O exchanges in distributed systems increase
Solution Approach 1:
The patent applies pre-storage operations selectively based on local data characteristics rather than uniformly to all data. By defining operations at specific granularities (column, table, database levels) and specifying data types that qualify for particular operations, the system applies compression only where beneficial, reducing unnecessary I/O exchanges in distributed systems while maintaining high storage resource utilization for data that benefits from compression.
4Manufacturing precision
If fine-tuning of operations is enabled at data type level, then compression performance improves, but the difficulty of configuring the system increases
Solution Approach 1:
The system performs preliminary configuration by establishing pre-storage operations at the data type level through declarative directives before actual data storage. Users declare the desired operations, data types, and granularities in advance, and the system automatically applies these configurations to matching data objects. This preliminary action simplifies the configuration process by eliminating the need for manual fine-tuning of each data object while achieving optimal compression performance through type-based generalization.
Data Source
AI summary
A specified data type and pre-storage operation are receive. In response, an association between the two is created in storage metadata. After the association is created, data to be stored is received where the data has a data type. In response to receiving the data, the storage metadata, including the association, is accessed and it is determined if the data type of the data is the same as the specified one. If so, the specified pre-storage operation is automatically performed on the data in order to obtain an output and the output is stored.