Indexing Service Concurrent Aggregate Updates
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Solution Overview
Problem
In cloud computing environments, conventional indexing approaches face challenges in managing and retrieving data efficiently due to the large volume of granular data distributed across multiple locations, leading to increased latency and inconsistencies between base and aggregated documents.
Innovation Solution
An indexing service is implemented to monitor and update data in real-time, applying changes to aggregated documents concurrently with base document updates, reducing latency and inconsistencies by processing fewer documents and eliminating the need for post-processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional indexing approaches are used to manage distributed data, then data retrieval functionality is provided, but latency increases and inconsistencies occur between base and aggregated documents
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing aggregate documents before they are needed. The system maintains aggregate documents that are updated in advance through concurrent processing, so when queries need aggregated data, it is already available without requiring real-time computation, thus reducing latency while maintaining consistency
Solution Approach 2:
The patent introduces aggregate documents as an intermediary layer between base documents and queries. This intermediary pre-aggregates data from multiple base documents and makes it available for quick retrieval, eliminating the need for queries to directly access and process large volumes of distributed base documents, thereby reducing latency while maintaining data consistency
2Adaptability or versatility
If granular data is distributed across multiple locations in cloud computing, then data accessibility is improved, but indexing complexity increases
Solution Approach 1:
The patent merges the indexing operations for base documents and aggregate documents into a single concurrent processing framework. Instead of maintaining separate indexing systems for distributed base documents and their aggregates, the system combines both operations, allowing them to be processed together and reducing overall indexing complexity while maintaining data accessibility across distributed locations
Solution Approach 2:
The patent creates a universal indexing service that handles both base documents and aggregate documents through the same mechanism. This multi-functional approach allows the system to manage distributed data and aggregated data with a single indexing framework, reducing complexity while maintaining accessibility across the cloud computing environment
3Reliability
If base documents are updated, then data currency is improved, but inconsistencies occur with aggregated documents requiring post-processing
Solution Approach 1:
The patent implements continuity of useful action by making the update of aggregate documents a continuous, concurrent process that happens simultaneously with base document indexing. Instead of updating aggregates after base documents are indexed (discontinuous post-processing), the system continuously maintains aggregate documents in sync with base documents through concurrent processing, ensuring data currency without sacrificing productivity
Solution Approach 2:
The patent applies preliminary action by preparing and updating aggregate documents in advance through concurrent processing. When base documents are updated, the system proactively updates associated aggregate documents during the same processing window, rather than waiting for post-processing triggers, ensuring data currency is maintained without requiring additional post-processing steps
Data Source
AI summary
Approaches provide for management of resources such as data storage devices. For example, such approaches include providing an indexing service to reliably index data that may be accessed and used over one or more networks by any of various users, applications, processes, and/or services. As one example, data storage devices that store data may in some embodiments be co-located at a geographical location, such as in each of one or more geographically distributed data centers, and the application(s) that use a volume stored on a data storage device may execute on one or more other physical computing devices. An indexing service can operate on more or more of the data storage devices or portions of the data storage devices such as a directory, to manage and index data. The indexing service can monitor activity on a data storage device and any additions, deletions and/or modifications to data (e.g., documents, files, etc.) in a particular data storage device cause the indexing service to update its index while concurrently updating any aggregated documents associated with the data. The index can then be accessed by any of a number of applications in the same manner as conventional indexes.