Slim Analytics Server for Offline Document Processing

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Solution Overview

Problem

Analytics platforms face memory and CPU usage issues due to the need for an offline document processing engine, which consumes significant resources and introduces latency when handling large offline documents, and can impact online document processing and server functionality.

Innovation Solution

Implementing a lightweight analytics server that operates without an offline document processing engine, using a slim analytics server in online mode for online documents and communicating with an offline document server for offline documents, allowing separate process execution to manage memory and reduce latency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If an offline document processing engine is bundled within the analytics server as an in-memory database, then offline documents can be processed, but significant memory and CPU usage is consumed

Engineering Contradiction:

Improvecapability to process offline documentsVSAvoidmemory and CPU usage

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The system is divided into two separate components: a slim analytics server that handles online document processing and an offline document server that handles offline document processing. This segmentation allows each component to be optimized independently, with the slim analytics server consuming minimal resources while the offline document server handles large document loads separately.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The offline document processing engine is extracted from the analytics server, creating a separate offline document server. This extraction removes the memory and CPU burden from the analytics server while preserving the capability to process offline documents through the separate server component.

Inventive Principle:

Principle #2Taking out (Extraction)

2Quantity of substance

If the offline document processing engine reaches memory threshold, then pagination is triggered to free-up memory, but significant latency is introduced

Engineering Contradiction:

Improvememory managementVSAvoiddata access latency

Core Design Contradiction:

Quantity of substanceVSLoss of time

Solution Approach 1:

The offline document server pre-loads and caches document data into memory before analytics processing is needed. This preliminary action ensures that when analytics queries are executed, the data is already available in memory, eliminating the need for pagination during query execution and reducing access latency.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically manages memory allocation between the slim analytics server and the offline document server. The offline document server can allocate substantial memory for caching when needed, while the slim analytics server maintains a lightweight memory footprint, allowing flexible memory management without rigid thresholds triggering pagination.

Inventive Principle:

Principle #15Dynamics

3Adaptability or versatility

If the offline document processing engine is bundled within the analytics server, then offline document processing is enabled, but online document processing is impacted

Engineering Contradiction:

Improveoffline document processing capabilityVSAvoidonline document processing efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system segments document processing into two independent paths: online document processing handled by the slim analytics server and offline document processing handled by the offline document server. This segmentation eliminates resource contention between online and offline processing, allowing both to operate at optimal efficiency simultaneously.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The offline document processing functionality is extracted as a separate server component, removing its impact on the analytics server's online document processing performance. The slim analytics server can focus exclusively on online processing without being burdened by offline document loading and management operations.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS11409710B2Lightweight analytics server to handle heterogeneous document types

Publication Date: 2022.08.09 SAP SE

AI summary

Methods, systems, and computer-readable storage media for receiving, by a web tier, an analytics request from a client device, determining, by the web tier, that the analytics request implicates at least one offline document, transmitting, by the web tier, at least a portion of the analytics request to a slim analytics server of an analytics platform, the slim analytics server operating in an offline mode and, in response to receiving the at least a portion of the analytics request, the slim analytics server communicates with an offline document server that loads data from the at least one offline document and executes one or more computations on the data to provide analytics results to the slim analytics server, receiving, by the web tier, the first analytics results from the first slim analytics server, and transmitting, by the web tier, a response to the client device, the response including the analytics results.