In-Memory MDAV Runtime for Search Engine Analytical Views

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Solution Overview

Problem

Conventional business software frameworks face performance issues due to the need to replicate large data structures from search engine servers to application servers for multidimensional analytical views, leading to increased processing costs and inefficiencies, especially when handling large datasets.

Innovation Solution

Implementing an in-memory multidimensional analytical view (MDAV) runtime at the search engine server to execute data operations such as union, join, and filtering directly, reducing the need for data replication by aggregating and preprocessing data using a calculation engine, and utilizing a temporary index for transactional changes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If data structures are replicated from search engine server to application server for multidimensional analytical views, then analytical processing can be performed, but processing costs and time increase significantly

Engineering Contradiction:

Improveanalytical processing speedVSAvoiddata replication time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent pre-aggregates and preprocesses data at the search engine server before it reaches the application server. By performing data aggregation, filtering, and transformation operations in advance during data ingestion and storage phases, the system eliminates the need for time-consuming data replication and preprocessing at query time, thus resolving the contradiction between analytical processing speed and data replication time.

Inventive Principle:

Principle #10Preliminary action

2Ease of operation

If complete data replication is performed from search engine server to application server, then data access is enabled, but processing costs and network bandwidth consumption increase

Engineering Contradiction:

Improvedata access capabilityVSAvoidprocessing cost

Core Design Contradiction:

Ease of operationVSLoss of energy

Solution Approach 1:

The patent extracts and computes only the essential aggregated data and statistical measures needed for analytical views at the search engine server, rather than replicating complete detailed data structures. This selective extraction of necessary information enables data access functionality while significantly reducing network bandwidth consumption and processing costs associated with transferring and storing redundant data.

Inventive Principle:

Principle #2Taking out (Extraction)

3Quantity of substance

If data operations are performed on-disk rather than in-memory, then storage capacity is sufficient, but processing speed decreases

Engineering Contradiction:

Improvedata storage capacityVSAvoiddata processing speed

Core Design Contradiction:

Quantity of substanceVSSpeed

Solution Approach 1:

The patent changes the physical state parameter of data from persistent on-disk storage to volatile in-memory representation for active analytical processing. By loading aggregated data and maintaining working datasets in server memory rather than reading from disk during query execution, the system achieves dramatically faster data processing speeds while maintaining sufficient storage capacity through selective data retention and efficient memory management.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS9177037B2In-memory runtime for multidimensional analytical views

Publication Date: 2015.11.03 SAP SE

AI summary

A multi-dimensional analytical view (MDAV) calculation can be enhanced by use of an in-memory MDAV runtime at a search engine server. The in-memory MDAV runtime can perform all or some of the processing required to respond to a data request that requires some analytical processing.