Elastic Data Ingestion Subsystem for Energy Exploration
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Solution Overview
Problem
Energy exploration systems face challenges in efficiently ingesting diverse and complex data sets, including issues with data format variations, incomplete or incorrect data, different coordinate systems, and the impact of computing resource faults, which can lead to slow and unreliable data ingestion processes.
Innovation Solution
A data ingestion system is implemented with a parsing subsystem to encode records into intermediate geographical object records, a conversion subsystem to format these records according to specific sink specifications, and a publication subsystem to export them to designated tenants, allowing for parallel processing and error resilience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single data ingestion process is used to handle diverse data sets, then the system structure is simple, but the processing speed is slow and the system is unreliable
Solution Approach 1:
The data ingestion system is divided into multiple independent ingestion processes, each capable of handling specific data sets. Each process includes separate parsing, conversion, and publication subsystems that operate independently in parallel, enabling simultaneous processing of multiple data sets without mutual interference, thus improving overall ingestion speed while maintaining modular system architecture.
Solution Approach 2:
The system transitions from sequential single-process handling to parallel multi-process architecture, adding the dimension of concurrent execution. Multiple ingestion processes run simultaneously on different computing resources, transforming the time dimension from linear sequential processing to parallel simultaneous processing, thereby dramatically increasing throughput.
2Loss of time
If data is processed sequentially through parsing, conversion, and publication, then the system is simple to manage, but the total processing time is long
Solution Approach 1:
The data ingestion pipeline is segmented into three independent subsystems: parsing subsystem, conversion subsystem, and publication subsystem. Each subsystem processes data independently and can operate in parallel with others, eliminating sequential bottlenecks. The parsing subsystem encodes records into intermediate geographical object records, the conversion subsystem formats these records according to sink specifications, and the publication subsystem exports formatted records to designated tenants, all simultaneously.
Solution Approach 2:
The system performs preliminary encoding of data records into a standardized intermediate geographical object format during the parsing phase. This preliminary standardization enables subsequent conversion and publication operations to proceed independently and in parallel, as each downstream subsystem receives pre-processed data in a consistent format, reducing overall processing time.
3Adaptability or versatility
If computing resources are allocated statically, then resource management is simple, but the system cannot handle variable data loads efficiently
Solution Approach 1:
The system employs dynamic resource allocation where computing resources are not fixed but can be allocated and deallocated based on actual data ingestion needs. Multiple ingestion processes can dynamically access available computing resources, and the system can scale resource allocation up or down depending on the volume and complexity of data sets being processed, enabling efficient handling of variable data loads.
Solution Approach 2:
The ingestion processes are designed to be universal and can handle various types of data sets with different formats and requirements. Each ingestion process can dynamically adapt to different data sources, applying appropriate parsing strategies and conversion rules, making the system versatile across different data scenarios without requiring dedicated resources for each data type.
4Productivity
If all data records are processed through the same parsing logic, then the parsing logic is simple, but the system cannot handle different data formats efficiently
Solution Approach 1:
The parsing subsystem applies different parsing logic locally based on the specific data format being processed. Each ingestion process can identify the data format and apply appropriate parsing rules specific to that format, rather than forcing all data through a single uniform parsing approach. This localized adaptation to different data qualities and formats improves processing efficiency while maintaining manageable parsing logic through format-specific optimization.
Data Source
AI summary
An energy exploration system includes a plurality of computer nodes. Each of the computer nodes includes a processor and memory coupled to the processor. The computer nodes are configured to implement a data ingestion system configured to add a data set to the energy exploration system. The data ingestion system includes a parsing subsystem, a conversion subsystem, and a publication subsystem. The parsing subsystem includes a plurality of parser instances configured to encode records of the data set as intermediate geographical object records. The conversion subsystem includes a plurality of conversion instances configured to format the intermediate geographical object records according to a sink specific specification to produce formatted geographic object records. The publication subsystem includes a plurality of publication instances configured to export the formatted geographic object records to a designated tenant.