Binary Data Protocol for Schemaless Records Without Deserialization
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Solution Overview
Problem
Existing data processing systems face challenges in efficiently handling large volumes of schemaless data in distributed environments due to high CPU and memory requirements for serialization and deserialization, especially in environments with automated garbage collection, and lack support for modification without deserialization.
Innovation Solution
A unified serialization and processing format that supports interleaved network transport and processing of encoded data records, allowing for read-only and modifying operations without deserialization, using a format with a validity indicator, type information, and meta data for efficient access and modification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If Protocol Buffers or Protobuf framework is used for automated serialization and deserialization of data records, then development effort is reduced due to encapsulated network communication logic, but CPU and memory resources increase significantly leading to performance issues at high record volumes
Solution Approach 1:
The patent extracts the critical serialization/deserialization overhead by implementing a custom binary format that eliminates the need for complex Protobuf frameworks. The solution uses a simplified header structure with record type, length, and validity flags that can be processed with minimal CPU instructions, directly addressing the resource consumption issue while maintaining ease of implementation through a clear format specification
Solution Approach 2:
The patent changes the serialization parameters by using a fixed-header binary format instead of variable-length Protobuf encoding. The header contains explicit fields for record type (1 byte), length (4 bytes), and validity (1 byte), which enables faster parsing with simple byte stream processing rather than complex protocol validation, significantly reducing CPU and memory overhead
2Ease of manufacture
If Protocol Buffers framework is used for data record transfer, then network communication logic is encapsulated and development is simplified, but processing time increases when the number of processed records increases
Solution Approach 1:
The patent removes the heavy Protobuf framework dependency by implementing a lightweight custom binary format. The network communication logic is simplified to basic read/write operations on binary streams, eliminating the processing time overhead associated with Protobuf's complex serialization/deserialization while maintaining development simplicity through a well-defined format
Solution Approach 2:
The patent implements efficient processing by skipping unnecessary validation steps. The binary format includes explicit length and type fields that allow direct memory access and parsing without protocol verification, enabling rapid throughput of large numbers of records with minimal processing overhead per record
3Ease of manufacture
If automated garbage collection is used in Java or .NET environments, then memory management is simplified, but serialization/deserialization creates short-lived objects that increase garbage collection burden
Solution Approach 1:
The patent replaces heavy Protobuf objects with a lightweight binary stream representation that can be processed directly in memory. The custom format uses simple byte arrays and primitive types instead of complex serialized objects, significantly reducing the number of short-lived objects created during processing and thereby reducing garbage collection frequency and overhead
Solution Approach 2:
The patent extracts the object creation overhead by processing data as raw binary streams rather than through Protobuf object instantiation. This eliminates the allocation of numerous short-lived Protobuf messages and enables more efficient memory utilization that aligns better with garbage collection patterns, improving overall system throughput
4Adaptability or versatility
If schemaless or semi-structured data is ingested to handle modern monitoring environments, then monitoring capability is extended to handle diverse data formats, but data structure analysis and semantic alignment require additional pre-processing steps
Solution Approach 1:
The patent performs preliminary structuring action by implementing a fixed binary format with predefined fields for record type, length, and validity. This pre-structured format eliminates the need for runtime schema analysis and semantic alignment, as the structure is explicitly defined in the binary header rather than inferred from the data content, significantly reducing pre-processing complexity while maintaining versatility
Solution Approach 2:
The patent changes the data representation parameters by converting schemaless data into a standardized binary format with explicit structural metadata. The format includes fixed-field headers that define the structure beforehand, transforming the data from requiring complex analysis to enabling direct, efficient processing with minimal pre-processing overhead
Data Source
AI summary
A serialization data format for the transfer, analysis, and modification of schemaless mass data is proposed. The data format supports stream oriented, pipeline-based processing, and it enables read access of contained data without deserialization, and modification access that only requires the deserialization of portions of structure and meta data. Incoming, semi-structured data records may be transformed into records of the proposed serialization data format, compressed and stored in processing buffers containing multiple of those records. During processing, only individual records are decompressed, and processed records are then compressed and stored in output processing buffers for efficient memory usage. Manipulations of data records are performed by appending new values to data records, invalidating old ones and updating access data structures to refer to new values instead of old ones, to enable various modification activities by only requiring append or not-size-changing operations of serialized data records.