Newline-Delimited Text-Based Data Format

A Newline-Delimited Text-Based Data Format is a text-based data format that separates data records using newline characters to enable line-by-line processing, streaming data parsing, and incremental data reading.

• AKA: Line-Delimited Format, Line-Oriented Data Format, Newline-Separated Format, Line-Based Data Format.
• Context:
  • It can typically separate individual data records with line terminators ([\n] or [\r\n]) for record boundary identification.
  • It can typically enable streaming data processing without loading entire files into memory.
  • It can typically support parallel processing through line-based data partitioning.
  • It can often facilitate append-only operations for log files and event streams.
  • It can often enable error recovery since corrupted lines don't affect other records.
  • It can often simplify data parsing through line-based tokenization.
  • It can support heterogeneous record types within the same file when using self-describing formats.
  • It can provide human readability while maintaining machine processability.
  • It can integrate with Unix command-line tools through pipe-based processing.
  • It can minimize parsing overhead compared to nested structure formats.
  • It can range from being a Simple Newline-Delimited Text-Based Data Format to being a Complex Newline-Delimited Text-Based Data Format, depending on its record structure.
  • It can range from being a Fixed-Schema Newline-Delimited Format to being a Schema-Free Newline-Delimited Format, depending on its structure flexibility.
  • It can serve as foundation for log file formats, streaming protocols, and batch processing systems.
  • ...
• Example(s):
  • Structured Newline-Delimited Formats, such as:
    • JSONL (JSON Lines) Format, with JSON objects per line.
    • NDJSON (Newline-Delimited JSON), for streaming JSON data.
    • CSV Format (when treating rows as records), for tabular data.
    • TSV Format, using tab-separated values per line.
  • Log File Formats, such as:
    • Apache Combined Log Format, for web server logs.
    • Common Log Format (CLF), for HTTP server logging.
    • Syslog Format, for system event logging.
    • Application Log Formats, with timestamp-prefixed lines.
  • Streaming Data Formats, such as:
    • Server-Sent Events (SSE) Format, for real-time web data.
    • Line Protocol Format, for time-series databases.
    • Kafka Message Format, for message queue records.
  • Command Output Formats, such as:
    • Unix Tool Output, from commands like grep, awk, sed.
    • Git Log Format, for commit history display.
    • Database Query Results in line-oriented output.
  • Configuration Formats, such as:
    • .env File Format, for environment variables.
    • Hosts File Format, for network address mapping.
    • Properties File Format, for key-value configuration.
  • ...
• Counter-Example(s):
  • XML Format, which uses hierarchical tag structure without line-based separation.
  • Binary Data Format, which uses byte-level encoding rather than text lines.
  • JSON Format (standard), which requires complete document parsing.
  • Protocol Buffers, which uses binary serialization without line delimiters.
  • Parquet Format, which uses columnar storage rather than line orientation.
  • Fixed-Width Format, which uses position-based fields rather than line delimiters.
• See: Text-Based Data Format, Line-Oriented Processing, Streaming Data Format, Data Record, JSONL Format, Log File Format, CSV Format, Stream Processing, Line Terminator, Text File Processing.

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