this outlines a strategy for processing newline-separated data from streams or files using multiple threads.

processing large volumes of newline-separated data with:

• efficient handling of large input
• support for multithreaded execution
• compatibility with streams and multiple large files

• buffers:

  • two buffers, data[0] and data[1], alternate during reading
  • data[0] is initially filled from the input source

• newline search:

  • after data is read into data[0], the algorithm locates the last newline in the second half of the buffer
  • if no newline is found, the buffer is either expanded or an error is returned if a line exceeds the allowed length

• line handling:

  • any data after the last newline is moved to the beginning of data[1]

  • the next read continues into data[1], with buffers alternating to ensure all lines are preserved and completed

input is assumed to be line-aligned, with eof or end of stream marked by a newline.

• buffer chains: multiple threads process data via a sequence of buffers. only one thread reads from the input, but all threads can operate on their respective buffers

• file metadata optimization:

  • file size metadata is used to group small files and partition large ones efficiently

  • threads may seek to predefined offsets in large files, enabling parallel file processing

the fgets() function reads a line from a stream into a buffer. while simple and portable, it introduces overhead:

• buffer size constraint: predefined buffer sizes may be insufficient for long lines, requiring multiple reads
• data copying: data is copied from internal to user buffers, incurring memory overhead
• per-call cost: each fgets() call performs checks and incurs function overhead, reducing throughput on large data sets

modern libraries may optimize fgets() through:

• internal buffering to reduce system calls
• simd-based character scanning
• thread-safe implementations with minimal locking

however, these optimizations are insufficient for cases involving extremely large data volumes or strict memory/performance control.

this algorithm mitigates fgets() limitations by:

• reading large chunks to reduce system call frequency and call overhead
• exposing direct pointers into the buffer to avoid unnecessary data copies
• scanning large blocks for newlines to process multiple lines per operation

• long lines: the buffer can grow dynamically if no newline is found. alternatively, a line-length cap can be enforced and excess data skipped
• incomplete lines: partial lines at the end of a buffer are copied to the start of the next buffer to ensure continuity
• thread usage: each thread processes an independent buffer to parallelize data parsing and improve throughput

• synchronization: thread contention is minimized since reading is serialized but parsing is parallel
• i/o vs. cpu bound: reading large chunks benefits i/o-bound applications. cpu-bound gains depend on parsing cost
• error handling: partial reads, i/o failures, and buffer overflows must be explicitly managed for robust behavior

this algorithm offers benefits over fgets() for:

• large-scale data processing where minimizing system calls and copies matters
• scenarios involving long lines or fragmented input
• environments where multithreaded processing improves throughput