* Version 3
* trying to optimize memory access (-0.2s)
- use smaller segments confined to thread
- unload in parallel
* Only call MemorySegment.address() once (~200ms)
* Squashing a bunch of commits together.
Commit#2; Uplift of 7% using native byteorder from ByteBuffer.
Commit#1: Minor changes to formatting.
* Commit #4: Parallelize munmap() and reduce completion time further by
10%. As the jvm exits with exit(0) syscall, the kernel reclaims the
memory mappings via munmap() call. Prior to this change. all the unmap()
calls were happening right at the end as the JVM exited. This led to
serial execution of about 350ms out of 2500 ms right at the end after
each shard completed its work. We can parallelize it by exposing the
Cleaner from MappedByteBuffer and then ensure that it is truly parallel
execution of munmap() by using a non-blocking lock (SeqLock). The
optimal strategy for when each thread must call unmap() is an interesting math problem with an exact solution and this code roughly reflects it.
Commit #3: Tried out reading long at a time from bytebuffer and
checking for presence of ';'.. it was slower compared to just reading int().
Removed the code for reading longs; just retaining the
hasSemicolonByte(..) check code
Commit #2: Introduce processLineSlow() and processRangeSlow() for the
tial part.
Commit #1: Create a separate tail piece of work for the last few lines to be
processed separately from the main loop. This allows the main loop to
read past its allocated range (by a 'long' if we reserve atleast 8 bytes
for the tail piece of work.)
* Golang implementation
* Speed up by avoiding copying the lines
* Memory mapping
* Add script for testing
* Now passing most of the tests
* Refactor to composed method
* Now using integer math throughout
* Now using a state machine for parsing!
* Refactoring state names
* Enabling profiling
* Running in parallel!
* Fully parallel!
* Refactor
* Improve type safety of methods
* The rounding problem is due to difference between Javas and Gos printf implementation
* Converting my solution to Java
* Merging results
* Splitting the file in several buffers
* Made it parallel!
* Removed test file
* Removed go implementation
* Removed unused files
* Add header to .sh file
---------
Co-authored-by: Matteo Vaccari <mvaccari@thoughtworks.com>
* Modify baseline version to improve performance
- Consume and process stream in parallel with memory map buffers, parsing it directly
- Use int instead of float/double to store values
- Use Epsilon GC and graal
* Update src/main/java/dev/morling/onebrc/CalculateAverage_adriacabeza.java
* Update calculate_average_adriacabeza.sh
---------
Co-authored-by: Gunnar Morling <gunnar.morling@googlemail.com>
* - Read file in multiple threads if available: 17" -> 15" locally
- Changed String to BytesText with cache: 12" locally
* - Fixed bug
- BytesText to Text
- More checks when reading the file
* - Combining measurements should be thread safe
- More readability changes
* Initial version
* Small result merge optimisation
* Switched from reading bytes to longs
* Reading into internal buffer, test fixes
* Licence and minor string creation optimisation
* Hash collision fix
* Initial commit with custom implementation, 2:40
* Initial file-channel based version, 1:27
* Individual maps for executors, 0:54
* Use better-suited map: 0:34
* Verified correct, skip CharBuffer, :37
* Minor improvements and cleanup, 0:24
* String to byte[], 0:21
* Additional cleanup, use GraalVM, 0:17
* Faster number handling, 0:11
* Faster buffer reading, 0:08
* Prepare for environment with variable RAM and CPU, 0:08
* Fix bug causing issues with certain buffer sizes
* Larger overhead to not miss long station names that overlap buffers
* Reorder scripts and fix one-off bug
