squashfs-tools-ng VS RocksDB

... except that that is also subtly broken.

It works if you write multiple UTF-8 code-units in one go, but breaks if you send them in several writes, or if you use the ANSI API (with the A suffix). Guess what the Windows implementation of stdio (printf and friends) does.

I already had some fun with this: https://github.com/AgentD/squashfs-tools-ng/issues/96#issuec...

And we didn't even discuss command line argument passing yet :-)

I tried to test it with the only other two languages I know besides English: German and Mandarin. Specifically also, because the later requires multi-byte characters to work. Getting this to work at all in a Windows terminal on an existing, German Windows 7 installation was an adventure on it's own.

Turns out, trying to write language agnostic command line applications on Windows is a PITA.

IIRC fanalyzer is a fairly recent addition to gcc. Has it become reasonable usable yet?

I recall getting a bit excited when I first read about it, but the results I got where rather bizarre (e.g. every single function that allocated memory and returned a pointer to it was labeled as leaking memory).

It did the fun exercise myself once to riffle through the gcc manpage, cobble together warning flags and massage them into autoconf[1][2].

There is a very handy m4 script in the util-linux source for testing supported warning flags[3].

[1] https://git.infradead.org/mtd-utils.git/blob/HEAD:/configure...

[2] https://github.com/AgentD/squashfs-tools-ng/blob/master/conf...

[3] https://github.com/karelzak/util-linux/blob/master/m4/compil...

> Honestly I think you could be a little more respectful of the project that inspired yours.

I do. I had a lot of great "Huh? That's clever!" moments while reverse engineering the format and formed a mental image of a clearly brilliant programmer who managed to squeeze the last bits out of some data structures using really clever tricks that I myself probably wouldn't have come up with. During that time I gained a lot of respect for the project and the author.

Also, please don't forget: the whole project is the filesystem, the tools are just a part of that. I care about this project, which is why I decided to start this effort in the first place. Which I explicitly did not advertise as a replacement, but an augmentation (see [2]).

> I'd be angry too ... Definitely understandable.

Yes, I agree! And I can understand why in the heat of the moment you might write something angry and threatening. But certainly not if you've had a few weeks time to calm down and think things over.

> And you plagiarized part of his readme.

https://github.com/plougher/squashfs-tools/blob/master/RELEA...

https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/lin...

https://github.com/AgentD/squashfs-tools-ng/blob/master/READ...

Oh yes? Which part?

> ... calling it spaghetti code (which isn't immediately verifiable)

Here you go, have fun: https://github.com/plougher/squashfs-tools/blob/master/squas...

However, I cannot blame anyone here, I totally get how those things happen and have witnessed it myself in action:

You write a simple tool supporting a larger project. It's written by the seat of your pants without much planning, since it's not big and does one simple job. Then it gets used in production, eventually requirements change, other people pile on patches, but try to keep the diff small, so it's reviewable and it receives maybe a little less care than the actual project it supports. Nobody bothers to overhaul it or write documentation because, hey, it works, and any large changes might risk breaking things.

Even if nobody is to blame for it, the end result is still the same: an undocumented mess that is hard to wrap your head around if you aren't the original author, who is the only one with the bigger picture.

I tried for roughly a week to pull the code (there are some more files than this and some of the inter dependencies are nasty) apart into stacked utility libraries and a pure command line parsing front end, with the hopes to maybe get this upstream once it is done. I gave up and decided that at this point I understood enough about the format to start afresh and not touch what I believed to be an unmaintained mess.

FWIW there is an on various BSDs that contains "beXXtoh", "leXXtoh", "htobeXX", "htoleXX" where XX is a number of bits (16, 32, 64).

That header is also available on Linux, but glibc (and compatible libraries) put named it instead.

See: man 3 endian (https://linux.die.net/man/3/endian)

Of course it gets a bit hairier if the code is also supposed to run on other systems.

MacOS has OSSwapHostToLittleIntXX, OSSwapLittleToHostIntXX, OSSwapHostToBigIntXX and OSSwapBigToHostIntXX in .

I'm not sure if Windows has something similar, or if it even supports running on big endian machines (if you know, please tell).

My solution for achieving some portability currently entails cobbling together a "compat.h" header that defines macros for the MacOS functions and including the right headers. Something like this:

https://github.com/AgentD/squashfs-tools-ng/blob/master/incl...

This is usually my go-to-solution for working with low level on-disk or on-the-wire binary data structures that demand a specific endianness. In C I use "load/store" style functions that memcpy the data from a buffer into a struct instance and do the endian swapping. The copying is also necessary because the struct in the buffer may not have proper alignment.

In C++ code, all of this can of course be neatly stowed away in a special class with overloaded operators that transparently takes care of everything and "decays" into a single integer and exactly the above code after compilation, but is IMO somewhat cleaner to read and adds much needed type safety.

I once foolishly thought, I'll write a tar parser because, "how hard can it be" [1].

I simply tried to follow the tar(5) man page[2], and got a reference test set from another website posted previously on HN[3].

Along the way I discovered that NetBSD pax apparently cannot handle the PAX format[3] and my parser inadvertently uncovered that git-archive was doing the checksums wrong, but nobody noticed because other tar parsers were more lax about it[4].

As the article describes (as does the man page), tar is actually a really simple format, but there are just so many variants to choose from.

Turns out, if you strive for maximum compatibility, it's easiest to stick to what GNU tar does. If you think about it, IMO in many ways the GNU project ended up doing "embrace, extend, extinguish" with Unix.

[1] https://github.com/AgentD/squashfs-tools-ng/tree/master/lib/...

[2] https://www.freebsd.org/cgi/man.cgi?query=tar&sektion=5

[3] https://mgorny.pl/articles/portability-of-tar-features.html

[4] https://www.spinics.net/lists/git/msg363049.html

A while ago I did some simplistic SquashFS pack/unpack benchmarks[1][2]. I was primarily interested in looking at the behavior of my thread-pool based packer, but as a side effect I got a comparison of compressor speed & ratios over the various available compressors for my Debian test image.

I must say that LZ4 definitely stands out for both compression and uncompression speed, while still being able to cut the data size in half, making it probably quite suitable for life filesystems and network protocols. Particularly interesting was also comparing Zstd and LZ4[3], the former being substantially slower, but at the same time achieving a compression ratio somewhere between zlib and xz, while beating both in time (in my benchmark at least).

[1] https://github.com/AgentD/squashfs-tools-ng/blob/master/doc/...

[2] https://github.com/AgentD/squashfs-tools-ng/blob/master/doc/...

[3] https://github.com/AgentD/squashfs-tools-ng/blob/master/doc/...

RocksDB: A high-performance embedded database optimized for multi-core CPUs and fast storage like SSDs. Its use of a log-structured merge-tree (LSM tree) makes it suitable for applications requiring high throughput and efficient storage, such as streaming data processing.

[RocksDB](https://rocksdb.org/) isn’t a distributed storage system, fwiw. It’s an embedded KV engine similar to LevelDB, LMDB, or really sqlite (though that’s full SQL, not just KV)

To output the top 3 rocks, our engine has to first store all the rocks in some sorted way. To do this, we of course picked RocksDB, an embedded lexicographically sorted key-value store, which acts as the sorting operation's persistent state. In our RocksDB state, the diffs are keyed by the value of weight, and since RocksDB is sorted, our stored diffs are automatically sorted by their weight.

The in-memory version of Memgraph uses Delta storage to support multi-version concurrency control (MVCC). However, for larger-than-memory storage, we decided to use the Optimistic Concurrency Control Protocol (OCC) since we assumed conflicts would rarely happen, and we could make use of RocksDB’s transactions without dealing with the custom layer of complexity like in the case of Delta storage.

I was looking at https://github.com/facebook/rocksdb/ but it seems to not allow queries by value, as my last requirmenet.

Tuning RocksDB well is a very very hard challenge, and one that I am happy to not do day to day anymore. RocksDB is very powerful but it comes with other very sharp edges. Compaction is one of those, and all answers are likely workload dependent.

If you are worried about write amplification then leveled compactions are sub-optimal. I would try the universal compaction.

- https://github.com/facebook/rocksdb/wiki/Universal-Compactio...

It's fairly challenging to write a KV database, and takes several years of development to get the balance right between performance and reliability and avoiding data loss. Maybe read through the documentation for RocksDB https://github.com/facebook/rocksdb/wiki/RocksDB-Overview and watch the video on why it was developed and that may give you an impression of what is involved.

LMDB is much more sain in the sense that it supports real ACID transactions instead of savepoints for RocksDB. The latter is heavy and consumes a lot more memory for a lot less read throughput. However, RocksDB has a much better parallel and concurrent write story, where you can merge entries with merge functions and therefore write from multiple CPUs.

https://github.com/facebook/rocksdb/issues?q=is%3Aissue+clic...

Here are some bugs in JeMalloc: