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When Git first came onto the scene in the mid 's, I was initially skeptical because of its horrible user interface. But once I learned it, I appreciated its speed and features - especially the ease at which you could create feature branches, merge, and even create commits offline which was a big deal in the era when Subversion was the dominant version control tool in open source and you needed to speak with a server in order to commit code. When I started working for Mozilla inI was exposed to the Mercurial version control, which then - and still today - hosts the canonical repository for Firefox.

I didn't like Mercurial initially. Actually, I despised it. I thought it was slow and its features lacking. And I frequently encountered repository corruption. I was hacking on hg-git so I could improve the performance of converting Mercurial repositories to Git repositories. I was trying to enable an unofficial Git mirror of the Firefox repository to synchronize faster so it would be more usable. The ulterior motive was to demonstrate that Git is a superior version control tool and that Firefox should switch its canonical version control tool from Mercurial to Git.

In what is a textbook definition of ironywhat happened instead was I actually learned how Mercurial worked, interacted with the Mercurial Community, realized that Mozilla's documentation and developer practices were It's an old post, but I summarized my conversion four and a half years ago.

This started a chain of events that somehow resulted in me contributing a ton of patches to Mercurial, taking stewardship of hg. I've been an advocate of Mercurial over the years. Some would probably say I'm a Mercurial fanboy.

I reject zopflipng binary system core trading systems developer characterization because fanboy has connotations that imply I'm ignorant of realities. I'm well aware of Mercurial's faults and weaknesses. I'm well aware of Mercurial's relative lack of popularity, I'm well aware that this lack of popularity almost certainly turns away contributors to Firefox and other Mozilla projects because people don't want to have to learn a new tool.

I'm well aware that there are changes underway to enable Git to scale zopflipng binary system core trading systems developer very large repositories and that these changes could threaten Mercurial's scalability advantages over Git, making choices to use Mercurial even harder to defend. As an aside, the party most responsible for pushing Git to adopt architectural changes to enable it to scale these days is Microsoft.

Could anyone have foreseen that?! I've achieved mastery in both Git and Mercurial. I know their internals and their command line interfaces extremely well. I understand the architecture and principles upon which both are built. I'm also exposed to some very experienced and knowledgeable people in the Mercurial Community. People zopflipng binary system core trading systems developer have been around version control for much, much longer than me zopflipng binary system core trading systems developer have knowledge of random version control tools you've probably never zopflipng binary system core trading systems developer of.

This knowledge and exposure allows me to make connections and see opportunities for version control that quite frankly most do not. In this post, I'll be talking about some high-level, high-impact problems with Git and possible solutions for them.

My primary goal of this post is to foster positive change in Git and the services around it. While I personally prefer Mercurial, improving Git is good for everyone. Put another way, I want my knowledge and perspective from being part of a version control community to be put to good wherever it can. Speaking of Mercurial, as I said, I'm a heavy contributor and am somewhat influential in the Mercurial Community. I want to be clear that my opinions in this post are my own and I'm not speaking on behalf of the Mercurial Project or the larger Mercurial Community.

I also don't intend to claim that Mercurial is holier-than-thou. Mercurial has tons of user interface failings and deficiencies. And I'll even admit to being frustrated that some systemic failings in Mercurial have gone unaddressed for as long as they have.

But that's for another post. This post is about Git. Most people see version control as an obstacle standing in the way of accomplishing some other task. They just want to save their progress towards some goal. In other words, they want version control to be a save file feature in their workflow. Unfortunately, modern version control tools don't work that way. For starters, they require people to specify a commit message every time they save.

This zopflipng binary system core trading systems developer of itself can be annoying. But we generally accept that as the price you pay for version control: So you must record it. Most people want the barrier to saving changes to be effortless. A commit message is already too annoying for many users! The Git staging area establishes a higher barrier to saving. Instead of just saving your changes, you must first stage your changes to be saved. If you requested save in your favorite GUI application, text editor, etc and it popped open a select the changes you would like to save dialogyou would rightly think just save all my changes already, dammit.

But this is exactly what Git does with its staging area! Git is saying I know all the changes you made: To the average user, this is infuriating because it works in contrast to how the save feature works in almost every other application. There is a counterargument to be zopflipng binary system core trading systems developer here. However, it isn't an appropriate default feature. The ability to pick which changes to save is a power-user feature. Most users just want to save all the changes all the time.

So that should be the default behavior. And the Git staging area should be an opt-in feature. If intrinsic workflow warts aren't enough, the Git staging area has a horrible user interface. It is often referred to as the cache for historical reasons. Cache of course means something to anyone who knows anything about computers or programming. And Git's use of cache doesn't at all align with that common definition. Yet the zopflipng binary system core trading systems developer terminology in Git persists.

You have to run commands like git diff --cached to examine the state of the staging area. But Git also refers to the staging area as the index. And this terminology also appears in Zopflipng binary system core trading systems developer commands! Let's see what git help glossary has to say In terms of end-user documentation, this is a train wreck. It tells the lay user absolutely nothing about what the index actually is.

Instead, it casually throws out references to stat information requires the user know what the stat function call and struct are and objects a Git term for a piece of data stored by Git. It even undermines its own credibility with that truth be told sentence. This definition is so bad that it would probably improve user understanding if it were deleted! Of course, git help index says No manual entry for gitindex. So there is literally no hope for you to get a concise, understandable definition of the index.

Instead, it is one of those concepts that you think you learn from interacting with it all the time. Oh, when I git add something it gets into this state where git commit will actually save it. Do zopflipng binary system core trading systems developer know the interaction between uncommitted changes in the staging area and working directory when you git rebase?

What about git checkout? What about the various git reset invocations? I have a confession: I can't remember all the edge cases either. To play it safe, I try to make sure all my outstanding changes are committed before I run something like git rebase because I know that will be safe. The Git staging area doesn't have to be this complicated. A re-branding away from index to staging area would go a long way.

Adding an alias from git diff --staged to git diff --cached and removing references to the cache from common user commands would make a lot of sense and reduce end-user confusion. Of course, the Git staging area doesn't really need to exist at all!

The staging area is essentially a soft commit. It performs the save progress role - the basic requirement of a version control tool. And in some aspects it is actually a better save progress implementation than a commit because it doesn't require you to type a commit message! Because the staging area is a soft commit, all workflows using it can be modeled as if it were a real commit and the staging area didn't exist at all!

Or if you wish zopflipng binary system core trading systems developer incrementally add new changes to an in-progress commit, you can run git commit --amend or git commit --amend --interactive or git commit --amend --all. If you actually understand the various modes of git resetyou can use those to uncommit. Of course, the user interface to performing these actions in Git today is a bit convoluted. But if the staging area didn't exist, new high-level commands like git amend and git uncommit could certainly be invented.

To the average user, the staging area is a complicated concept. I'm a power user. I understand its purpose and how to harness its power.

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I think I first heard about the Zstandard compression algorithm at a Mercurial developer sprint in At one end of a large table a few people were uttering expletives out of sheer excitement. At developer gatherings, that's the universal signal for something is awesome.

Long story short, a Facebook engineer shared a link to the RealTime Data Compression blog operated by Yann Collet then known as the author of LZ4 - a compression algorithm known for its insane speeds and people were completely nerding out over the excellent articles and the data within showing the beginnings of a new general purpose lossless compression algorithm named Zstandard. This being a Mercurial meeting, many of us were intrigued because zlib is used by Mercurial for various functionality including on-disk storage and compression over the wire protocol and zlib operations frequently appear as performance hot spots.

Before I continue, if you are interested in low-level performance and software optimization, I highly recommend perusing the RealTime Data Compression blog. There are some absolute nuggets of info in there. Anyway, over the months, the news about Zstandard zstd kept getting better and more promising. I was toying around with pre-release versions and was absolutely blown away by the performance and features.

I believed the hype. A few days later, I started the python-zstandard project to provide a fully-featured and Pythonic interface to the underlying zstd C API while not sacrificing safety or performance. The ulterior motive was to leverage those bindings in Mercurial so Zstandard could be a first class citizen in Mercurial, possibly replacing zlib as the default compression algorithm for all operations. Fast forward six months and I've achieved many of those goals.

It even exposes some primitives not in the C API, such as batch compression operations that leverage multiple threads and use minimal memory allocations to facilitate insanely fast execution. Expect a dedicated post on python-zstandard from me soon. When cloning from hg. And, work is ongoing for Mercurial to support Zstandard for on-disk storage, which should bring considerable performance wins over zlib for local operations. I've learned a lot working on python-zstandard and integrating Zstandard into Mercurial.

My primary takeaway is Zstandard is awesome. In this post, I'm going to extol the virtues of Zstandard and provide reasons why I think you should use it. This trade-off is usually made because data - either at rest in storage or in motion over a network or even through a machine via software and memory - is a limiting factor for performance.

At scale, better and more efficient compression can translate to substantial cost savings in infrastructure. It can also lead to improved application performance, translating to better end-user engagement, sales, productivity, etc.

This is why companies like Facebook Zstandard , Google brotli, snappy, zopfli , and Pied Piper middle-out invest in compression. Computers are completely different today than they were in The Pentium microprocessor debuted in For comparison, a modern NVMe M.

And of course CPU and network speeds have increased as well. We also have completely different instruction sets on CPUs for well-designed algorithms and software to take advantage of. What I'm trying to say is the market is ripe for DEFLATE and zlib to be dethroned by algorithms and software that take into account the realities of modern computers.

Zstandard initially piqued my attention by promising better-than-zlib compression and performance in both the compression and decompression directions.

But it isn't unique. Brotli achieves the same, for example. But what kept my attention was Zstandard's rich feature set, tuning abilities, and therefore versatility. Before I do, I need to throw in an obligatory disclaimer about data and numbers that I use. Benchmarks should not be trusted.

There are so many variables that can influence performance and benchmarks. And if you change power settings, does that reflect real-life usage? Reporting useful and accurate performance numbers for compression is hard because there are so many variables to care about. Since Mercurial is the driver for my work in Zstandard, the data and numbers I report in this post are mostly Mercurial data.

Specifically, I'll be referring to data in the mozilla-unified Firefox repository. This repository contains over , commits spanning almost 10 years. The Mercurial layer adds some binary structures to e. There are two Mercurial-specific pieces of data I will use. One is a Mercurial bundle. This is essentially a representation of all data in a repository. It stores a mix of raw, fulltext data and deltas on that data. The other piece of data is revlog chunks. This is a mix of fulltext and delta data for a specific item tracked in version control.

I frequently use the changelog corpus, which is the fulltext data describing changesets or commits to Firefox. The numbers quoted and used for charts in this post are available in a Google Sheet. All performance data was obtained on an iK running Ubuntu Memory used is DDR with a cycle time of 35 clocks. While I'm pretty positive about Zstandard, it isn't perfect. There are corpora for which Zstandard performs worse than other algorithms, even ones I compare it directly to in this post.

So, your mileage may vary. Please enlighten me with your counterexamples by leaving a comment. With that rather large disclaimer out of the way, let's talk about what makes Zstandard awesome.

Compression algorithms typically contain parameters to control how much work to do. You can choose to spend more CPU to hopefully achieve better compression or you can spend less CPU to sacrifice compression.

OK, fine, there are other factors like memory usage at play too. This is commonly exposed to end-users as a compression level. In reality there are often multiple parameters that can be tuned.

But I'll just use level as a stand-in to represent the concept. But even with adjustable compression levels, the performance of many compression algorithms and libraries tend to fall within a relatively narrow window. In other words, many compression algorithms focus on niche markets.

For example, LZ4 is super fast but doesn't yield great compression ratios. LZMA yields terrific compression ratios but is extremely slow.

This can be visualized in the following chart showing results when compressing a mozilla-unified Mercurial bundle:. This chart plots the logarithmic compression speed in megabytes per second against achieved compression ratio.

The further right a data point is, the better the compression and the smaller the output. The higher up a point is, the faster compression is. The ideal compression algorithm lives in the top right, which means it compresses well and is fast. But the powers of mathematics push compression algorithms away from the top right.

LZ4 is highly vertical, which means its compression ratios are limited in variance but it is extremely flexible in speed. So for this data, you might as well stick to a lower compression level because higher values don't buy you much.

Bzip2 is the opposite: That means it is consistently the same speed while yielding different compression ratios. In other words, you might as well crank bzip2 up to maximum compression because it doesn't have a significant adverse impact on speed. LZMA and zlib are more interesting because they exhibit more variance in both the compression ratio and speed dimensions.

But let's be frank, they are still pretty narrow. This small window of flexibility means that you often have to choose a compression algorithm based on the speed versus size trade-off you are willing to make at that time.

That choice often gets baked into software. And as time passes and your software or data gains popularity, changing the software to swap in or support a new compression algorithm becomes harder because of the cost and disruption it will cause.

What we really want is a single compression algorithm that occupies lots of space in both dimensions of our chart - a curve that has high variance in both compression speed and ratio. Such an algorithm would allow you to make an easy decision choosing a compression algorithm without locking you into a narrow behavior profile.

It would allow you make a completely different size versus speed trade-off in the future by only adjusting a config knob or two in your application - no swapping of compression algorithms needed! As you can guess, Zstandard fulfills this role. This can clearly be seen in the following chart which also adds brotli for comparison. The advantages of Zstandard and brotli are obvious. That fastest speed is only 2x slower than LZ4 level 1. It's worth noting that zstd's C API exposes several knobs for tweaking the compression algorithm.

Each compression level maps to a pre-defined set of values for these knobs. It is possible to set these values beyond the ranges exposed by the default compression levels 1 through I've done some basic experimentation with this and have made compression even faster while sacrificing ratio, of course. This covers the gap between Zstandard and brotli on this end of the tuning curve. The wide span of compression speeds and ratios is a game changer for compression. Unless you have special requirements such as lightning fast operations which LZ4 can provide or special corpora that Zstandard can't handle well, Zstandard is a very safe and flexible choice for general purpose compression.

The output from this API is compatible with the Zstandard frame format and doesn't require any special handling on the decompression side.