Guava VS Folly

The first problem is at the level of Type System, given that a situation more correct would allow us to distinguish through the Collection Type which abstraction we are operating with, species if definable as mutable or immutable. The JCF was born at a time when great care was taken to offer immediate operational data structures, and with attention to performance, but with less attention to constructs or uses that are now seen as common. These concepts have been taken up by other infrastructures from which we certainly cannot fail to mention: Eclipse Collection, Guava Collections, and VAVR.

Even better is getting Gradle/Maven to correctly pull "plain" vs "Android" versions of the package instead of them just publishing the diverging code base as two repository packages.

https://github.com/google/guava/issues/2914

I'll admit I'm surprised to see that BOMs have been documented on maven.apache.org since mid-2008. It looks like Spring, for example, didn't adopt them until mid-2014. I don't know how widely they caught on in other areas. The first discussion of them in the context of Guava may have been in 2018, as I don't see mention of them in the various issues from 2011-2015 (#605, #1329, #1471, #1954.

And a quick peek at the source code for ImmutableList seems to confirm this (https://github.com/google/guava/blob/master/guava/src/com/google/common/collect/ImmutableList.java - it goes via a bunch of methods, but ends up using Arrays.copyOf(), which creates a fixed-size array).

The guava library of Java has some of these data structures implemented: https://github.com/google/guava/wiki/ImmutableCollectionsExplained , but implementations of the above book in many languages can be found on github (say, this one for Haskell: https://github.com/aistrate/Okasaki )

Java Mask: Java Mask is a library that offers various string masking techniques for sensitive data such as credit card numbers, email addresses, and more. You can find the library at: https://github.com/miguelfreitas93/java-mask DataMasker: DataMasker is a Java library specifically designed for masking sensitive data, including credit card numbers, using customizable masking patterns. Visit the GitHub repository for more information and usage examples: https://github.com/GDSSecurity/DataMasker Maskify: Maskify is a simple Java library that can be used to mask credit card numbers, Social Security numbers, and other sensitive information. You can find the library at: https://github.com/jonathancarvalhoalves/maskify CreditCardUtils: This is a lightweight Java library that provides utility methods for validating, formatting, and masking credit card numbers. Visit the GitHub repository for more information: https://github.com/malkusch/creditcardutils Google Guava: Google Guava is a popular set of Java libraries containing a wealth of utilities for working with strings, collections, and more. While not specifically designed for masking credit card information, you can use Guava's string manipulation methods to mask sensitive data: https://github.com/google/guava

I mean, I guess, technically? If you define it like that, then Microsoft has people working for them for free, as does Google, as does Apple, etc. It's not that weird, and you can try to twist it to be weird, but those of us in the software industry largely regard this as a good thing.

So we have https://github.com/google/guava/issues/4011

Ok, so let's implement our lazy initialization more smartly to avoid acquiring the lock every time and use old fashion but still working double-checked locking. I've found it implemented by Suppliers.memoize in guava library.

https://github.com/facebook/folly/commit/b1391e1c57be71c1e2a...

https://github.com/facebook/folly/pull/2153

To set a HP on Linux, Folly just does a relaxed load of the src pointer, release store of the HP, compiler-only barrier, and acquire load. (This prevents the compiler from reordering the 2nd load before the store, right? But to my understanding does not prevent a hypothetical CPU reordering of the 2nd load before the store, which seems potentially problematic!)

Then on the GC/reclaim side of things, after protected object pointers are stored, it does a more expensive barrier[0] before acquire-loading the HPs.

I'll admit, I am not confident I understand why this works. I mean, even on x86, loads can be reordered before earlier program-order stores. So it seems like the 2nd check on the protection side could be ineffective. (The non-Linux portable version just uses an atomic_thread_fence SeqCst on both sides, which seems more obviously correct.) And if they don't need the 2nd load on Linux, I'm unclear on why they do it.

[0]: https://github.com/facebook/folly/blob/main/folly/synchroniz...

(This uses either mprotect to force a TLB flush in process-relevant CPUs, or the newer Linux membarrier syscall if available.)

folly provides functions to resize std::string & std::vector without initialization [0].

[0] https://github.com/facebook/folly/blob/3c8829785e3ce86cb821c...

My implementation was quite similar to Boost's spsc_queue and Facebook's folly/ProducerConsumerQueue.h.

> How is that relevant?

Roaring bitmaps and similar data structures get their speed from decoding together consecutive groups of elements, so if you do sequential decoding or decode a large fraction of the list you get excellent performance.

EF instead excels at random skipping, so if you visit a small fraction of the list you generally get better performance. This is why it works so well for inverted indexes, as generally the queries are very selective (otherwise why do you need an index?) and if you have good intersection algorithms you can skip a large fraction of documents.

I didn't follow the rest of your comment, select is what EF is good at, every other data structure needs a lot more scanning once you land on the right chunk. With BMI2 you can also use the PDEP instruction to accelerate the final select on a 64-bit block: https://github.com/facebook/folly/blob/main/folly/experiment...

C++ with folly's SCOPE_EXIT {} construct:

https://github.com/facebook/folly/blob/main/folly/ScopeGuard...

Seems like github issues taking a long time to get any response: https://github.com/facebook/folly

Can't speak for abseil and tbb, but in folly there are a few solutions for the common problem of sharing state between a writer that updates it very infrequently and concurrent readers that read it very frequently (typical use case is configs).

The most performant solutions are RCU (https://github.com/facebook/folly/blob/main/folly/synchroniz...) and hazard pointers (https://github.com/facebook/folly/blob/main/folly/synchroniz...), but they're not quite as easy to use as a shared_ptr [1].

Then there is simil-shared_ptr implemented with thread-local counters (https://github.com/facebook/folly/blob/main/folly/experiment...).

If you absolutely need a std::shared_ptr (which can be the case if you're working with pre-existing interfaces) there is CoreCachedSharedPtr (https://github.com/facebook/folly/blob/main/folly/concurrenc...), which uses an aliasing trick to transparently maintain per-core reference counts, and scales linearly, but it works only when acquiring the shared_ptr, any subsequent copies of that would still cause contention if passed around in threads.

[1] Google has a proposal to make a smart pointer based on RCU/hazptr, but I'm not a fan of it because generally RCU/hazptr guards need to be released in the same thread that acquired them, and hiding them in a freely movable object looks like a recipe for disaster to me, especially if paired with coroutines https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2020/p05...

Not sure if it's still the case but about 6 years ago Facebook's folly C++ library was something I'd point to for my junior engineers to get a sense of "good" C++ https://github.com/facebook/folly