FlatBuffers VS vast

I don't work at Cloudflare but follow their work and occasionally work on performance sensitive projects.

If I had to guess, they looked at the landscape a bit like I do and regarded Cap'n Proto, flatbuffers, SBE, etc. as being in one category apart from other data formats like Avro, protobuf, and the like.

So once you're committed to record'ish shaped (rather than columnar like Parquet) data that has an upfront parse time of zero (nominally, there could be marshalling if you transmogrify the field values on read), the list gets pretty short.

https://capnproto.org/news/2014-06-17-capnproto-flatbuffers-... goes into some of the trade-offs here.

Cap'n Proto was originally made for https://sandstorm.io/. That work (which Kenton has presumably done at Cloudflare since he's been employed there) eventually turned into Cloudflare workers.

Another consideration: https://github.com/google/flatbuffers/issues/2#issuecomment-...

Much more in the discussion of this particular issue onGitHub: flatbuffers:Reverse engineering #4258

Related but not Rust-specific: FlatBuffers, Cap'n Proto.

If json files are a concern because of space, you can always look into something like protobuffers or flatbuffers. But whatever you use, you should try to find a solution where you don't have to think about the actual serialization/deserialization of your objects, and can just concentrate on the data.

Or, as an alternative to protobuffers, there's also flatbuffers, which is lighter weight and needs less memory: https://google.github.io/flatbuffers/

As the title suggests, I am considering using Flatbuffers as a way to parse sensor data that has been stored in local datafiles. The project language is python.

Most languages target C or LLVM, and C and LLVM have a fundamentally lossy compilation processes.

To get around this, you'd need a hodge podge of pre compiler directives, or take a completely different approach.

I found a cool project that uses a "Tower of IRs" that can restablish source to binary provenance, which, seems to me, to be on the right track:

https://github.com/trailofbits/vast

I'd definitely like to see the compilation processes be more transparent and easy to work with.

At Trail of Bits, we are creating a new compiler front/middle end for Clang called VAST [1]. It consumes Clang ASTs and creates a high-level, information-rich MLIR dialect. Then, we progressively lower it through various other dialects, eventually down to the LLVM dialect in MLIR, which can be translated directly to MLIR.

Our goals with this pipeline are to enable static analyses that can choose the right abstraction level(s) for their goals, and using provenance, cross abstraction levels to relate results back to source code.

Neither Clang ASTs nor LLVM IR alone meet our needs for static analysis. Clang ASTs are too verbose and lack explicit representations for implicit behaviours in C++. LLVM IR isn't really "one IR," it's a two IRs (LLVM proper, and metadata), where LLVM proper is an unspecified family of dialects (-O0, -O1, -O2, -O3, then all the arch-specific stuff). LLVM IR also isn't easy to relate to source, even in the presence of maximal debug information. The Clang codegen process does ABI-specific lowering takes high-level types/values and transforms them to be more amenable to storing in target-cpu locations (e.g. registers). This actively works against relating information across levels; something that we want to solve with intermediate MLIR dialects.

Beyond our static analysis goals, I think an MLIR-based setup will be a key enabler of library-aware compiler optimizations. Right now, library-aware optimizations are challenging because Clang ASTs are hard to mutate, and by the time things are in LLVM IR, the abstraction boundaries provided by libraries are broken down by optimizations (e.g. inlining, specialization, folding), forcing optimization passes to reckon with the mechanics of how libraries are implemented.

We're very excited about MLIR, and we're pushing full steam ahead with VAST. MLIR is a technology that we can use to fix a lot of issues in Clang/LLVM that hinder really good static analysis.

[1] https://github.com/trailofbits/vast