158 lines
8.4 KiB
Markdown
158 lines
8.4 KiB
Markdown
---
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layout: post
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title: "Binary Format Shootout"
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description: "Making sense of binary streams"
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category:
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tags: [rust]
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---
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I've found that in many personal projects, [analysis paralysis](https://en.wikipedia.org/wiki/Analysis_paralysis)
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is particularly deadly. There's nothing like having other options available to make you question your decisions.
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There's a particular scenario that scares me: I'm a couple months into a project, only to realize that if I had
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made a different choice at an earlier juncture, weeks of work could have been saved. If only an extra hour or
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two of research had been conducted, everything would've turned out differently.
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Let's say you're in need of a binary serialization schema for a project you're working on. Data will be going
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over the network, not just in memory, so having a schema document is a must. Performance is important;
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there's no reason to use Protocol Buffers when other projects support similar features at faster speed.
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And it must be polyglot; Rust support needs to be there, but we can't predict what other languages this will
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interact with.
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Given these requirements, the formats I could find were:
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1. [Cap'n Proto](https://capnproto.org/) has been around the longest, and integrates well with all the build tools
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2. [Flatbuffers](https://google.github.io/flatbuffers/) is the newest, and claims to have a simpler encoding
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3. [Simple Binary Encoding](https://github.com/real-logic/simple-binary-encoding) is being adopted by the
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[High-performance financial](https://www.fixtrading.org/standards/sbe/) community, but the Rust implementation
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is essentially unmaintained
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Any one of these will satisfy the project requirements: easy to transmit over a network, reasonably fast,
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and support multiple languages. But actually picking one to build a system on is intimidating; it's impossible
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to know what issues that choice will lead to.
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Still, a choice must be made. It's not particularly groundbreaking, but I decided to build a test system to help
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understand how they all behave.
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# Prologue: Reading the Data
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Our benchmark will be a simple market data processor; given messages from [IEX](https://iextrading.com/trading/market-data/#deep),
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serialize each message into the schema format, then read back each message to do some basic aggregation.
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But before we make it to that point, we have to read in the market data. To do so, I'm using a library
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called [`nom`](https://github.com/Geal/nom). Version 5.0 was recently released and brought some big changes,
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so this was an opportunity to build a non-trivial program and see how it fared.
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If you're not familiar with `nom`, the idea is to build a binary data parser by combining different
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mini-parsers. For example, if your data looks like
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[this](https://www.winpcap.org/ntar/draft/PCAP-DumpFileFormat.html#rfc.section.3.3):
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```
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0 1 2 3
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0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1
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+---------------------------------------------------------------+
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0 | Block Type = 0x00000006 |
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+---------------------------------------------------------------+
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4 | Block Total Length |
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+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
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8 | Interface ID |
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+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
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12 | Timestamp (High) |
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+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
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16 | Timestamp (Low) |
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+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
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20 | Captured Len |
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+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
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24 | Packet Len |
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+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
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| Packet Data |
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| ... |
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```
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...you can build a parser in `nom` like
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[this](https://github.com/bspeice/speice.io-md_shootout/blob/369613843d39cfdc728e1003123bf87f79422497/src/parsers.rs#L59-L93):
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```rust
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const ENHANCED_PACKET: [u8; 4] = [0x06, 0x00, 0x00, 0x00];
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pub fn enhanced_packet_block(input: &[u8]) -> IResult<&[u8], &[u8]> {
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let (
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remaining,
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(
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block_type,
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block_len,
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interface_id,
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timestamp_high,
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timestamp_low,
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captured_len,
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packet_len,
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),
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) = tuple((
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tag(ENHANCED_PACKET),
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le_u32,
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le_u32,
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le_u32,
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le_u32,
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le_u32,
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le_u32,
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))(input)?;
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let (remaining, packet_data) = take(captured_len)(remaining)?;
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Ok((remaining, packet_data))
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}
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```
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This demonstration isn't too interesting, but when more complex formats need to be parsed (like IEX market data),
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[`nom` really shines](https://github.com/bspeice/speice.io-md_shootout/blob/369613843d39cfdc728e1003123bf87f79422497/src/iex.rs).
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Ultimately, because `nom` was used to parse the IEX-format market data before serialization, we're not too interested
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in its performance. However, it's worth mentioning how much easier this project was because I didn't have to write
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all the boring code by hand.
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# Part 1: Cap'n Proto
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Now it's time to get into the meaty part of the story. Cap'n Proto was the first format I tried because of how long
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it has supported Rust. It was a bit tricky to get the compiler installed, but once that was done, the
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[schema document](https://github.com/bspeice/speice.io-md_shootout/blob/369613843d39cfdc728e1003123bf87f79422497/marketdata.capnp)
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wasn't hard to create.
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In practice, I had a ton of issues with Cap'n Proto.
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To serialize new messages, Cap'n Proto uses a "builder" object. This builder allocates memory on the heap to hold the message
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content, but because builders [can't be re-used](https://github.com/capnproto/capnproto-rust/issues/111), we have to allocate
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a new buffer for every single message. I was able to work around this and re-use memory with a
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[special builder](https://github.com/bspeice/speice.io-md_shootout/blob/369613843d39cfdc728e1003123bf87f79422497/src/capnp_runner.rs#L17-L51),
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but it required reading through Cap'n Proto's [benchmarks](https://github.com/capnproto/capnproto-rust/blob/master/benchmark/benchmark.rs#L124-L156)
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to find an example usage and using `transmute` to bypass Rust's borrow checker.
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Reading messages was similarly problematic. Cap'n Proto has two message encodings: a ["packed"](https://capnproto.org/encoding.html#packing)
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version, and an unpacked version. When reading "packed" messages, we need to unpack the message before we can make use of it.
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This allocates a new buffer for each message, and I wasn't able to find a way to get around this. Unpacked messages, however,
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shouldn't require any allocation or decoding steps. In practice, because of a
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[bounds check](https://github.com/capnproto/capnproto-rust/blob/master/capnp/src/serialize.rs#L60) on the payload size,
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I had to [copy parts](https://github.com/bspeice/speice.io-md_shootout/blob/369613843d39cfdc728e1003123bf87f79422497/src/capnp_runner.rs#L255-L340)
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of the Cap'n Proto API to read messages without allocation.
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In the end, I put in significant work to make Cap'n Proto as fast as possible, but there were too many issues for me to feel
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comfortable making use of Cap'n Proto.
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# Final Results
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NOTE: Need to expand on this, but numbers reported below are from the IEX's 2019-09-03 data, took average over 10 runs.
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Serialization
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| | median | 99th Pctl | 99.9th Pctl | Total |
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|----------------------|--------|-----------|-------------|--------|
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| Cap'n Proto Packed | 413ns | 1751ns | 2943ns | 14.80s |
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| Cap'n Proto Unpacked | 273ns | 1828ns | 2836ns | 10.65s |
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| Flatbuffers | 355ns | 2185ns | 3497ns | 14.31s |
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| SBE | 91ns | 1535ns | 2423ns | 3.91s |
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Deserialization
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| | median | 99th Pctl | 99.9th Pctl | Total |
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|----------------------|--------|-----------|-------------|--------|
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| Cap'n Proto Packed | 539ns | 1216ns | 2599ns | 18.92s |
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| Cap'n Proto Unpacked | 366ns | 737ns | 1583ns | 12.32s |
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| Flatbuffers | 173ns | 421ns | 1007ns | 6.00s |
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| SBE | 116ns | 286ns | 659ns | 4.05s |
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