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Bradlee Speice
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@ -7,50 +7,49 @@ tags: [rust]
--- ---
I've found that in many personal projects, [analysis paralysis](https://en.wikipedia.org/wiki/Analysis_paralysis) I've found that in many personal projects, [analysis paralysis](https://en.wikipedia.org/wiki/Analysis_paralysis)
is particularly deadly. Making good decisions at the start avoids pain and suffering down the line; is particularly deadly. Making good decisions in the beginning avoids pain and suffering later;
if doing extra research avoids problems in the future, I'm happy to continue researching indefinitely. if extra research prevents future problems, I'm happy to continue researching indefinitely.
So let's say you're in need of a binary serialization schema for a project you're working on. Data will be going So let's say you're in need of a binary serialization schema. Data will be going over the network, not just in memory,
over the network, not just in memory, so having a schema document and code generation is a must. Performance is important; so having a schema document and code generation is a must. Performance is crucial; there's no reason to use Protocol Buffers
there's no reason to use Protocol Buffers when other projects support similar features at faster speed. when other formats support similar features at faster speeds. And the more languages supported, the better; I use Rust,
And it must be polyglot; Rust support is a minimum, but we can't predict what other languages this will but can't predict what other languages this will interact with.
interact with.
Given these requirements, the candidates I could find were: Given these requirements, the candidates I could find were:
1. [Cap'n Proto](https://capnproto.org/) has been around the longest, and integrates well with all the build tools 1. [Cap'n Proto](https://capnproto.org/) has been around the longest, and is the most established
2. [Flatbuffers](https://google.github.io/flatbuffers/) is the newest, and claims to have a simpler encoding 2. [Flatbuffers](https://google.github.io/flatbuffers/) is the newest, and claims to have a simpler encoding
3. [Simple Binary Encoding](https://github.com/real-logic/simple-binary-encoding) has the simplest encoding, 3. [Simple Binary Encoding](https://github.com/real-logic/simple-binary-encoding) has the simplest encoding,
but the Rust implementation is essentially unmaintained but the Rust implementation is [essentially unmaintained](https://users.rust-lang.org/t/zero-cost-abstraction-frontier-no-copy-low-allocation-ordered-decoding/11515/9)
Any one of these will satisfy the project requirements: easy to transmit over a network, reasonably fast, Any one of these will satisfy the project requirements: easy to transmit over a network, reasonably fast,
and support multiple languages. But how do you actually pick one? It's impossible to know what issues that and polyglot support. But how do you actually pick one? It's impossible to know what issues will follow that choice,
choice will lead to, so you avoid commitment until the last possible moment. so I tend to avoid commitment until the last possible moment.
Still, a choice must be made. Instead of worrying about which is "the best," I decided to build a small Still, a choice must be made. Instead of worrying about which is "the best," I decided to build a small
proof-of-concept system in each format and pit them against each other. All code can be found in the proof-of-concept system in each format and pit them against each other. All code can be found in the
[repository](https://github.com/bspeice/speice.io-md_shootout) for this project. [repository](https://github.com/bspeice/speice.io-md_shootout) for this post.
We'll discuss more in detail, but a quick preview of the results: We'll discuss more in detail, but a quick preview of the results:
- Cap'n Proto can theoretically perform incredibly well, but the implementation had performance issues - Cap'n Proto can theoretically perform incredibly well, but the implementation had performance issues
- Flatbuffers had poor serialization performance, but more than made up for it during deserialiation - Flatbuffers had some quirks, but largely lived up to its "zero-copy" promises
- SBE has the best median and worst-case performance, but the message structure doesn't support some - SBE has the best median and worst-case performance, but the message structure has a limited feature set
features that both Cap'n Proto and Flatbuffers do relative to Cap'n Proto and Flatbuffers
# Prologue: Reading the Data # Prologue: Reading the Data
Our benchmark system will be a simple market data processor; given messages from Our benchmark system will be a simple data processor; given depth-of-book market data from
[IEX](https://iextrading.com/trading/market-data/#deep), serialize each message into the schema format, [IEX](https://iextrading.com/trading/market-data/#deep), serialize each message into the schema format,
then read back the message to do some basic aggregation. This test isn't complex, but it is representative then read back the message for some basic aggregation. This test isn't complex, but is representative
of the project I need a binary format for. of the project I need a binary format for.
But before we make it to that point, we have to actually read in the market data. To do so, I'm using a library But before we make it to that point, we have to actually read in the market data. To do so, I'm using a library
called [`nom`](https://github.com/Geal/nom). Version 5.0 was recently released and brought some big changes, called [`nom`](https://github.com/Geal/nom). Version 5.0 was recently released and brought some big changes,
so this was an opportunity to build a non-trivial program and get familiar again. so this was an opportunity to build a non-trivial program and get familiar again.
If you don't already know about `nom`, it's a kind of "parser generator". By combining different If you don't already know about `nom`, it's a "parser generator". By combining different smaller parsers,
mini-parsers, you can parse more complex structures without writing all tedious code by hand. you can build a parser to handle more complex structures without writing all the tedious code by hand.
For example, when parsing [PCAP files](https://www.winpcap.org/ntar/draft/PCAP-DumpFileFormat.html#rfc.section.3.3): For example, when parsing [PCAP files](https://www.winpcap.org/ntar/draft/PCAP-DumpFileFormat.html#rfc.section.3.3):
``` ```
@ -107,40 +106,41 @@ pub fn enhanced_packet_block(input: &[u8]) -> IResult<&[u8], &[u8]> {
} }
``` ```
This example isn't too interesting, but when more complex formats need to be parsed (like IEX market data), While this example isn't too interesting, more complex formats (like IEX market data) are where
[`nom` really shines](https://github.com/bspeice/speice.io-md_shootout/blob/369613843d39cfdc728e1003123bf87f79422497/src/iex.rs). [`nom` really shines](https://github.com/bspeice/speice.io-md_shootout/blob/369613843d39cfdc728e1003123bf87f79422497/src/iex.rs).
Ultimately, because the `nom` code in this shootout was used for all formats, we're not too interested in its performance. Ultimately, because the `nom` code in this shootout was the same for all formats, we're not too interested in its performance.
Still, building the market data parser was actually fun because I didn't have to write all the boring code by hand. Still, it's worth mentioning that building the market data parser was actually fun; I didn't have to write all the boring code by hand.
# Part 1: Cap'n Proto # Part 1: Cap'n Proto
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 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
it has supported Rust (thanks to [David Renshaw](https://github.com/dwrensha) for maintaining the Rust port since it has supported Rust (thanks to [dwrensha](https://github.com/dwrensha) for maintaining the Rust port since
[2014!](https://github.com/capnproto/capnproto-rust/releases/tag/rustc-0.10)). However, I had a ton of performance concerns [2014!](https://github.com/capnproto/capnproto-rust/releases/tag/rustc-0.10)). However, I had a ton of performance concerns
actually using of Cap'n Proto. once I started using it.
To serialize new messages, Cap'n Proto uses a "builder" object. This builder allocates memory on the heap to hold the message To serialize new messages, Cap'n Proto uses a "builder" object. This builder allocates memory on the heap to hold the message
content, but because builders [can't be re-used](https://github.com/capnproto/capnproto-rust/issues/111), we have to allocate content, but because builders [can't be re-used](https://github.com/capnproto/capnproto-rust/issues/111), we have to allocate
a new buffer for every single message. I was able to work around this and re-use memory with a a new buffer for every single message. I was able to work around this with a
[special builder](https://github.com/bspeice/speice.io-md_shootout/blob/369613843d39cfdc728e1003123bf87f79422497/src/capnp_runner.rs#L17-L51), [special builder](https://github.com/bspeice/speice.io-md_shootout/blob/369613843d39cfdc728e1003123bf87f79422497/src/capnp_runner.rs#L17-L51)
but it required reading through Cap'n Proto's [benchmarks](https://github.com/capnproto/capnproto-rust/blob/master/benchmark/benchmark.rs#L124-L156) that could re-use the buffer, but it required reading through Cap'n Proto's
to find an example and using `transmute` to bypass Rust's borrow checker. [benchmarks](https://github.com/capnproto/capnproto-rust/blob/master/benchmark/benchmark.rs#L124-L156)
to find an example, and used [`std::mem::transmute`](https://doc.rust-lang.org/std/mem/fn.transmute.html) to bypass Rust's borrow checker.
The process of reading messages was better, but still had issues. Cap'n Proto has two message encodings: a ["packed"](https://capnproto.org/encoding.html#packing) The process of reading messages was better, but still had issues. Cap'n Proto has two message encodings: a ["packed"](https://capnproto.org/encoding.html#packing)
representation, and an "unpacked" version. When reading "packed" messages, we need a buffer to unpack the message into before we can use it; representation, and an "unpacked" version. When reading "packed" messages, we need a buffer to unpack the message into before we can use it;
Cap'n Proto allocates a new buffer for each message we unpack, and I wasn't able to figure out a way around that. Cap'n Proto allocates a new buffer for each message we unpack, and I wasn't able to figure out a way around that.
In contrast, the unpacked message format should be where Cap'n Proto shines; its main selling point is that there's [no decoding step](https://capnproto.org/). In contrast, the unpacked message format should be where Cap'n Proto shines; its main selling point is that there's [no decoding step](https://capnproto.org/).
However, accomplishing zero-copy deserialization required copying code from the private API ([since fixed](https://github.com/capnproto/capnproto-rust/issues/148)), However, accomplishing zero-copy deserialization required code in the private API ([since fixed](https://github.com/capnproto/capnproto-rust/issues/148)),
and we still allocate a vector on every read for the segment table. and we still allocate a vector on every read for the segment table.
In the end, I put in significant work to make Cap'n Proto as fast as possible in the tests, but there were too many issues 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 comfortable
for me to feel comfortable using it long-term. using it long-term.
# Part 2: Flatbuffers # Part 2: Flatbuffers
This is the new kid on the block. After a [first attempt](https://github.com/google/flatbuffers/pull/3894) didn't pan out, This is the new kid on the block. After a [first attempt](https://github.com/google/flatbuffers/pull/3894) didn't pan out,
official support was [recently added](https://github.com/google/flatbuffers/pull/4898). Flatbuffers is intended to address official support was [recently added](https://github.com/google/flatbuffers/pull/4898). Flatbuffers intends to address
the same problems as Cap'n Proto: high-performance, polyglot, binary messaging. The difference is that Flatbuffers claims the same problems as Cap'n Proto: high-performance, polyglot, binary messaging. The difference is that Flatbuffers claims
to have a simpler wire format and [more flexibility](https://google.github.io/flatbuffers/flatbuffers_benchmarks.html). to have a simpler wire format and [more flexibility](https://google.github.io/flatbuffers/flatbuffers_benchmarks.html).
@ -158,13 +158,13 @@ table MultiMessage {
} }
``` ```
We want to create a `MultiMessage` that contains a vector of `Message`, but each `Message` has a vector (the `string` type). We want to create a `MultiMessage` which contains a vector of `Message`, and each `Message` itself contains a vector (the `string` type).
I was able to work around this by [caching `Message` elements](https://github.com/bspeice/speice.io-md_shootout/blob/e9d07d148bf36a211a6f86802b313c4918377d1b/src/flatbuffers_runner.rs#L83) I was able to work around this by [caching `Message` elements](https://github.com/bspeice/speice.io-md_shootout/blob/e9d07d148bf36a211a6f86802b313c4918377d1b/src/flatbuffers_runner.rs#L83)
in a `SmallVec` before building the final `MultiMessage`, but it was a painful process. in a `SmallVec` before building the final `MultiMessage`, but it was a painful process.
Second, streaming support in Flatbuffers seems to be something of an [afterthought](https://github.com/google/flatbuffers/issues/3898). Second, streaming support in Flatbuffers seems to be something of an [afterthought](https://github.com/google/flatbuffers/issues/3898).
Where Cap'n Proto in Rust handles reading messages from a stream as part of the API, Flatbuffers just puts a `u32` at the front of each Where Cap'n Proto in Rust handles reading messages from a stream as part of the API, Flatbuffers just sticks a `u32` at the front of each
message to indicate the size. Not specifically a problem, but calculating message size without that size tag at the front is nigh on impossible. message to indicate the size. Not specifically a problem, but calculating message size without that tag is nigh on impossible.
Ultimately, I enjoyed using Flatbuffers, and had to do significantly less work to make it perform well. Ultimately, I enjoyed using Flatbuffers, and had to do significantly less work to make it perform well.
@ -177,32 +177,31 @@ high-performance systems, so it was encouraging to read about a format that
[directly addressed](https://github.com/real-logic/simple-binary-encoding/wiki/Why-Low-Latency) my concerns. SBE has by far [directly addressed](https://github.com/real-logic/simple-binary-encoding/wiki/Why-Low-Latency) my concerns. SBE has by far
the simplest binary format, but it does make some tradeoffs. the simplest binary format, but it does make some tradeoffs.
Both Cap'n Proto and Flatbuffers use [pointers in their messages](https://capnproto.org/encoding.html#structs) to handle Both Cap'n Proto and Flatbuffers use [message offsets](https://capnproto.org/encoding.html#structs) to handle
variable-length data, [unions](https://capnproto.org/language.html#unions), and various other features. In contrast, variable-length data, [unions](https://capnproto.org/language.html#unions), and various other features. In contrast,
messages in SBE are essentially [just structs](https://github.com/real-logic/simple-binary-encoding/blob/master/sbe-samples/src/main/resources/example-schema.xml); messages in SBE are essentially [just structs](https://github.com/real-logic/simple-binary-encoding/blob/master/sbe-samples/src/main/resources/example-schema.xml);
variable-length data is supported, but there's no union type. variable-length data is supported, but there's no union type.
As mentioned in the beginning, the Rust port of SBE works well, but is essentially unmaintained. However, if you As mentioned in the beginning, the Rust port of SBE works well, but is essentially unmaintained. However, if you
don't need union types, and can accept that schemas are XML documents, it's still worth using. The Rust SBE implementation don't need union types, and can accept that schemas are XML documents, it's still worth using. The implementation
had the best streaming support of any format I used, and doesn't trigger allocation during de/serialization. had the best streaming support of all formats being tested, and doesn't trigger allocation during de/serialization.
# Results # Results
After building a test harness [for](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/capnp_runner.rs) After building a test harness [for](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/capnp_runner.rs)
[each](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/flatbuffers_runner.rs) [each](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/flatbuffers_runner.rs)
[protocol](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/sbe_runner.rs), [format](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/sbe_runner.rs),
it was time to actually take them for a spin. I used it was time to actually take them for a spin. I used
[this script](https://github.com/bspeice/speice.io-md_shootout/blob/master/run_shootout.sh) to manage the test process, [this script](https://github.com/bspeice/speice.io-md_shootout/blob/master/run_shootout.sh) to manage the benchmarking,
and the raw results are [here](https://github.com/bspeice/speice.io-md_shootout/blob/master/shootout.csv). All data and the raw results are [here](https://github.com/bspeice/speice.io-md_shootout/blob/master/shootout.csv). All data
reported below is the average of 10 runs over a single day of IEX data. Data checks were implemented to make sure reported below is the average of 10 runs over a single day of IEX data. Results were validated to make sure
that each format achieved the same results. that each format parsed the data correctly.
## Serialization ## Serialization
Serialization measures on a This test measures, on a
[per-message basis](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/main.rs#L268-L272) [per-message basis](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/main.rs#L268-L272),
how long it takes to convert the pre-parsed IEX message into the desired format how long it takes to serialize the IEX message into the desired format and write to a pre-allocated buffer.
and write to a pre-allocated buffer.
| Schema | Median | 99th Pctl | 99.9th Pctl | Total | | Schema | Median | 99th Pctl | 99.9th Pctl | Total |
|:---------------------|:-------|:----------|:------------|:-------| |:---------------------|:-------|:----------|:------------|:-------|
@ -213,9 +212,9 @@ and write to a pre-allocated buffer.
## Deserialization ## Deserialization
Deserialization measures on a This test measures, on a
[per-message basis](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/main.rs#L294-L298) [per-message basis](https://github.com/bspeice/speice.io-md_shootout/blob/master/src/main.rs#L294-L298),
how long it takes to read the message encoded during deserialization and how long it takes to read the previously-serialized message and
perform some basic aggregation. The aggregation code is the same for each format, perform some basic aggregation. The aggregation code is the same for each format,
so any performance differences are due solely to the format implementation. so any performance differences are due solely to the format implementation.
@ -229,9 +228,9 @@ so any performance differences are due solely to the format implementation.
# Conclusion # Conclusion
Building a benchmark turned out to be incredibly helpful in making a decision; because a Building a benchmark turned out to be incredibly helpful in making a decision; because a
"union" type isn't important to me, I'll be using SBE for my personal projects. "union" type isn't important to me, I can be confident that SBE best addresses my needs.
While SBE was the fastest in terms of both median and worst-case performance, its worst case While SBE was the fastest in terms of both median and worst-case performance, its worst case
performance was proportionately far higher than any other format. It seems to be that deserialization performance was proportionately far higher than any other format. It seems to be that de/serialization
time scales with message size, but I'll need to do some more research to understand what exactly time scales with message size, but I'll need to do some more research to understand what exactly
is going on. is going on.