logd

logd

high-performance log transport

overview

logd is a client-server application for storing and retrieving logs. Features include:

• simple, text-based protocol
• batched message delivery
• lookup messages by offset
• topics
• failed deliveries can be recovered
• configurable write guarantees
• high-performance

logd is pre-alpha. things generally work, but the interfaces are probably still going to change.

installation

go get github.com/jeffrom/logd

usage

server

logd

command-line client

log-cli can be used to read and write messages.

# you'll get back some offsets
jeff $ cat some_file | log-cli write
10240
10800
12223

# read from the beginning of the log
jeff $ log-cli read --limit 1

# read from an offset
jeff $ log-cli read --offset 10240

go client library

Writer can be used for sending messages, in batches, to the log.

// safe for concurrent calls
w := logd.NewWriter(conf, "mytopic").WithStateHandler(myhandler)
log.SetOutput(w)

Scanner can be used to read messages back from the log.

s, _ := logd.DialScanner("myserver:1774")
for s.Scan() {
    msg := s.Message()
    fmt.Println(msg)
}
if err := s.Error(); err != nil {
    panic(err)
}

design

logd is built for simplicity and usability. Batches come via the network, are validated, and then written without modification directly to partitions (represented as files) on disk. Topics are just directories which hold partitions. A text protocol is used and logd can be operated pretty easily using telnet if desired. The client library attempts to follow go conventions. For example, usage of logd.Scanner should be predictable to someone familiar with scanners in the go standard library. The server attempts to model itself closely to the OS such that tuning OS disk, network, and scheduling parameters can have significant benefits.

Clients write messages in batches and receive a response containing an offset in the log the batch was written to within a particular topic. This can be used later to efficiently read starting at that offset. Each topic is managed by a goroutine which controls synchronous access to the topic's partitions. There is another goroutine which handles non-blocking requests such as the CLOSE and STATS commands.

The client libraries consist of a socket client, which handles sending requests, receiving responses, and synchronous retries. Some higher-level libraries are built on top of this, Writer and Scanner: Writer collects messages, sending along batches to the server when the current batch reaches a certain size or a time interval is reached. Scanner reads messages back from the server. The client libraries attempt to provide strategies for common stream processing requirements, such as persisting log state so scanning can resume from a checkpoint after failures. Writer aggressively returns errors during failure, and failed batch deliveries can be accessed and retried. The lower-level client can be used to compose other abstractions, such as more lenient writers and parallel scanners. Callers can write their own state handlers which keep track of log offsets.

performance

The goal is for server to be able to persist all messages when the network interface is saturated, while clients can send and receive tens of thousands of reasonably-sized messages per second. The bottleneck for reads and writes should be kernel space, specifically network and disk IO, not the server itself. The kernel should be leveraged here to increase performance. For example, on OSes that support it, the sendfile system call is used when sending batches to client readers.

Other goals are to minimize hot-path memory allocations and copying of bytes.

Here are some benchmarks on a 12-core, 16gb memory linux machine, using a loopback device for networking:

pkg: github.com/jeffrom/logd/events
BenchmarkBatchFile-12                    1000000              3192 ns/op              70 B/op          1 allocs/op
BenchmarkLifecycle-12                      20000            131053 ns/op           90164 B/op        205 allocs/op
BenchmarkBatchFull-12                    1000000              2852 ns/op              88 B/op          6 allocs/op
BenchmarkBatchFullLarge-12                 20000            149112 ns/op            1086 B/op          8 allocs/op
BenchmarkBatchFullTopics8-12             1000000              3010 ns/op              82 B/op          6 allocs/op
BenchmarkReadHead-12                      200000             10275 ns/op            4398 B/op         25 allocs/op
BenchmarkReadTail-12                      200000             11437 ns/op            4716 B/op         25 allocs/op
BenchmarkReadAll-12                       200000             13197 ns/op            5512 B/op         29 allocs/op

jeff$ log-cli bench --conns 16 --topics 4 --duration 60s
batch size: 65500b, topics: 4, duration: 1m0s, connections: 16

bytes out :             50.56Gb                 863.53Mb/s
batches   :             828.61K                 13.82K/s
timing    :
        min 626.93μ
        p50 626.93μ
        p90 626.93μ
        p95 626.93μ
        p99 21.92ms
        max 1.25s

planned

• clean up API
• multi-language client libraries
• over-the-wire compression
• TLS
• more state handlers (postgres, mysql, redis)
• replication
• automatic failover