Implementing non re-entrant functions in Golang

A non re-entrant function is a function that could only be executing once at any point in time, regardless of how many times it is being invoked and by how many goroutines.

This post illustrates blocking non re-entrant functions and yielding non re-entrant functions implementations in golang.

A use case

A service is polling for some conditions, monitoring some statuses once per second. We want each status to be checked independently of others without blocking. An implementation might look like:

func main() {
    tick := time.Tick(time.Second)
    go func() {
        for range tick {
            go CheckSomeStatus()
            go CheckAnotherStatus()
        }
    }()
}

We choose to run each status check in its own goroutine so that CheckAnotherStatus() doesn’t wait upon CheckSomeStatus() to complete.

Each of these checks typically take a very short amount of time, and much less than a second. What happens, though, if CheckAnotherStatus() itself takes more than one second to run? Perhaps there’s an unexpected network or disk latency affecting the execution time of the check.

Does it make sense for the function to be executed twice at the same time? If not, we want it to be non re-entrant. Continue reading » “Implementing non re-entrant functions in Golang”

Observations on the hashicorp/raft library, and notes on RDBMS

The hashicorp/raft library is a Go library to provide consensus via Raft protocol implementation. It is the underlying library behind Hashicorp’s Consul.

I’ve had the opportunity to work with this library a couple projects, namely freno and orchestrator. Here are a few observations on working with this library:

  • TL;DR on Raft: a group communication protocol; multiple nodes communicate, elect a leader. A leader leads a consensus (any subgroup of more than half the nodes of the original group, or hopefully all of them). Nodes may leave and rejoin, and will remain consistent with consensus.
  • The hashicorp/raft library is an implementation of the Raft protocol. There are other implementations, and different implementations support different features.
  • The most basic premise is leader election. This is pretty straightforward to implement; you set up nodes to communicate to each other, and they elect a leader. You may query for the leader identity via Leader(), VerifyLeader(), or observing LeaderCh.
  • You have no control over the identity of the leader. You cannot “prefer” one node to be the leader. You cannot grab leadership from an elected leader, and you cannot demote a leader unless by killing it.
  • The next premise is gossip, sending messages between the raft nodes. With hashicorp/raft, only the leader may send messages to the group. This is done via the Apply() function.
  • Messages are nothing but blobs. Your app encodes the messages into []byte and ships it via raft. Receiving ends need to decode the bytes into a meaningful message.
  • You will check the result of Apply(), an ApplyFuture. The call to Error() will wait for consensus.
  • Just what is a message consensus? It’s a guarantee that the consensus of nodes has received and registered the message.
  • Messages form the raft log.
  • Messages are guaranteed to be handled in-order across all nodes.
  • The leader is satisfied when the followers receive the messages/log, but it cares not for their interpretation of the log.
  • The leader does not collect the output, or return value, of the followers applying of the log.
  • Consequently, your followers may not abort the message. They may not cast an opinion. They must adhere to the instruction received from the leader.
  • hashicorp/raft uses either an LMDB-based store or BoltDB for persisting your messages. Both are transactional stores.
  • Messages are expected to be idempotent: a node that, say, happens to restart, will request to join back the consensus (or to form a consensus with some other node). To do that, it will have to reapply historical messages that it may have applied in the past.
  • Number of messages (log entries) will grow infinitely. Snapshots are taken so as to truncate the log history. You will implement the snapshot dump & load.
  • A snapshot includes the log index up to which it covers.
  • Upon startup, your node will look for the most recent snapshot. It will read it, then resume replication from the aforementioned log index.
  • hashicorp/raft provides a file-system based snapshot implementation.

One of my use cases is completely satisfied with the existing implementations of BoltDB and of the filesystem snapshot.

However in another (orchestrator), my app stores its state in a relational backend. To that effect, I’ve modified the logstore and snapshot store. I’m using either MySQL or sqlite as backend stores for my app. How does that affect my raft use? Continue reading » “Observations on the hashicorp/raft library, and notes on RDBMS”

Forking Golang repositories on GitHub and managing the import path

Problem: there’s an awesome Golang project on GitHub which you want to fork. You want to develop & collaborate on that fork, but the golang import path, in your source code, still references the original path, breaking everything.

A couple solutions offered below. First, though, let’s get some names.

A sample case, the problem at hand

There’s an awesome tool on http://github.com/awsome-org/tool. You successfully fork it onto http://github.com/awesome-you/tool.

You want to collaborate on http://github.com/awesome-you/tool; you wish to pull, commit & push. Maybe you want to send pull requests to the origin.

The following is commonly found throughout .go files in the repository:

import (
    "github.com/awesome-org/tool/config"
    "github.com/awesome-org/tool/driver"
    "github.com/awesome-org/tool/net"
    "github.com/awesome-org/tool/util"
)

If you:

go get http://github.com/awesome-you/tool

golang creates your $GOPATH/src/github.com/awesome-you/tool/, which is awesome. However, as you resolve dependencies via

cd $GOPATH/src/github.com/awesome-you/tool/ ; go get ./...

golang digs into the source code, finds references to github.com/awesome-org/tool/configgithub.com/awesome-org/tool/driver etc, and fetches those from http://github.com/awsome-org/tool and onto $GOPATH/src/github.com/awesome-org/tool/, which is not awesome. You actually have two copies of the code, one from your fork, one from the origin, and your own fork will be largely ignored as it mostly points back to the origin.

A bad solution

The dirty, bad solution would be for you to go over the source code and replace “github.com/awesome-org/tool” entries with “github.com/awesome-you/tool”. It is bad for two reasons:

  • You will not be able to further pull changes from upstream
  • You will not be able to pull-request and push your own changes upstream

Continue reading » “Forking Golang repositories on GitHub and managing the import path”