Gomr

Map-reduce framework based on https://tip.golang.org/pkg/plugin/. It allows to submit job with your own implementation of Map-Reduce. The compilation of Map-Reduce implementation is done before the job submission and then compiled plugin is transferred to the workers where its load and run against the input files described in the job.

Requirements

• Go in version 1.8 or above
• gRPC - go get google.golang.org/grpc

Architecture

Components

Gomr - client

• Is responsible for submitting job to the gomr cluster
• Connects to the Consul to get the address of master service
• Tracks the progress of computation
• Job submit blocks the invocation

Gomr - master

• Connects to the Consul to get the address of all worker services
• Watches for new workers or removes dead ones
• Prepares files for the map phase
• Merges files after the reduce phase
• Reruns the failed tasks
• Gets the current status of work and pass it to the client

Gomr - worker

• Loads plugin implementation
• Sends status of work to master
• Computes map and reduce phase
• Prepares intermediate files for reduce phase - partitioning

Gomr limitations

• No distributed filesystem
• Due to no DFS everything is run on the same machine
• Split phase loads everything into memory
• Partitioning phase loads everything into memory
• Merge phase loads everything into memory

Example of Map-Reduce implementation

package main

import (
	"fmt"
	"github.com/mateuszdyminski/gomr/mapreduce"
	"strconv"
	"strings"
	"unicode"
)

func main() {}

// MrImpl implements the gomr MapReduce interface.
type MrImpl struct{}

// Map analyzes the each line of the input file and returns the number of occurrences of word.
func (mr MrImpl) Map(key, value string) (result []mapreduce.KeyValue) {
	isNotLetter := func(r rune) bool { return !unicode.IsLetter(r) }
	words := strings.FieldsFunc(value, isNotLetter)

	result = make([]mapreduce.KeyValue, 0, len(words))
	for _, w := range words {
		result = append(result, mapreduce.KeyValue{Key: strings.ToLower(w), Value: strconv.Itoa(1)})
	}
	return
}

// Reduce calculates the number of particular word(key).
func (mr MrImpl) Reduce(key string, values []string) string {
	counter := 0
	for _, v := range values {
		val, err := strconv.Atoi(v)
		if err != nil {
			continue
		}
		counter += val
	}

	return fmt.Sprintf("%d", counter)
}

// Impl exports the implementation of MapReduce to be available for plugin.Lookup.
var Impl mapreduce.MapReduce = MrImpl{}

Example of job submission

package main

import (
	"flag"
	"log"

	"github.com/mateuszdyminski/gomr/api"
)

var (
	mrImplDir     = flag.String("mrImplDir", "implementation", "A directory with the implementation of MapReduce interface")
	consulAddress = flag.String("consulAddress", "localhost:8500", "Address of Consul")
)

func main() {
	flag.Parse()

	job := api.Job{
		Name:           "WordCount",
		Input:          "/Users/md/workspace/go/src/github.com/mateuszdyminski/gomr/data/chapter1",
		MapTasksNum:    5,
		ReduceTasksNum: 1,
		MrImplDir:      *mrImplDir,
		GoBinPath:      "/Users/md/workspace/gosrc/go/bin/go",
	}

	client, err := api.NewMrClient(*consulAddress)
	if err != nil {
		log.Fatal(err)
	}

	log.Printf("submitting job %s!\n", job.Name)

	summary, err := client.Submit(job)
	if err != nil {
		log.Fatal(err)
	}

	log.Printf("status: %+v \n", summary.Status)
	log.Printf("result: %+v \n", summary.Result)
	log.Printf("duration: %+v \n", summary.Duration)
}

How to run gomr cluster

Install Consul on Mac

./dev.sh consul-install-mac

or Linux

./dev.sh consul-install-linux

Run Consul

./dev.sh consul-run

Run Master - in new terminal

./dev.sh master-run

Run some workers - each in new terminal

./dev.sh worker-run ID

where ID is 1,2,3,4...N where N is less than 10

How to submit word-count job

./dev.sh wordcount-run

Results should be in 'results/WordCount//mrtmp.WordCount'

Inspirations

• Go-Plugins
• MIT distributed systems course
• Glow project
• Glow Advent article especially last paragraph:

'Glow has limitations that Go code can not be sent and executed remotely.'