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dataset_splitter.go
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dataset_splitter.go
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package elasticthought
import (
"archive/tar"
"compress/gzip"
"fmt"
"io"
"net/http"
"path"
"strings"
"sync"
"github.com/couchbaselabs/logg"
)
// Worker job that splits a dataset into training/test set
type DatasetSplitter struct {
Configuration Configuration
Dataset Dataset
}
// Run this job
func (d DatasetSplitter) Run(wg *sync.WaitGroup) {
defer wg.Done()
dataset := &d.Dataset
updatedState, err := dataset.UpdateProcessingState(Processing)
if err != nil {
d.recordProcessingError(err)
return
}
if !updatedState {
logg.LogTo("TRAINING_JOB", "%+v already processed. Ignoring.", d)
return
}
switch d.Dataset.isSplittable() {
case true:
d.SplitDatafile()
default:
d.DownloadDatafiles()
}
}
func (d DatasetSplitter) SplitDatafile() {
// Find the datafile object associated with dataset
db := d.Configuration.DbConnection()
datafile, err := d.Dataset.GetSplittableDatafile(db)
if err != nil {
errMsg := fmt.Errorf("Error looking up datafile: %+v. Error: %v", d.Dataset, err)
d.recordProcessingError(errMsg)
return
}
// Open the url -- content type should be application/x-gzip
tr, err := openTarGzStream(datafile.Url)
if err != nil {
errMsg := fmt.Errorf("Error opening tar.gz streams: %v", err)
d.recordProcessingError(errMsg)
return
}
// Create pipes
prTrain, pwTrain := io.Pipe()
prTest, pwTest := io.Pipe()
// Wrap in gzip writers
pwGzTest := gzip.NewWriter(pwTest)
pwGzTrain := gzip.NewWriter(pwTrain)
// Create tar writers on the write end of the pipes
tarWriterTesting := tar.NewWriter(pwGzTest)
tarWriterTraining := tar.NewWriter(pwGzTrain)
// Create a cbfs client
cbfs, err := NewBlobStore(d.Configuration.CbfsUrl)
options := BlobPutOptions{}
options.ContentType = "application/x-gzip"
if err != nil {
errMsg := fmt.Errorf("Error creating cbfs client: %v", err)
d.recordProcessingError(errMsg)
return
}
// Figure out where to store these on cbfs
destTraining := d.Dataset.TrainingArtifactPath()
destTesting := d.Dataset.TestingArtifactPath()
// Spawn a goroutine that will read from tar.gz reader coming from url data
// and write to the training and test tar writers (which are on write ends of pipe)
transformDoneChan := make(chan error, 1)
go func() {
// Must close _underlying_ piped writers, or the piped readers will
// never get an EOF. Closing just the tar writers that wrap the underlying
// piped writers is not enough.
defer pwTest.Close()
defer pwTrain.Close()
defer pwGzTest.Close()
defer pwGzTrain.Close()
logg.LogTo("DATASET_SPLITTER", "Calling transform")
err = d.transform(tr, tarWriterTraining, tarWriterTesting)
if err != nil {
errMsg := fmt.Errorf("Error transforming tar stream: %v", err)
logg.LogError(errMsg)
transformDoneChan <- errMsg
return
}
transformDoneChan <- nil
}()
// Spawn goroutines to read off the read ends of the pipe and store in cbfs
cbfsTrainDoneChan := make(chan error, 1)
cbfsTestDoneChan := make(chan error, 1)
go func() {
if err := cbfs.Put("", destTesting, prTest, options); err != nil {
errMsg := fmt.Errorf("Error writing %v to cbfs: %v", destTesting, err)
logg.LogError(errMsg)
cbfsTestDoneChan <- errMsg
return
}
logg.LogTo("DATASET_SPLITTER", "Wrote %v to cbfs", destTesting)
cbfsTestDoneChan <- nil
}()
go func() {
if err := cbfs.Put("", destTraining, prTrain, options); err != nil {
errMsg := fmt.Errorf("Error writing %v to cbfs: %v", destTraining, err)
logg.LogError(errMsg)
cbfsTrainDoneChan <- errMsg
return
}
logg.LogTo("DATASET_SPLITTER", "Wrote %v to cbfs", destTraining)
cbfsTrainDoneChan <- nil
}()
// Wait for the results from all the goroutines
cbfsTrainResult := <-cbfsTrainDoneChan
cbfsTestResult := <-cbfsTestDoneChan
transformResult := <-transformDoneChan
// If any results had an error, log it and return
results := []error{transformResult, cbfsTestResult, cbfsTrainResult}
for _, result := range results {
if result != nil {
logg.LogTo("DATASET_SPLITTER", "Setting dataset to failed: %v", result)
d.Dataset.Failed(db, fmt.Errorf("%v", result))
return
}
}
// Update the state of the dataset to be finished
d.Dataset.FinishedSuccessfully(db)
if err := d.Dataset.FinishedSuccessfully(db); err != nil {
errMsg := fmt.Errorf("Error marking dataset %+v finished: %v", d, err)
d.recordProcessingError(errMsg)
return
}
}
func (d DatasetSplitter) DownloadDatafiles() {
// Create a cbfs client
cbfs, err := NewBlobStore(d.Configuration.CbfsUrl)
options := BlobPutOptions{}
options.ContentType = "application/x-gzip"
if err != nil {
errMsg := fmt.Errorf("Error creating cbfs client: %v", err)
d.recordProcessingError(errMsg)
return
}
db := d.Configuration.DbConnection()
source2destEntries := []struct {
Url string
DestPath string
}{
{
Url: d.Dataset.GetTrainingDatafileUrl(db),
DestPath: d.Dataset.TrainingArtifactPath(),
},
{
Url: d.Dataset.GetTestingDatafileUrl(db),
DestPath: d.Dataset.TestingArtifactPath(),
},
}
for _, source2destEntry := range source2destEntries {
// open tar.gz stream to source
// Open the url -- content type should be application/x-gzip
func() {
resp, err := http.Get(source2destEntry.Url)
if err != nil {
errMsg := fmt.Errorf("Error opening stream to: %v. Err %v", source2destEntry.Url, err)
d.recordProcessingError(errMsg)
return
}
defer resp.Body.Close()
if err := cbfs.Put("", source2destEntry.DestPath, resp.Body, options); err != nil {
errMsg := fmt.Errorf("Error writing %v to cbfs: %v", source2destEntry.DestPath, err)
d.recordProcessingError(errMsg)
return
}
logg.LogTo("DATASET_SPLITTER", "Wrote %v to cbfs", source2destEntry.DestPath)
}()
}
// Update the state of the dataset to be finished
if err := d.Dataset.FinishedSuccessfully(db); err != nil {
errMsg := fmt.Errorf("Error marking dataset %+v finished: %v", d, err)
d.recordProcessingError(errMsg)
return
}
}
// Codereview: de-dupe
func (d DatasetSplitter) recordProcessingError(err error) {
logg.LogError(err)
db := d.Configuration.DbConnection()
if err := d.Dataset.Failed(db, err); err != nil {
errMsg := fmt.Errorf("Error setting dataset as failed: %v", err)
logg.LogError(errMsg)
}
}
// Read from source tar stream and write training and test to given tar writers
func (d DatasetSplitter) transform(source *tar.Reader, train, test *tar.Writer) error {
splitter := d.splitter(train, test)
for {
hdr, err := source.Next()
if err == io.EOF {
// end of tar archive
break
}
if err != nil {
return err
}
tw := splitter(hdr.Name)
if err := tw.WriteHeader(hdr); err != nil {
return err
}
_, err = io.Copy(tw, source)
if err != nil {
return err
}
}
// close writers
if err := train.Close(); err != nil {
errMsg := fmt.Errorf("Error closing tar writer: %v", err)
logg.LogError(errMsg)
return err
}
if err := test.Close(); err != nil {
errMsg := fmt.Errorf("Error closing tar reader: %v", err)
logg.LogError(errMsg)
return err
}
return nil
}
func (d DatasetSplitter) splitter(train, test *tar.Writer) func(string) *tar.Writer {
trainingRatio := int(d.Dataset.TrainingDataset.SplitPercentage * 100)
testRatio := int(d.Dataset.TestDataset.SplitPercentage * 100)
ratio := [2]int{trainingRatio, testRatio}
dircounts := make(map[string][2]int)
return func(file string) *tar.Writer {
dir := path.Dir(file)
counts := dircounts[dir]
count0ratio1 := counts[0] * ratio[1]
count1ratio0 := counts[1] * ratio[0]
if count0ratio1 <= count1ratio0 {
counts[0]++
dircounts[dir] = counts
return train
} else {
counts[1]++
dircounts[dir] = counts
return test
}
}
}
// Validate that the source tar stream conforms to expected specs
func (d DatasetSplitter) validate(source *tar.Reader) (bool, error) {
// validation rules:
// 1. has at least 2 files
// 2. the depth of each file is 2 (folder/filename.xxx)
numFiles := 0
for {
hdr, err := source.Next()
if err == io.EOF {
// end of tar archive
break
}
if err != nil {
return false, err
}
numFiles += 1
pathComponents := strings.Split(hdr.Name, "/")
if len(pathComponents) != 2 {
return false, fmt.Errorf("Path does not have 2 components: %v", hdr.Name)
}
}
if numFiles < 2 {
return false, fmt.Errorf("Archive must contain at least 2 files")
}
return true, nil
}