mirror of
https://github.com/kubernetes-sigs/kustomize.git
synced 2026-06-29 09:40:49 +00:00
Crawler performance improvements, better structure
Refactored the crawler implementation to make the whole thing more testable. Added a document interface to make the crawler generic. This will be useful for collecting plugins, and other documents.
This commit is contained in:
@@ -16,7 +16,11 @@ import (
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"strings"
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"time"
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"sigs.k8s.io/kustomize/internal/tools/crawler"
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"sigs.k8s.io/kustomize/internal/tools/doc"
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"sigs.k8s.io/kustomize/internal/tools/httpclient"
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"sigs.k8s.io/kustomize/v3/pkg/git"
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"sigs.k8s.io/kustomize/v3/pkg/pgmconfig"
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)
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var logger = log.New(os.Stdout, "Github Crawler: ",
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@@ -34,6 +38,17 @@ type GitHubClient struct {
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client *http.Client
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}
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func NewClient(accessToken string, retryCount uint64, client *http.Client) GitHubClient {
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return GitHubClient{
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retryCount: retryCount,
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client: client,
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RequestConfig: RequestConfig{
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perPage: githubMaxPageSize,
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accessToken: accessToken,
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},
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}
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}
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func NewCrawler(accessToken string, retryCount uint64, client *http.Client,
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query Query) githubCrawler {
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@@ -52,7 +67,7 @@ func NewCrawler(accessToken string, retryCount uint64, client *http.Client,
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// Implements crawler.Crawler.
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func (gc githubCrawler) Crawl(
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ctx context.Context, output chan<- *doc.KustomizationDocument) error {
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ctx context.Context, output chan<- crawler.CrawlerDocument) error {
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noETagClient := GitHubClient{
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RequestConfig: gc.client.RequestConfig,
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@@ -80,13 +95,78 @@ func (gc githubCrawler) Crawl(
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}
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}
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return errs
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if len(errs) > 0 {
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return errs
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}
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return nil
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}
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func (gc githubCrawler) FetchDocument(ctx context.Context, d *doc.Document) error {
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repoURL := d.RepositoryURL + "/" + d.FilePath + "?ref=" + d.DefaultBranch
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repoSpec, err := git.NewRepoSpecFromUrl(repoURL)
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if err != nil {
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return fmt.Errorf("invalid repospec: %v", err)
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}
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url := "https://raw.githubusercontent.com/" + repoSpec.OrgRepo +
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"/" + repoSpec.Ref + "/" + repoSpec.Path
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handle := func(resp *http.Response, err error, path string) error {
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if err == nil && resp.StatusCode == http.StatusOK {
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d.IsSame = httpclient.FromCache(resp.Header)
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defer resp.Body.Close()
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data, err := ioutil.ReadAll(resp.Body)
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if err != nil {
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return err
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}
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d.DocumentData = string(data)
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d.FilePath = d.FilePath + path
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return nil
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}
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return err
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}
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resp, err := gc.client.GetRawUserContent(url)
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if err := handle(resp, err, ""); err == nil {
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return nil
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}
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for _, file := range pgmconfig.KustomizationFileNames {
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resp, err = gc.client.GetRawUserContent(url + "/" + file)
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err := handle(resp, err, "/"+file)
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if err != nil {
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continue
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}
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}
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return fmt.Errorf("File Not Found: %s", url)
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}
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func (gc githubCrawler) SetCreated(ctx context.Context, d *doc.Document) error {
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fs := GithubFileSpec{}
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fs.Repository.FullName = d.RepositoryURL + "/" + d.FilePath
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creationTime, err := gc.client.GetFileCreationTime(fs)
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if err != nil {
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return err
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}
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d.CreationTime = &creationTime
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return nil
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}
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func (gc githubCrawler) Match(d *doc.Document) bool {
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url := d.RepositoryURL + "/" + d.FilePath + "?ref=" + "/" +
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d.DefaultBranch
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repoSpec, err := git.NewRepoSpecFromUrl(url)
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if err != nil {
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return false
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}
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return strings.Contains(repoSpec.Host, "github.com")
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}
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// processQuery follows all of the pages in a query, and updates/adds the
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// documents from the crawl to the datastore/index.
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func processQuery(ctx context.Context, gcl GitHubClient, query string,
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output chan<- *doc.KustomizationDocument) error {
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output chan<- crawler.CrawlerDocument) error {
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queryPages := make(chan GithubResponseInfo)
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@@ -112,13 +192,6 @@ func processQuery(ctx context.Context, gcl GitHubClient, query string,
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}
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for _, file := range page.Parsed.Items {
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// TODO(damienr74) This is where we'd need to
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// communicate with redis. Currently always doing a full
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// reindex of the documents. Since the documents are in
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// sorted order in each bucket, we can short circuit the
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// search when we find a file that has been seen, or we
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// can choose to selectively update files.
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k, err := kustomizationResultAdapter(gcl, file)
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if err != nil {
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errs = append(errs, err)
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@@ -137,23 +210,33 @@ func processQuery(ctx context.Context, gcl GitHubClient, query string,
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}
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func kustomizationResultAdapter(gcl GitHubClient, k GithubFileSpec) (
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*doc.KustomizationDocument, error) {
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crawler.CrawlerDocument, error) {
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data, err := gcl.GetFileData(k)
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if err != nil {
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return nil, err
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}
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creationTime, err := gcl.GetFileCreationTime(k)
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if err != nil {
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logger.Printf("(error: %v) initializing to current time.", err)
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logger.Printf(
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"(error: %v) initializing to current time.\n", err)
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}
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url := gcl.ReposRequest(k.Repository.FullName)
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defaultBranch, err := gcl.GetDefaultBranch(url)
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if err != nil {
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logger.Printf(
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"(error: %v) setting default_branch to master\n", err)
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defaultBranch = "master"
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}
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doc := doc.KustomizationDocument{
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DocumentData: string(data),
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FilePath: k.Path,
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RepositoryURL: k.Repository.URL,
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CreationTime: creationTime,
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Document: doc.Document{
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DocumentData: string(data),
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FilePath: k.Path,
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DefaultBranch: defaultBranch,
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RepositoryURL: k.Repository.URL,
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},
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}
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return &doc, nil
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@@ -227,7 +310,34 @@ func (gcl GitHubClient) GetFileData(k GithubFileSpec) ([]byte, error) {
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}
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defer resp.Body.Close()
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return ioutil.ReadAll(resp.Body)
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data, err = ioutil.ReadAll(resp.Body)
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return data, err
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}
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func (gcl GitHubClient) GetDefaultBranch(url string) (string, error) {
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resp, err := gcl.GetReposData(url)
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if err != nil {
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return "", fmt.Errorf(
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"'%s' could not get default_branch: %v", url, err)
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}
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defer resp.Body.Close()
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data, err := ioutil.ReadAll(resp.Body)
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if err != nil {
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return "", fmt.Errorf(
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"could not read default_branch: %v", err)
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}
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type defaultBranch struct {
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DefaultBranch string `json:"default_branch,omitempty"`
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}
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var branch defaultBranch
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err = json.Unmarshal(data, &branch)
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if err != nil {
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return "", fmt.Errorf(
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"default_branch json malformed: %v", err)
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}
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return branch.DefaultBranch, nil
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}
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// GetFileCreationTime gets the earliest date of a file.
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@@ -301,29 +411,23 @@ func throttleRepoAPI() {
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<-contentRateTicker.C
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}
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const (
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accessTokenKeyword = "access_token="
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perPageKeyword = "per_page="
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contentSearchURL = "https://api.github.com/repos"
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contentKeyword = "contents"
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)
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type multiError []error
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func (me multiError) Error() string {
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size := len(me) + 2
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strs := make([]string, size)
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strs[0] = "Errors [\n\t"
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strs[0] = "Errors ["
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for i, err := range me {
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strs[i+1] = err.Error()
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strs[i+1] = "\t" + err.Error()
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}
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strs[size-1] = "\n]"
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return strings.Join(strs, "\n\t")
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strs[size-1] = "]"
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return strings.Join(strs, "\n")
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}
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type GithubFileSpec struct {
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Path string `json:"path,omitempty"`
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Repository struct {
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API string `json:"url,omitempty"`
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URL string `json:"html_url,omitempty"`
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FullName string `json:"full_name,omitempty"`
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} `json:"repository,omitempty"`
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@@ -127,6 +127,11 @@ func (rc RequestConfig) ContentsRequest(fullRepoName, path string) string {
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return rc.makeRequest(uri, Query{}).URL()
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}
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func (rc RequestConfig) ReposRequest(fullRepoName string) string {
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uri := fmt.Sprintf("repos/%s", fullRepoName)
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return rc.makeRequest(uri, Query{}).URL()
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}
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// CommitsRequest given the repo name, and a filepath returns a formatted query
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// for the Github API to find the commits that affect this file.
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func (rc RequestConfig) CommitsRequest(fullRepoName, path string) string {
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@@ -1,5 +1,102 @@
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package github
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// GitHub only returns at most 1000 results per search query,
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// this is problematic if you want to retrieve all the results for a given
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// search query. However, GitHub allows you to specify as much as you want per
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// query to make things more specific. Specifically for files, GitHub allows
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// you to specify their sizes with range queries. This is very convenient
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// since it allows us to split the search into disjoint sets/shards of results
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// from the different file size ranges.
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//
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// Some important factors to consider:
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//
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// - These queries are rate limited by the API to roughly once query every two
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// seconds.
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//
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// - The search space for file sizes is in bytes, from 0B to < 512KiB (this is
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// a huge search space that cannot be probed linearly in a timely manner if
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// granularity is to be expected).
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//
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// - If you have K files there will likely be ~K/1000 sets that you have find
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// from this search space in order to get all of the results.
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//
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// - If you have O(K) sets it is unlikely that they are all of the same size,
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// since (most files are power law distributed). That means that the range
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// might be significantly smaller for 1000 small files, than it is for
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// 1000 large files.
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//
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// - This method is a best effort approach. There are some limitations to what
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// it can and can't do, so please note the following:
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//
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// + There may very well be a filesize that has more than 1000 results.
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// this method cannot help in this case. However, requerying over time
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// (days/weeks/months) while sorting by last indexed values may be
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// sufficient to eventually get all of the results.
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//
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// + It's possible that the github API returns inconsistent counts. This
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// is problematic in most cases, since it can cause many issues if the
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// case is not handled properly. For instance, if you requested the
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// number of files of an interval from size:0..64 and get that there
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// are 900 results, you may query at size:0..96 and get that there
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// are 800 results. To guarantee that this approach completes and does
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// not get into a query loop over the same intervals, it will retry a few
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// times and take the largest of the results or the largest previously
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// queried value from another range (in this case, the implementation
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// could decide that size:0..96 must have 900) results. This makes the
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// approach best effort even if there are no single file sizes of over
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// 1000 results.
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//
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//
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// The approach that was taken to solve this problem is the following:
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//
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// 1. Determine the total number of results by querying from the lower bound
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// to the upper bound (size:0..max). If there are less than 1000 files,
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// return a single range of values (size:0..max) since all results can be
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// retrieved.
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//
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// 2. Otherwise, set a target number of files to be 1000.
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//
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// 3. Binary search for the range from 0..r that provides a file count that is
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// less than or equal to the target. Once this value is found, store the
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// upper bound of range (r). If r is the same as the previous value, (or 0)
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// increase r by one (this guarantees progress, but will miss out on some
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// results).
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//
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// 4. Increase the target by 1000.
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//
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// 5. Repeat steps 3 and 4 until the target is at or exceeds the total number
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// of files.
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//
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//
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// In general there are other ways to get all of the files from GitHub. In
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// some cases it would be sufficient to just get the files that are being
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// updated/indexed by github periodically to update the corpus, so this
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// complicated approach does not have to be run every time. However, for
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// some searches, there may be too many results on a time interval to do
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// this simple update search limited to only 1000 results.
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//
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// There is also a more sophisticated approach that may yield better
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// performance:
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// - Perform this search once and create a prior distribution of file sizes.
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// Each time you want to retrieve the results of the query, scale the
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// prior of expected ranges to the current number of files. From each
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// expected range of 1000 files, perform a exponential search to find the
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// lower bound of the range. This would likely reduce the total number
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// of queries by a significant amount since it would only have to search
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// for a small set of values around each likely range boundary.
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//
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// However, actually retrieving the files will be the bottleneck operation
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// since the number of queries to find the ranges will be close to:
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// log2(maxFileSize) * totalResults / 1000 ~= totalResults / 50
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// whereas the number of queries to actually get all of the search results
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// are close to:
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// apiCallsPerResult * 10(pages) * 100(resultsPerPage) * totalResults / 1000
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// = apiCallsPerResult * totalResults.
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//
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// So it could very well take apiCallsPerResult * 50 times longer to acutally
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// fetch the results (assuming the quotas for the API calls are the same as the
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// search API), than it does to perform these range searches.
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import (
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"fmt"
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"math/bits"
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@@ -12,14 +109,20 @@ const (
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githubMaxResultsPerQuery = uint64(1000)
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)
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// Interface for testing purposes. Not expecting to have multiple
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// implementations.
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// Interface instead of struct for testing purposes.
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// Not expecting to have multiple implementations.
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type cachedSearch interface {
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CountResults(uint64) (uint64, error)
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RequestString(filesize rangeFormatter) string
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}
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// Cache uses bit tricks to be more efficient in detecting
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// cachedSearch is a simple data structure that maps the upper bound (r) of a
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// range from 0 to r to the number of files that have between 0 and r files
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// (inclusive). It also guarantees that the counts are monotonically increasing
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// (not strict) as the value for r increases, by looking at the maximal
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// previous file count for the value that precedes r in the cache.
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//
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// It uses a bit trick to be more efficient in detecting
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// inconsistencies in the returned data from the Github API.
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// Therefore, the cache expects a search to always start at 0, and
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// it expects the max file size to be a power of 2. If this is to be changed
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@@ -36,11 +139,12 @@ type cachedSearch interface {
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// problematic). The current cache implementation looks at the
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// predecessor entry to find out if the current value is monotonic.
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// This is where the bit trick is used, since each step in the binary
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// search is adding or ommiting to add a decreasing of 2 to the query value,
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// we can remove the least significant set bit to find the predecessor in
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// constant time. Ultimately since the search is rate limited, we could also
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// easily afford to compute this in linear time by iterating
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// over cached values.
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// search is adding or ommiting to add a decreasing power of 2 to the query
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// value, we can remove the least significant set bit to find the
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// predecessor in constant time. Ultimately since the search is rate
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// limited, we could also easily afford to compute this in linear time
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// by iterating over cached values. So this trick is not crucial to the
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// cache's performance.
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type githubCachedSearch struct {
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cache map[uint64]uint64
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gcl GitHubClient
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@@ -160,7 +264,7 @@ func FindRangesForRepoSearch(cache cachedSearch) ([]string, error) {
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//
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// My intuition is that this approach is competitive to a perfectly
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// optimal solution, but I didn't actually take the time to do a
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// rigurous proof. Intuitively, since files sizes are typically power
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// rigorous proof. Intuitively, since files sizes are typically power
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// law distibuted the binary search will be very skewed towards the
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// smaller file ranges. This means that in practice this approach will
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// make fewer than (#files/1000)*(log(n) = 19) queries for
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Reference in New Issue
Block a user