[MM-55726] Create batch report worker, add batch report job for exporting users to CSV (#25832)
* Split out migration logic and create generic BatchWorker * WIP * WIP * POC batch reporting * Oops * Job hookup * Working export to file * PR feedback * Merge'd * Fix error handling * Add API to start report, translations, couple fixes * Add DMs to send reports to users * Merge'd * Update types * A bit of cleanup * Some fixes * Add missing API doc * PR feedback * Fix generated * Fix bug with post creation * PR feedback * Add some tests * PR feedback * Fix lint * Some test changes * Fix tests * Add comment to explain why we forcibly stop * Rework of some tests * Batch report test * Restrict batch exports to Pro and Enterprise licenses * Fix erroneous comment --------- Co-authored-by: Mattermost Build <build@mattermost.com>
Этот коммит содержится в:
Devin Binnie
коммит произвёл
GitHub
GitHub
родитель
eac9a39677
Коммит
f7446d7443
174
server/channels/jobs/batch_worker.go
Обычный файл
174
server/channels/jobs/batch_worker.go
Обычный файл
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// Copyright (c) 2015-present Mattermost, Inc. All Rights Reserved.
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// See LICENSE.txt for license information.
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package jobs
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import (
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"sync/atomic"
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"time"
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"github.com/mattermost/mattermost/server/public/model"
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"github.com/mattermost/mattermost/server/public/shared/mlog"
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"github.com/mattermost/mattermost/server/public/shared/request"
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"github.com/mattermost/mattermost/server/v8/channels/store"
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)
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type BatchWorker struct {
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jobServer *JobServer
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logger mlog.LoggerIFace
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store store.Store
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stop chan struct{}
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stopped chan bool
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closed atomic.Bool
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jobs chan model.Job
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timeBetweenBatches time.Duration
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doBatch func(rctx *request.Context, job *model.Job) bool
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}
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// MakeBatchWorker creates a worker to process the given batch function.
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func MakeBatchWorker(
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jobServer *JobServer,
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store store.Store,
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timeBetweenBatches time.Duration,
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doBatch func(rctx *request.Context, job *model.Job) bool,
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) *BatchWorker {
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return &BatchWorker{
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jobServer: jobServer,
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logger: jobServer.Logger(),
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store: store,
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stop: make(chan struct{}),
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stopped: make(chan bool, 1),
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jobs: make(chan model.Job),
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timeBetweenBatches: timeBetweenBatches,
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doBatch: doBatch,
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}
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}
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// Run starts the worker dedicated to the unique migration batch job it will be given to process.
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func (worker *BatchWorker) Run() {
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worker.logger.Debug("Worker started")
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// We have to re-assign the stop channel again, because
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// it might happen that the job was restarted due to a config change.
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if worker.closed.CompareAndSwap(true, false) {
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worker.stop = make(chan struct{})
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}
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defer func() {
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worker.logger.Debug("Worker finished")
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worker.stopped <- true
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}()
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for {
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select {
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case <-worker.stop:
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worker.logger.Debug("Worker received stop signal")
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return
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case job := <-worker.jobs:
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worker.DoJob(&job)
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}
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}
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}
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// Stop interrupts the worker even if the migration has not yet completed.
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func (worker *BatchWorker) Stop() {
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// Set to close, and if already closed before, then return.
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if !worker.closed.CompareAndSwap(false, true) {
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return
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}
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worker.logger.Debug("Worker stopping")
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close(worker.stop)
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<-worker.stopped
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}
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// JobChannel is the means by which the jobs infrastructure provides the worker the job to execute.
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func (worker *BatchWorker) JobChannel() chan<- model.Job {
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return worker.jobs
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}
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// IsEnabled is always true for batches.
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func (worker *BatchWorker) IsEnabled(_ *model.Config) bool {
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return true
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}
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// DoJob executes the job picked up through the job channel.
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//
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// Note that this is a lot of distracting machinery here to claim the job, then double check the
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// status, and keep the status up to date in line with job infrastrcuture semantics. Unless an
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// error occurs, this worker should hold onto the job until its completed.
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func (worker *BatchWorker) DoJob(job *model.Job) {
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logger := worker.logger.With(mlog.Any("job", job))
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logger.Debug("Worker received a new candidate job.")
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defer worker.jobServer.HandleJobPanic(logger, job)
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if claimed, err := worker.jobServer.ClaimJob(job); err != nil {
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logger.Warn("Worker experienced an error while trying to claim job", mlog.Err(err))
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return
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} else if !claimed {
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return
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}
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c := request.EmptyContext(logger)
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var appErr *model.AppError
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// We get the job again because ClaimJob changes the job status.
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job, appErr = worker.jobServer.GetJob(c, job.Id)
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if appErr != nil {
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worker.logger.Error("Worker: job execution error", mlog.Err(appErr))
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worker.setJobError(logger, job, appErr)
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return
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}
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if job.Data == nil {
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job.Data = make(model.StringMap)
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}
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for {
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select {
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case <-worker.stop:
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logger.Info("Worker: Batch has been canceled via Worker Stop. Setting the job back to pending.")
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if err := worker.jobServer.SetJobPending(job); err != nil {
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worker.logger.Error("Worker: Failed to mark job as pending", mlog.Err(err))
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}
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return
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case <-time.After(worker.timeBetweenBatches):
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if stop := worker.doBatch(c, job); stop {
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return
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}
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}
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}
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}
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// resetJob erases the data tracking the next batch to execute and returns the job status to
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// pending to allow the job infrastructure to requeue it.
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func (worker *BatchWorker) resetJob(logger mlog.LoggerIFace, job *model.Job) {
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job.Data = nil
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job.Progress = 0
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job.Status = model.JobStatusPending
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if _, err := worker.store.Job().UpdateOptimistically(job, model.JobStatusInProgress); err != nil {
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worker.logger.Error("Worker: Failed to reset job data. May resume instead of restarting.", mlog.Err(err))
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}
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}
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// setJobSuccess records the job as successful.
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func (worker *BatchWorker) setJobSuccess(logger mlog.LoggerIFace, job *model.Job) {
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if err := worker.jobServer.SetJobProgress(job, 100); err != nil {
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logger.Error("Worker: Failed to update progress for job", mlog.Err(err))
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worker.setJobError(logger, job, err)
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}
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if err := worker.jobServer.SetJobSuccess(job); err != nil {
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logger.Error("Worker: Failed to set success for job", mlog.Err(err))
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worker.setJobError(logger, job, err)
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}
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}
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// setJobError puts the job into an error state, preventing the job from running again.
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func (worker *BatchWorker) setJobError(logger mlog.LoggerIFace, job *model.Job, appError *model.AppError) {
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if err := worker.jobServer.SetJobError(job, appError); err != nil {
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logger.Error("Worker: Failed to set job error", mlog.Err(err))
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}
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}
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