Deferred Processing of Data¶

While a Pachyderm pipeline is running, it processes any new data that you commit to its input branch. However, in some cases, you want to commit data more frequently than you want to process it.

Because Pachyderm pipelines do not reprocess the data that has already been processed, in most cases, this is not an issue. But, some pipelines might need to process everything from scratch. For example, you might want to commit data every hour, but only want to retrain a machine learning model on that data daily because it needs to train on all the data from scratch.

In these cases, you can leverage a massive performance benefit from deferred processing. This section covers how to achieve that and control what gets processed.

Pachyderm controls what is being processed by using the filesystem, rather than at the pipeline level. Although pipelines are inflexible, they are simple and always try to process the data at the heads of their input branches. In contrast, the filesystem is very flexible and gives you the ability to commit data in different places and then efficiently move and rename the data so that it gets processed when you want.

Configure a Staging Branch in an Input repository¶

When you want to load data into Pachyderm without triggering a pipeline, you can upload it to a staging branch and then submit accumulated changes in one batch by re-pointing the HEAD of your master branch to a commit in the staging branch.

Although, in this section, the branch in which you consolidate changes is called staging, you can name it as you like.

In the example below, we first create a repository called data on which we configure a staging branch:

   "pfs": {
      "repo": "data",
      "branch": "master",
      "glob": "/*",
}

1. Create a repository. For example, data.

   $ pachctl create repo data
   

2. Create a master branch.

   $ pachctl create branch data@master
   

3. View the created branch:

   $ pachctl list commit data
   

   REPO BRANCH COMMIT                           FINISHED           SIZE  ORIGIN DESCRIPTION
   data master 8090bfb4d4fe44158eac12199c37a591 About a minute ago   0B  AUTO
   

   Pachyderm automatically created an empty HEAD commit on the new branch, as you can see from the zero-byte size and AUTO commit origin. When you commit data to the master branch, the pipeline immediately starts a job to process it. However, if you want to commit something without immediately processing it, you need to commit it to a different branch.

4. Commit a file to the staging branch:

   $ pachctl put file data@staging -f <file>
   

   Pachyderm automatically creates the staging branch. Your repo now has 2 branches, staging and master. In this example, the staging name is used, but you can name the branch as you want.

5. Verify that the branches were created:

   $ pachctl list branch data
   

   BRANCH  HEAD                              TRIGGER
   
   staging f3506f0fab6e483e8338754081109e69   -
   master  8090bfb4d4fe44158eac12199c37a591   -
   

   The master branch still has the same HEAD commit. No jobs have started to process the new file, because there are no pipelines that take staging as inputs. You can continue to commit to staging to add new data to the branch, and the pipeline will not process anything.

6. When you are ready to process the data, update the master branch to point it to the head of the staging branch:

   $ pachctl create branch data@master --head staging
   

7. List your branches to verify that the master branch's HEAD commit has changed:

   $ pachctl list branch data
   

   staging f3506f0fab6e483e8338754081109e69
   master  f3506f0fab6e483e8338754081109e69
   

   The master and staging branches now have the same HEAD commit. This means that your pipeline has data to process.

8. Verify that the pipeline has new jobs:

   $ pachctl list job test@f3506f0fab6e483e8338754081109e69
   
   ID                               PIPELINE STARTED        DURATION           RESTART PROGRESS  DL   UL  STATE
   f3506f0fab6e483e8338754081109e69 test     32 seconds ago Less than a second 0       6 + 0 / 6 108B 24B success
   

   You should see one job that Pachyderm created for all the changes you have submitted to the staging branch, with the same ID. While the commits to the staging branch are ancestors of the current HEAD in master, they were never the actual HEAD of master themselves, so they do not get processed. This behavior works for most of the use cases because commits in Pachyderm are generally additive, so processing the HEAD commit also processes data from previous commits.

Process Specific Commits¶

Sometimes you want to process specific intermediary commits that are not in the HEAD of the branch. To do this, you need to set master to have these commits as HEAD. For example, if you submitted ten commits in the staging branch and you want to process the seventh, third, and most recent commits, you need to run the following commands respectively:

$ pachctl create branch data@master --head staging^7
$ pachctl create branch data@master --head staging^3
$ pachctl create branch data@master --head staging

When you run the commands above, Pachyderm creates a job for each of the commands one after another. Therefore, when one job is completed, Pachyderm starts the next one. To verify that Pachyderm created jobs for these commands, run pachctl list job -p <pipeline_name> --history all.

Change the HEAD of your Branch¶

You can move backward to previous commits as easily as advancing to the latest commits. For example, if you want to change the final output to be the result of processing staging^1, you can roll back your HEAD commit by running the following command:

$ pachctl create branch data@master --head staging^1

This command starts a new job to process staging^1. The HEAD commit on your output repo will be the result of processing staging^1 instead of staging.

Copy Files from One Branch to Another¶

Using a staging branch allows you to defer processing. To use this functionality you need to know your input commits in advance. However, sometimes you want to be able to commit data in an ad-hoc, disorganized manner and then organize it later. Instead of pointing your master branch to a commit in a staging branch, you can copy individual files from staging to master. When you run copy file, Pachyderm only copies references to the files and does not move the actual data for the files around.

To copy files from one branch to another, complete the following steps:

1. Start a commit:

   $ pachctl start commit data@master
   

2. Copy files:

   $ pachctl copy file data@staging:file1 data@master:file1
   $ pachctl copy file data@staging:file2 data@master:file2
   ...
   

3. Close the commit:

   $ pachctl finish commit data@master
   

Deferred Processing in Output Repositories¶

You can perform the same deferred processing operations with data in output repositories. To do so, rather than committing to a staging branch, configure the output_branch field in your pipeline specification.

To configure deferred processing in an output repository, complete the following steps:

1. In the pipeline specification, add the output_branch field with the name of the branch in which you want to accumulate your data before processing:

   "output_branch": "staging"
   

2. When you want to process data, run:

   $ pachctl create branch pipeline@master --head staging
   

Automate Deferred Processing With Branch Triggers¶

Typically, repointing from one branch to another happens when a certain condition is met. For example, you might want to repoint your branch when you have a specific number of commits, or when the amount of unprocessed data reaches a certain size, or at a specific time interval, such as daily, or other. This can be automated using branch triggers. A trigger is a relationship between two branches, such as master and staging in the examples above, that says: when the head commit of staging meets a certain condition it should trigger master to update its head to that same commit. In other words it does pachctl create branch data@master --head staging automatically when the trigger condition is met.

Building on the example above, to make master automatically trigger when there's 1 Megabyte of new data on staging, run:

$ pachctl create branch data@master --trigger staging --trigger-size 1MB
$ pachctl list branch data

BRANCH  HEAD                             TRIGGER
staging 8b5f3eb8dc4346dcbd1a547f537982a6 -
master  8090bfb4d4fe44158eac12199c37a591 staging on Size(1MB)

When you run that command, it may or may not set the head of master. It depends on the difference between the size of the head of staging and the existing head of master, or 0 if it doesn't exist. Notice that in the example above staging had an existing head with less than a MB of data in it so master is still empty. If you don't see staging when you list branch that's ok, triggers can point to branches that don't exist yet. The head of master will update if you add a MB of new data to staging:

$ dd if=/dev/urandom bs=1MiB count=1 | pachctl put file data@staging:/file
$ pachctl list branch data

BRANCH  HEAD                             TRIGGER
staging 64b70e6aeda84845858c42d755023673 -
master  64b70e6aeda84845858c42d755023673 staging on Size(1MB)

Triggers automate deferred processing, but they don't prevent manually updating the head of a branch. If you ever want to trigger master even though the trigger condition hasn't been met you can run:

$ pachctl create branch data@master --head staging

Notice that you don't need to re-specify the trigger when you call create branch to change the head. If you do want to clear the trigger delete the branch and recreate it.

There are three conditions on which you can trigger the repointing of a branch.

• time, using a cron specification (--trigger-cron)
• size (--trigger-size)
• number of commits (--trigger-commits)

When more than one is specified, a branch repoint will be triggered when any of the conditions is met. To guarantee that they all must be met, add --trigger-all.

To experiment further, see the full triggers example.

Embed Triggers in Pipelines¶

Triggers can also be specified in the pipeline spec and automatically created when the pipeline is created. For example, this is the edges pipeline from our our OpenCV demo modified to only trigger when there is a 1 Megabyte of new images:

{
  "pipeline": {
    "name": "edges"
  },
  "description": "A pipeline that performs image edge detection by using the OpenCV library.",
  "input": {
    "pfs": {
      "glob": "/*",
      "repo": "images",
      "trigger": {
          "size": "1MB"
      }
    }
  },
  "transform": {
    "cmd": [ "python3", "/edges.py" ],
    "image": "pachyderm/opencv"
  }
}

When you create this pipeline, Pachyderm will also create a branch in the input repo that specifies the trigger and the pipeline will use that branch as its input. The name of the branch is auto-generated with the form <pipeline-name>-trigger-n. You can manually update the heads of these branches to trigger processing just like in the previous example.

More advanced automation¶

More advanced use cases might not be covered by the trigger methods above. For those, you need to create a Kubernetes application that uses Pachyderm APIs and watches the repositories for the specified condition. When the condition is met, the application switches the Pachyderm branch from staging to master.