I can't seem to find a straightforward way to run multiple process flows at once. I can select multiple and right click, but the 'Run' function disappears.
Any ideas? Programmatic or otherwise?
Assuming you mean you want to run multiple flows sequentially, you would use an Ordered List to do that. You can include any number of programs in a process flow.
Process flows are intended to contain all of the items you want to run in one shot, so you would not normally run many entire process flows at once. You can of course run one, then run the next one, if it's a few. I don't believe you can link programs or objects from one process flow to another.
If you mean run simultaneously, then you can do that if you set your project up to allow parallel execution, and your server allows it. File -> Project Properties -> Code Submission, check "Allow parallel execution on the same server" allows you to run multiple things at once - but be aware that each submission is in its own distinct SAS session and doesn't have direct access to the other submissions' temporary libraries or macro variables.
Related
I come from experiences with Luigi, where if a file was produced successfully by a task and the task was also unmodified, then re-runs of the DAG would not re-run that task, but would reuse its previously-obtained output.
Is there any way to obtain the same behavior with AirFlow?
Currently, if I re-run the dag, it re-executes all the tasks, no matter if they produced a successful (and unchanged) output in the past. So, basically I need a task to be marked as successful if its code was unchanged.
This is the crucial and important feature of Airflow to have all the tasks as idempotent. This means that re-running a task on the same input should generally override the output with newly processed version of that data - so that task depending on it can be automatically rerun. But the data might be different after reprocessing than it was originally.
That's why in Airflow you have a backfill command that basically means.
Please re-run this DAG for selected past runs (say last week worth of runs) - but you should JUST reprocess starting from task X (which will re-run task X and ALL tasks that depend on its output).
This also means that when you want to re-run parts of past DAGs but you know that you want to relay on existing output of certain tasks there - you only backfill the tasks that are depending on the output of that task (but not the task itself).
This allows for much more flexibility by defining which tasks in past DAG runs should be re-run (you basically invalidate outputs of certain tasks by making them target of backfill).
This covers more than the case you mention:
a) if you want to not change an output of certain task - you do not backfill that task - but the task(s) that follow from it
b) more importantly - if you want to re-process the task even in the task input and task itself were modified, you can still do it - by backfilling that task.
The case b) is often important, because some of the tasks might have implicit dependencies that change - even if the inputs and task did not change, processing it again might produce different (often better) result.
A good example that I've heard is re-processing call records by telecom operators where you had to determine phone models from IMEI of the phones. In this case you might have a single service that does the mapping, but it might get updated to a newer version when manufacturers refresh their model database - when new phones are introduced, the refresh will happen with some delays, so reprocessing regularly last week's of data might give different results even if the input ("list of calls") and task ("execute map IMEIS to phone models") did not change from the DAG's Python point of view.
Airflow almost always calls external services to run certain tasks, and those services themselves might improve over time - this means that limiting re-processing to the cases where "no input + no task code" has changed is very limiting (but you can still deliberately decide on it by choosing the backfill scope - i.e. which tasks to reprocess).
I'm trying to understand the Enterprise Guide process flow. As I understand it, the process flow is supposed to make it easy to run related steps in the order they need to be run to make a dependent action able to run and be up to date somewhere later in the flow.
Given that understanding, I'm getting stuck trying to make the process flow work in cases where the temporary data is purged. I'm warned when closing Enterprise Guide that the project has references to temporary data which must be the tables I created. That should be fine, the data is on the SAS server and I wrote code to import that data into SAS.
I would expect that the data can be regenerated when I try run an analysis that depends on that data again later, but instead I'm getting an error indicating that the input data does not exist. If I then run the code to import the data and/or join tables in each necessary place, the process flow seems to work as expected.
See the flow that I'm working with below:
I'm sure I must be missing something. Imagine I want to rerun the rightmost linear regression. Is there a way to make the process flow import the data without doing so manually for each individual table creation the first time round?
The general answer to your question is probably that you can't really do what you're wanting directly, but you can do it indirectly.
A process flow (of which you can have many per project, don't forget) is a single set of programs/tasks/etc. that you intend to run as a group. Typically, you will run whole process flows at once, rather than just individual pieces. If you have a point that you want to pause, look at things, then continue, then you have a few choices.
One is to have a process flow that goes to that point, then a second process flow that starts from that point. You can even take your 'import data' steps out of the process flow entirely, make an 'import data' process flow, always run that first, then run the other process flows individually as you need them. In fact, if you use the AUTOEXEC process flow, you could have the import data steps run whenever you open the project, and imported data ready and waiting for you.
A second is to use the UI and control+click or drag a box to select on the process flow to select a group of programs to run; select the first five, say, then run them, then select 'run branch from program...' option to run from that point on. You could also make separate 'branches' and run just the one branch at a time, making each branch dependent on the input streams.
A third option would be to have different starting points for different analysis tasks, and have the import data bit be after that starting point. It could be common to the starting points, and use macro variables and conditional execution to go different directions. For example, you could have a macro variable set in the first program that says which analysis program you're running, then the conditional from the last import step (which are in sequence, not in parallel like you have them) send you off to whatever analysis task the macro variable says. You could also have macro variables that indicate whether an import has been run once already in the current session that then would tell you not to rerun it via conditional steps.
Unfortunately, though, there's no direct way to run something and say 'run this and all of its dependencies', though.
Also how to make SAS Enterprise Guide to go to Output Data tab after a successful run instead of Results tab?
It's going to go to Results if you produce results, I don't think there's any way around that. You will get all of the datasets produced in that program in the Output Data tab, as well.
However, I'm going to venture a guess here: you're using EG like a single window programming environment, right? You have a single long program? If so, then the answer is simple: split your program up. EG is intended to have lots of small programs, each of which have a very specific goal and output. Think of it as steps: each program node is just one step, could be even just one data step. Then you link several programs together, in sequence, and run them all as a process flow (or an ordered list).
If you treat it that way, then it works very much like you say: you can have one program that has one output dataset and no results window, if your last program in a process flow just produces one dataset and no results.
I am working on a project in SAS EG (7.1) which involves process dependence and parallel execution, as depicted below:
I have the following questions:
Is there a way to retrieve or set relations (i.e. process_C --> program_D) between the processes programmatically? The maintenance is becoming problematic with complex projects. Ideally, I would like to be able to re-create the links between processes from external table.
I start the whole process with the option “Run branch from <>” process. Let’s assume that we have only 2 processors available. Is there a way to set the order of execution between process_A, B, C? The critical path of the whole flow is “begin -> process_C -> process_D -> end” hence we would like it to start with process_C in order to ensure minimum execution time.
Thank you in advance.
For 1, I think the answer is "no", if you mean a well defined SAS programmatic method. At least for the relatively limited information and example you provide above, anyway. More might be possible with metadata server - not my area of expertise.
You can do some of this at least using scripting via Powershell or VBScript. EG's API is fairly wide open and not all that hard to use. I won't suggest how as my understanding of this is limited also, but it seems like it should be possible to do what you suggest, though probably not easy.
For your second point:
First off, EG typically runs "top to bottom" if it has no other information on how to process a particular choice. So put c->d above a/b to get it processed first.
Second, you could use conditional processing perhaps. There should be a macro variable that tells you how many cpus you have (&SYSNCPU on my machine, hopefully same on other versions). You could use that value to conditionally link to A then B as opposed to A+B simultaneously. I'm not sure how easy this would be to do in a flexible fashion, though.
I have just started with Spark and was struggling with the concept of tasks.
Can any one please help me in understanding when does an action (say reduce) not run in the driver program.
From the spark tutorial,
"Aggregate the elements of the dataset using a function func (which
takes two arguments and returns one). The function should be
commutative and associative so that it can be computed correctly in
parallel. "
I'm currently experimenting with an application which reads a directory on 'n' files and counts the number of words.
From the web UI the number of tasks is equal to number of files. And all the reduce functions are taking place on the driver node.
Can you please tell a scenario where the reduce function won't execute at the driver. Does a task always include "transformation+action" or only "transformation"
All the actions are performed on the cluster and results of the actions may end up on the driver (depending on the action).
Generally speaking the spark code you write around your business logic is not the program that would actually run - rather spark uses it to create a plan which will execute your code in the cluster. The plan creates a task of all the actions that can be done on a partition without the need to shuffle data around. Every time spark needs the data arranged differently (e.g. after sorting) It will create a new task and a shuffle between the first and the latter tasks
Ill take a stab at this, although I may be missing part of the question. A task is indeed always transformation(s) and an action. The transformation's are lazy and would not submit anything, thus the need for an action. You can always call .toDebugString on your RDD to see where each job split will be; each level of indentation is a new stage. I think the reduce function showing on the driver is a bit of a misnomer as it will run first in parallel and then merge the results. So, I would expect that the task does indeed run on the workers as far as it can.