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Date: Sun, 21 May 2017 04:04:04 +0000 (UTC)
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Subject: [jira] [Commented] (DRILL-5512) Standardize error handling in
 ScanBatch
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archived-at: Sun, 21 May 2017 04:04:11 -0000


    [ https://issues.apache.org/jira/browse/DRILL-5512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16018684#comment-16018684 ] 

ASF GitHub Bot commented on DRILL-5512:
---------------------------------------

Github user paul-rogers commented on a diff in the pull request:

    https://github.com/apache/drill/pull/838#discussion_r117622601
  
    --- Diff: exec/java-exec/src/main/java/org/apache/drill/exec/physical/impl/ScanBatch.java ---
    @@ -173,9 +174,8 @@ public IterOutcome next() {
     
             currentReader.allocate(mutator.fieldVectorMap());
           } catch (OutOfMemoryException e) {
    -        logger.debug("Caught Out of Memory Exception", e);
             clearFieldVectorMap();
    -        return IterOutcome.OUT_OF_MEMORY;
    +        throw UserException.memoryError(e).build(logger);
    --- End diff --
    
    You raise two good points.
    
    The first is that Drill tends to use unchecked exceptions because, well, they are convenient and Drill must handle such unchecked exceptions as NPE, illegal state, illegal argument and so on.
    
    But, normal Java practice is to declare exceptions so that callers know what they should handle. See DRILL-5386 asks to rationalize exception use. Comments in that ticket from project veterans shows some degree of resistance to the idea of checked exceptions. So, yes we must expect any unchecked exception from any method. This is why operators should handle all exceptions, and why we need code to sort out exceptions based on type.
    
    The analysis of OOM is correct, but omits context. It is seldom (never?) that a sort sits directly above a scan. Seems most often there is a filter or project between them. If the scan hits OOM, it is not likely because it has exhausted the memory limit on the scan operator: each operator defaults to 10 GB limit. Instead, it is likely that overall system memory is exhausted. So, what is likely to happen? Each operator between the scan and sort must handle the OUT_OF_MEMORY status by bubbling it up the call stack. Let's assume that works.
    
    The sort now wants to spill. Spilling is an activity that requires memory to perform. Spilling requires a merge phase to combine the records from buffered batches in sort order so that the spilled run is sorted. That is, the sort must allocate a batch, often many MB in size. (Spilled runs must be sizable so we can limit the number of spilled runs merged in the final merge phase.)
    
    So, the sort tries to allocate vectors for the merge batch and... The allocation fails. Why? Because we are out of system memory -- that's why the scanner triggered an OOM.
    
    I can find no code that sets up this out-of-system-memory condition to verify that existing code works. I think we were taking it on faith that this behavior actually works.
    
    Moving forward, we are working towards a workable solution. Assign the scan some amount of memory, and limit batches to fit within that memory. Give the sort a certain amount of memory, and have it manage within that memory so that when a spill occurs, the sort has sufficient memory to create the required merge batches as part of the spill.
    
    Finally, let's consider the case you outlined: the scan fails with OOM on the initial allocation. The initial allocation is often small; the scan goes through many vector doublings to read the full complement of rows. (At least, thats what I've observed empirically; perhaps the original intent was different.) Let's say we tried to recover from an initial allocation failure.
    
    Say we have a row with five columns. We allocate three, but fail on the fourth. Say the fourth is a Varchar: has two vectors: offset and data. The current logic releases the partially-allocated vectors, which is good. OUT_OF_MEMORY is returned and the vectors are reallocated if memory could be released. Sounds good.
    
    But, most queries run in multiple threads. If one hits OOM, then the others probably will as well. The actual system memory is a shared resource, but there is no coordination. A scan might release its partially-allocated vectors so the sort can, in theory, spill. But, that memory might immediately be grabbed by some other thread, resulting in a sort spill OOM. In practice, however, the initial vector allocations are much smaller than the merge batch, so it is only slightly useful to free up the initial allocation. That initial allocation, plus luck that some other thread has freed enough memory, might allow us to spill. But it is a crap-shoot.
    
    In short, even if this logic might possibly work in some scenarios in a single-threaded query, it is too chaotic to work in general with many threads. And, of course no tests exist for either case so we are just guessing.
    
    All-in-all, the above argues strongly that the path forward is to:
    
    1. Rationalize error handling: OOM errors cause query failure.
    2. Design a memory assignment system so that operators live within a budget.
    3. Design tests to ensure that the system works rather than relying on hope.
    
    This checkin is a step toward goal 1. The external sort revision, hash agg spilling and other projects are steps toward goal 2. We continue to chip away at our ability to do goal 3.
    
    Given all of this, can you suggest how we could gather evidence that the current OUT_OF_MEMORY status is actually working in any actual queries? Or, do we have a tough case of comparing concrete changes against an aspiration for how the system work might?
    
    More practically, with the change, OOM will fail the query. Previously, there is some chance that Drill might recover from an OOM. But, we have no tests and no statistics. Is it worth risking that hypothetical for a concrete step in the right direction. I don't think we have the answer and that, itself, is a problem. Thoughts?


> Standardize error handling in ScanBatch
> ---------------------------------------
>
>                 Key: DRILL-5512
>                 URL: https://issues.apache.org/jira/browse/DRILL-5512
>             Project: Apache Drill
>          Issue Type: Improvement
>    Affects Versions: 1.10.0
>            Reporter: Paul Rogers
>            Assignee: Paul Rogers
>            Priority: Minor
>              Labels: ready-to-commit
>             Fix For: 1.10.0
>
>
> ScanBatch is the Drill operator executor that handles most readers. Like most Drill operators, it uses an ad-hoc set of error detection and reporting methods that evolved over Drill development.
> This ticket asks to standardize on error handling as outlined in DRILL-5083. This basically means reporting all errors as a {{UserException}} rather than using the {{IterOutcome.STOP}} return status or using the {{FragmentContext.fail()}} method.
> This work requires the new error codes introduced in DRILL-5511, and is a step toward making readers aware of vector size limits.


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