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https://issues.apache.org/jira/browse/CASSANDRA-13794?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16166838#comment-16166838
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Benedict edited comment on CASSANDRA-13794 at 9/14/17 7:13 PM:
---------------------------------------------------------------
This patch is great (excepting a couple of extraneous edits). Love the
comments.
+1
I would suggest filing two follow-up tickets to address some short comings with
this code path, but they're edge-case, and not straight-forward enough, to not
block this merge.
# For some extreme users, 16 rows could be a huge amount of data. There should
probably be some modulation of this lower bound based on known data sizes in
the table, or the like.
# Conversely, in an overloaded cluster on which users are commonly performing
fairly large-limit reads (say, 1k+ moderate sized rows) of larger partitions,
we could find ourselves doubling the amount of work the cluster needs to do;
during overload we can expect dropped writes, and a single missing row in any
read would trigger a same-sized read. This could iteratively compound the
overload.
The best solutions to this problem are probably non-trivial, though a simplish
approach might be to use exponential growth, bounded on both sides by a minimum
and maximum (perhaps similarly determined from the known data size
distribution) - with the query limit being used as the first value if it is
small enough.
I _would_ say that (2) is no worse than the status-quo, given the per-request
overheads are probably greater than the per-datum overheads in a typical
cluster, but CASSANDRA-12872 suggests we haven't been incurring the full
overheads of SRP, so we cannot claim that. I still think it is reasonable to
address this in a follow-up ticket, however.
was (Author: benedict):
This patch is great (excepting a couple of extraneous edits). Love the
comments.
+1
I would suggest filing two follow-up tickets to address some short comings with
this code path, but they're edge-case, and not straight-forward enough, to not
block this merge.
# For some extreme users, 16 rows could be a huge amount of data. There should
probably be some modulation of this lower bound based on known data sizes in
the table, or the like.
# Conversely, in an overloaded cluster on which users are commonly performing
fairly large-limit reads (say, 1k+ moderate sized rows) of larger partitions,
we could find ourselves doubling the amount of work the cluster needs to do;
during overload we can expect dropped writes, and a single missing row in any
read would trigger a same-sized read. This could iteratively compound the
overload.
The best solutions to this problem are probably non-trivial, though a simplish
approach might be to use exponential growth, bounded on both sides by a minimum
and maximum (perhaps similarly determined from the known data size
distribution) - with the query limit being used as the first value if it is
small enough.
I _would_ say that (2) is now worse than the status-quo, given the per-request
overheads are probably greater than the per-datum overheads in a typical
cluster, but CASSANDRA-12872 suggests we haven't been incurring the full
overheads of SRP, so we cannot claim that. I still think it is reasonable to
address this in a follow-up ticket, however.
> Fix short read protection logic for querying more rows
> ------------------------------------------------------
>
> Key: CASSANDRA-13794
> URL: https://issues.apache.org/jira/browse/CASSANDRA-13794
> Project: Cassandra
> Issue Type: Bug
> Components: Coordination
> Reporter: Benedict
> Assignee: Aleksey Yeschenko
> Labels: Correctness
> Fix For: 3.0.x, 3.11.x
>
>
> Discovered by [~benedict] while reviewing CASSANDRA-13747:
> {quote}
> While reviewing I got a little suspicious of the modified line
> {{DataResolver}} :479, as it seemed that n and x were the wrong way around...
> and, reading the comment of intent directly above, and reproducing the
> calculation, they are indeed.
> This is probably a significant enough bug that it warrants its own ticket for
> record keeping, though I'm fairly agnostic on that decision.
> I'm a little concerned about our current short read behaviour, as right now
> it seems we should be requesting exactly one row, for any size of under-read,
> which could mean extremely poor performance in case of large under-reads.
> I would suggest that the outer unconditional {{Math.max}} is a bad idea, has
> been (poorly) insulating us from this error, and that we should first be
> asserting that the calculation yields a value >= 0 before setting to 1.
> {quote}
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