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https://issues.apache.org/jira/browse/CASSANDRA-2062?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12987480#action_12987480
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Stu Hood commented on CASSANDRA-2062:
-------------------------------------
Also, as an important side note: the core reason for implementing this was to
gain control over the consumption of the lazy nested iterators in the read path.
We survive now because we write the size of the row at the front of the row
(via some serious acrobatics at write time), which gives us hasNext() for rows
for free. But it became apparent while working on the block-based format that
hasNext() will not be cheap unless the current item has been consumed.
"Consumption" of the row is easy, and blocks will be framed so that they can be
very easily skipped, but you don't want to have to seek to the end of the row
to answer hasNext, and then seek back to the beginning to consume the row,
which is what CollatingIterator would have forced us to do.
There is actually one more roadblock to making this crazy iterator dance work:
ReducingIterator pulls one more item than it needs from its source before
'reducing' (consuming) the items it is holding. This breaks the invariant, but
it should be fixable by smashing ReducingIterator into MergeIterator.
> Use more efficient merge algorithm
> ----------------------------------
>
> Key: CASSANDRA-2062
> URL: https://issues.apache.org/jira/browse/CASSANDRA-2062
> Project: Cassandra
> Issue Type: Improvement
> Components: Core
> Reporter: Stu Hood
> Priority: Minor
> Fix For: 0.7.2
>
> Attachments: 0001-Improved-iterator-for-merging-sorted-iterators.txt,
> 0002-Quickie-instrumentation-for-comparisons.txt,
> 0003-Replace-Collating-with-Merge-in-CompactionIterator.txt,
> 0004-Port-LazilyCompactedRow-ReducingKeyIterator-RangeSlice.txt,
> 0005-Remove-temporary-instrumentation-and-CollatingIterator.txt
>
>
> For {{M}} iterators containing {{N}} total items,
> commons.collections.CollatingIterator performs a {{O(M*N)}} merge, and calls
> hasNext multiple times per returned value. We can do better.
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