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https://issues.apache.org/jira/browse/FLINK-12886?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16867311#comment-16867311
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Jingsong Lee commented on FLINK-12886:
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Hi [~fan_li_ya], Thanks for your proposal. I think we should discuss whether we
should introduce container memory segment.
First, I don't think one more MemorySegment implementation is a good thing. You
can take a look to the comments of MemorySegment, For best efficiency, the code
that uses this class should make sure that only one subclass is loaded, or that
the methods that are abstract in this class are used only from one of the
subclasses.
Second, The segment size may be not a power of 2 in BinaryString and BinaryRow.
You can see BinaryRowSerializer.deserialize.
Third, in LongHashPartition, the calculated offset will reuse to getLong. And
it doesn't have that much code.
> Support container memory segment
> --------------------------------
>
> Key: FLINK-12886
> URL: https://issues.apache.org/jira/browse/FLINK-12886
> Project: Flink
> Issue Type: New Feature
> Components: Table SQL / Runtime
> Reporter: Liya Fan
> Assignee: Liya Fan
> Priority: Major
> Labels: pull-request-available
> Attachments: image-2019-06-18-17-59-42-136.png
>
> Time Spent: 10m
> Remaining Estimate: 0h
>
> We observe that in many scenarios, the operations/algorithms are based on an
> array of MemorySegment. These memory segments form a large, combined, and
> continuous memory space.
> For example, suppose we have an array of n memory segments. Memory addresses
> from 0 to segment_size - 1 are served by the first memory segment; memory
> addresses from segment_size to 2 * segment_size - 1 are served by the second
> memory segment, and so on.
> Specific algorithms decide the actual MemorySegment to serve the operation
> requests. For some rare cases, two or more memory segments serve the
> requests. There are many operations based on such a paradigm, for example,
> {{BinaryString#matchAt}}, {{SegmentsUtil#copyToBytes}},
> {{LongHashPartition#MatchIterator#get}}, etc.
> The problem is that, for memory segment array based operations, large amounts
> of code is devoted to
> 1. Computing the memory segment index & offset within the memory segment.
> 2. Processing boundary cases. For example, to write an integer, there are
> only 2 bytes left in the first memory segment, and the remaining 2 bytes must
> be written to the next memory segment.
> 3. Differentiate processing for short/long data. For example, when copying
> memory data to a byte array. Different methods are implemented for cases when
> 1) the data fits in a single segment; 2) the data spans multiple segments.
> Therefore, there are much duplicated code to achieve above purposes. What is
> worse, this paradigm significantly increases the amount of code, making the
> code more difficult to read and maintain. Furthermore, it easily gives rise
> to bugs which difficult to find and debug.
> To address these problems, we propose a new type of memory segment:
> {{ContainerMemorySegment}}. It is based on an array of underlying memory
> segments with the same size. It extends from the {{MemorySegment}} base
> class, so it provides all the functionalities provided by {{MemorySegment}}.
> In addition, it hides all the details for dealing with specific memory
> segments, and acts as if it were a big continuous memory region.
> A prototype implementation is given below:
> !image-2019-06-18-17-59-42-136.png|thumbnail!
> With this new type of memory segment, many operations/algorithms can be
> greatly simplified, without affecting performance. This is because,
> 1. Many checks, boundary processing are already there. We just move them to
> the new class.
> 2. We optimize the implementation of the new class, so the special
> optimizations (e.g. optimizations for short data) are still preserved.
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