[jira] [Updated] (APEXMALHAR-2190) Use reusable buffer to serial spillable data structure

["bright chen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/APEXMALHAR-2190?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

bright chen updated APEXMALHAR-2190:
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    Summary: Use reusable buffer to serial spillable data structure  (was: Use shared memory to serial spillable data structure)

> Use reusable buffer to serial spillable data structure
> ------------------------------------------------------
>
>                 Key: APEXMALHAR-2190
>                 URL: https://issues.apache.org/jira/browse/APEXMALHAR-2190
>             Project: Apache Apex Malhar
>          Issue Type: Task
>            Reporter: bright chen
>            Assignee: bright chen
>   Original Estimate: 240h
>  Remaining Estimate: 240h
>
> Spillable Data Structure created lots of temporary memory to serial data lot of of memory copy( see SliceUtils.concatenate(byte[], byte[]). Which used up memory very quickly. See APEXMALHAR-2182.
> Use a shared memory to avoid allocate temporary memory and memory copy
> some basic ideas
> - SerToLVBuffer interface provides a method serTo(T object, LengthValueBuffer buffer): instead of create a memory and then return the serialized data, this method let the caller pass in the buffer. So different objects or object with embed objects can share the same LengthValueBuffer
> - LengthValueBuffer: It is a buffer which manage the memory as length and value(which is the generic format of serialized data). which provide length placeholder mechanism to avoid temporary memory and data copy when the length can be know after data serialized
> - memory management classes: includes interface ByteStream and it's implementations: Block, FixedBlock, BlocksStream. Which provides a mechanism to dynamic allocate and manage memory. Which basically provides following function. I tried other some other stream mechamism such as ByteArrayInputStream, but it can meet 3rd criteria, and don't have good performance(50% loss) 
>   - dynamic allocate memory
>   - reset memory for reuse
>   - BlocksStream make sure the output slices will not be changed when need extra memory; Block can change the reference of output slices buffer is data was moved due to reallocate of memory(BlocksStream is better solution).



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