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https://issues.apache.org/jira/browse/HBASE-14918?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Eshcar Hillel updated HBASE-14918:
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Description:
A memstore serves as the in-memory component of a store unit, absorbing all
updates to the store. From time to time these updates are flushed to a file on
disk, where they are compacted (by eliminating redundancies) and compressed
(i.e., written in a compressed format to reduce their storage size).
We aim to speed up data access, and therefore suggest to apply in-memory
memstore flush. That is to flush the active in-memory segment into an
intermediate buffer where it can be accessed by the application. Data in the
buffer is subject to compaction and can be stored in any format that allows it
to take up smaller space in RAM. The less space the buffer consumes the longer
it can reside in memory before data is flushed to disk, resulting in better
performance.
Specifically, the optimization is beneficial for workloads with medium-to-high
key churn which incur many redundant cells, like persistent messaging.
We suggest to structure the solution as 4 subtasks (respectively, patches).
(1) Infrastructure - refactoring of the MemStore hierarchy, introducing segment
(StoreSegment) as first-class citizen, and decoupling memstore scanner from the
memstore implementation;
(2) Adding StoreServices facility at the region level to allow memstores update
region counters and access region level synchronization mechanism;
(3) Implementation of a new memstore (CompactingMemstore) with non-optimized
immutable segment representation, and
(4) Memory optimization including compressed format representation and off heap
allocations.
This Jira continues the discussion in HBASE-13408.
Design documents, evaluation results and previous patches can be found in
HBASE-13408.
was:
A memstore serves as the in-memory component of a store unit, absorbing all
updates to the store. From time to time these updates are flushed to a file on
disk, where they are compacted (by eliminating redundancies) and compressed
(i.e., written in a compressed format to reduce their storage size).
We aim to speed up data access, and therefore suggest to apply in-memory
memstore flush. That is to flush the active in-memory segment into an
intermediate buffer where it can be accessed by the application. Data in the
buffer is subject to compaction and can be stored in any format that allows it
to take up smaller space in RAM. The less space the buffer consumes the longer
it can reside in memory before data is flushed to disk, resulting in better
performance.
Specifically, the optimization is beneficial for workloads with medium-to-high
key churn which incur many redundant cells, like persistent messaging.
We suggest to structure the solution as 3 subtasks (respectively, patches).
(1) Infrastructure - refactoring of the MemStore hierarchy, introducing segment
(StoreSegment) as first-class citizen, and decoupling memstore scanner from the
memstore implementation;
(2) Implementation of a new memstore (CompactingMemstore) with non-optimized
immutable segment representation, and
(3) Memory optimization including compressed format representation and offheap
allocations.
This Jira continues the discussion in HBASE-13408.
Design documents, evaluation results and previous patches can be found in
HBASE-13408.
> In-Memory MemStore Flush and Compaction
> ---------------------------------------
>
> Key: HBASE-14918
> URL: https://issues.apache.org/jira/browse/HBASE-14918
> Project: HBase
> Issue Type: Umbrella
> Affects Versions: 2.0.0
> Reporter: Eshcar Hillel
> Assignee: Eshcar Hillel
>
> A memstore serves as the in-memory component of a store unit, absorbing all
> updates to the store. From time to time these updates are flushed to a file
> on disk, where they are compacted (by eliminating redundancies) and
> compressed (i.e., written in a compressed format to reduce their storage
> size).
> We aim to speed up data access, and therefore suggest to apply in-memory
> memstore flush. That is to flush the active in-memory segment into an
> intermediate buffer where it can be accessed by the application. Data in the
> buffer is subject to compaction and can be stored in any format that allows
> it to take up smaller space in RAM. The less space the buffer consumes the
> longer it can reside in memory before data is flushed to disk, resulting in
> better performance.
> Specifically, the optimization is beneficial for workloads with
> medium-to-high key churn which incur many redundant cells, like persistent
> messaging.
> We suggest to structure the solution as 4 subtasks (respectively, patches).
> (1) Infrastructure - refactoring of the MemStore hierarchy, introducing
> segment (StoreSegment) as first-class citizen, and decoupling memstore
> scanner from the memstore implementation;
> (2) Adding StoreServices facility at the region level to allow memstores
> update region counters and access region level synchronization mechanism;
> (3) Implementation of a new memstore (CompactingMemstore) with non-optimized
> immutable segment representation, and
> (4) Memory optimization including compressed format representation and off
> heap allocations.
> This Jira continues the discussion in HBASE-13408.
> Design documents, evaluation results and previous patches can be found in
> HBASE-13408.
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