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From "Clara Xiong (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-15181) A simple implementation of date based tiered compaction
Date Tue, 02 Feb 2016 23:49:39 GMT

    [ https://issues.apache.org/jira/browse/HBASE-15181?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15129366#comment-15129366
] 

Clara Xiong commented on HBASE-15181:
-------------------------------------

Thank you for your input. I will update the spec. 

We have date tiering like the spotify blog but with  tweaks. The overall theme is tiered store
files based on the max time stamp for their data. If new data comes in perfect order, there
is only one file per window except the incoming window or when they move across tiers. If
there is out-of-order  data/late arrival/bulk loaded data, they will fall into older windows
for compaction selection and may trigger compactions. We allow user to plug in a compaction
policy for this case, default at exploring compaction, to reduce compaction storms. Other
policy can be plugged in if user want to keep file count small by paying the price of re-compaction.

We use max time stamp instead of min as in the spotify blog to reduce performance penalty
for out-of-order data, assuming no timestamp will be set to future time.

TTL works out of box by skipping the whole files.

Major compaction is disabled except pushed manually.

> A simple implementation of date based tiered compaction
> -------------------------------------------------------
>
>                 Key: HBASE-15181
>                 URL: https://issues.apache.org/jira/browse/HBASE-15181
>             Project: HBase
>          Issue Type: New Feature
>          Components: Compaction
>            Reporter: Clara Xiong
>            Assignee: Clara Xiong
>             Fix For: 2.0.0
>
>         Attachments: HBASE-15181-v1.patch, HBASE-15181-v2.patch
>
>
> This is a simple implementation of date-based tiered compaction similar to Cassandra's
for the following benefits:
> 1. Improve date-range-based scan by structuring store files in date-based tiered layout.
> 2. Reduce compaction overhead.
> 3. Improve TTL efficiency.
> Perfect fit for the use cases that:
> 1. has mostly date-based date write and scan and a focus on the most recent data. 
> 2. never or rarely deletes data.
> Out-of-order writes are handled gracefully so the data will still get to the right store
file for time-range-scan and re-compacton with existing store file in the same time window
is handled by ExploringCompactionPolicy.
> Time range overlapping among store files is tolerated and the performance impact is minimized.
> Configuration can be set at hbase-site or overriden at per-table or per-column-famly
level by hbase shell.
> Design spec is at https://docs.google.com/document/d/1_AmlNb2N8Us1xICsTeGDLKIqL6T-oHoRLZ323MG_uy8/edit?usp=sharing



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