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https://issues.apache.org/jira/browse/HBASE-5416?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zhihong Yu updated HBASE-5416:
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Status: Open (was: Patch Available)
> Improve performance of scans with some kind of filters.
> -------------------------------------------------------
>
> Key: HBASE-5416
> URL: https://issues.apache.org/jira/browse/HBASE-5416
> Project: HBase
> Issue Type: Improvement
> Components: filters, performance, regionserver
> Affects Versions: 0.90.4
> Reporter: Max Lapan
> Assignee: Max Lapan
> Attachments: 5416-v5.txt, Filtered_scans.patch,
> Filtered_scans_v2.patch, Filtered_scans_v3.patch, Filtered_scans_v4.patch
>
>
> When the scan is performed, whole row is loaded into result list, after that
> filter (if exists) is applied to detect that row is needed.
> But when scan is performed on several CFs and filter checks only data from
> the subset of these CFs, data from CFs, not checked by a filter is not needed
> on a filter stage. Only when we decided to include current row. And in such
> case we can significantly reduce amount of IO performed by a scan, by loading
> only values, actually checked by a filter.
> For example, we have two CFs: flags and snap. Flags is quite small (bunch of
> megabytes) and is used to filter large entries from snap. Snap is very large
> (10s of GB) and it is quite costly to scan it. If we needed only rows with
> some flag specified, we use SingleColumnValueFilter to limit result to only
> small subset of region. But current implementation is loading both CFs to
> perform scan, when only small subset is needed.
> Attached patch adds one routine to Filter interface to allow filter to
> specify which CF is needed to it's operation. In HRegion, we separate all
> scanners into two groups: needed for filter and the rest (joined). When new
> row is considered, only needed data is loaded, filter applied, and only if
> filter accepts the row, rest of data is loaded. At our data, this speeds up
> such kind of scans 30-50 times. Also, this gives us the way to better
> normalize the data into separate columns by optimizing the scans performed.
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