Github user ramkrish86 commented on a diff in the pull request:
https://github.com/apache/phoenix/pull/8#discussion_r16795912
--- Diff:
phoenix-core/src/main/java/org/apache/phoenix/iterate/DefaultParallelIteratorRegionSplitter.java
---
@@ -138,14 +146,10 @@ public boolean apply(HRegionLocation location) {
// split each region in s splits such that:
// s = max(x) where s * x < t
//
- // The idea is to align splits with region boundaries. If rows are
not evenly
- // distributed across regions, using this scheme compensates for
regions that
- // have more rows than others, by applying tighter splits and
therefore spawning
- // off more scans over the overloaded regions.
- int splitsPerRegion = getSplitsPerRegion(regions.size());
// Create a multi-map of ServerName to List<KeyRange> which we'll
use to round robin from to ensure
// that we keep each region server busy for each query.
- ListMultimap<HRegionLocation,KeyRange> keyRangesPerRegion =
ArrayListMultimap.create(regions.size(),regions.size() * splitsPerRegion);;
+ int splitsPerRegion = getSplitsPerRegion(regions.size());
+ ListMultimap<HRegionLocation,KeyRange> keyRangesPerRegion =
ArrayListMultimap.create(regions.size(),regions.size() * splitsPerRegion);
--- End diff --
So inside the CP we actually do a scan of the table's region for which
update stats is issued. So before that create an HTable instance to talk to the
system.stats table and read the column where the last analyzed time is stored
for that table and then proceed with the scan of the region? I am bit skeptical
here of talking with the stats table inside the endpoint call for the table's
region.
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