Repository: storm
Updated Branches:
  refs/heads/master 7e718862a -> 7e622d178


Quick fix: typo in FAQ.md

Just a typo.

Project: http://git-wip-us.apache.org/repos/asf/storm/repo
Commit: http://git-wip-us.apache.org/repos/asf/storm/commit/44e0e0a4
Tree: http://git-wip-us.apache.org/repos/asf/storm/tree/44e0e0a4
Diff: http://git-wip-us.apache.org/repos/asf/storm/diff/44e0e0a4

Branch: refs/heads/master
Commit: 44e0e0a491d1db23884eb018852e97e7ca9d0a6b
Parents: bfd1006
Author: MichealShin <[email protected]>
Authored: Wed Nov 29 15:22:50 2017 +0800
Committer: GitHub <[email protected]>
Committed: Wed Nov 29 15:22:50 2017 +0800

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 docs/FAQ.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)
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http://git-wip-us.apache.org/repos/asf/storm/blob/44e0e0a4/docs/FAQ.md
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diff --git a/docs/FAQ.md b/docs/FAQ.md
index 127c95c..ce9130e 100644
--- a/docs/FAQ.md
+++ b/docs/FAQ.md
@@ -123,5 +123,5 @@ You cannot know that all events are collected -- this is an 
epistemological chal
 
 * Set a time limit using domain knowledge
 * Introduce a _punctuation_: a record known to come after all records in the 
given time bucket. Trident uses this scheme to know when a batch is complete. 
If you for instance receive records from a set of sensors, each in order for 
that sensor, then once all sensors have sent you a 3:02:xx or later timestamp 
lets you know you can commit. 
-* When possible, make your process incremental: each value that comes in makes 
the answer more an more true. A Trident ReducerAggregator is an operator that 
takes a prior result and a set of new records and returns a new result. This 
lets the result be cached and serialized to a datastore; if a server drops off 
line for a day and then comes back with a full day's worth of data in a rush, 
the old results will be calmly retrieved and updated.
+* When possible, make your process incremental: each value that comes in makes 
the answer more and more true. A Trident ReducerAggregator is an operator that 
takes a prior result and a set of new records and returns a new result. This 
lets the result be cached and serialized to a datastore; if a server drops off 
line for a day and then comes back with a full day's worth of data in a rush, 
the old results will be calmly retrieved and updated.
 * Lambda architecture: Record all events into an archival store (S3, HBase, 
HDFS) on receipt. in the fast layer, once the time window is clear, process the 
bucket to get an actionable answer, and ignore everything older than the time 
window. Periodically run a global aggregation to calculate a "correct" answer.

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