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From etha...@apache.org
Subject [storm] branch master updated: [MINOR] Fix broken javadoc link in Concepts (#3270)
Date Mon, 18 May 2020 18:19:41 GMT
This is an automated email from the ASF dual-hosted git repository.

ethanli pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/storm.git


The following commit(s) were added to refs/heads/master by this push:
     new 8e03772  [MINOR] Fix broken javadoc link in Concepts (#3270)
8e03772 is described below

commit 8e037721dfee166bcfc113da662caaa6b11d9b2d
Author: DONGYEON LEE <dev.loustler@gmail.com>
AuthorDate: Tue May 19 03:19:30 2020 +0900

    [MINOR] Fix broken javadoc link in Concepts (#3270)
---
 docs/Concepts.md | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/docs/Concepts.md b/docs/Concepts.md
index f810d36..fd8fa88 100644
--- a/docs/Concepts.md
+++ b/docs/Concepts.md
@@ -55,9 +55,9 @@ The other main methods on spouts are `ack` and `fail`. These are called
when Sto
 
 ### Bolts
 
-All processing in topologies is done in bolts. Bolts can do anything from filtering, functions,
aggregations, joins, talking to databases, and more. 
+All processing in topologies is done in bolts. Bolts can do anything from filtering, functions,
aggregations, joins, talking to databases, and more.
 
-Bolts can do simple stream transformations. Doing complex stream transformations often requires
multiple steps and thus multiple bolts. For example, transforming a stream of tweets into
a stream of trending images requires at least two steps: a bolt to do a rolling count of retweets
for each image, and one or more bolts to stream out the top X images (you can do this particular
stream transformation in a more scalable way with three bolts than with two). 
+Bolts can do simple stream transformations. Doing complex stream transformations often requires
multiple steps and thus multiple bolts. For example, transforming a stream of tweets into
a stream of trending images requires at least two steps: a bolt to do a rolling count of retweets
for each image, and one or more bolts to stream out the top X images (you can do this particular
stream transformation in a more scalable way with three bolts than with two).
 
 Bolts can emit more than one stream. To do so, declare multiple streams using the `declareStream`
method of [OutputFieldsDeclarer](javadocs/org/apache/storm/topology/OutputFieldsDeclarer.html)
and specify the stream to emit to when using the `emit` method on [OutputCollector](javadocs/org/apache/storm/task/OutputCollector.html).
 
@@ -86,7 +86,7 @@ There are eight built-in stream groupings in Storm, and you can implement
a cust
 4. **All grouping**: The stream is replicated across all the bolt's tasks. Use this grouping
with care.
 5. **Global grouping**: The entire stream goes to a single one of the bolt's tasks. Specifically,
it goes to the task with the lowest id.
 6. **None grouping**: This grouping specifies that you don't care how the stream is grouped.
Currently, none groupings are equivalent to shuffle groupings. Eventually though, Storm will
push down bolts with none groupings to execute in the same thread as the bolt or spout they
subscribe from (when possible).
-7. **Direct grouping**: This is a special kind of grouping. A stream grouped this way means
that the __producer__ of the tuple decides which task of the consumer will receive this tuple.
Direct groupings can only be declared on streams that have been declared as direct streams.
Tuples emitted to a direct stream must be emitted using one of the [emitDirect](javadocs/org/apache/storm/task/OutputCollector.html#emitDirect(int,
int, java.util.List) methods. A bolt can get the task ids of its  [...]
+7. **Direct grouping**: This is a special kind of grouping. A stream grouped this way means
that the __producer__ of the tuple decides which task of the consumer will receive this tuple.
Direct groupings can only be declared on streams that have been declared as direct streams.
Tuples emitted to a direct stream must be emitted using one of the [emitDirect](javadocs/org/apache/storm/task/OutputCollector.html#emitDirect-int-java.util.Collection-java.util.List-)
methods. A bolt can get the  [...]
 8. **Local or shuffle grouping**: If the target bolt has one or more tasks in the same worker
process, tuples will be shuffled to just those in-process tasks. Otherwise, this acts like
a normal shuffle grouping.
 
 **Resources:**
@@ -96,11 +96,11 @@ There are eight built-in stream groupings in Storm, and you can implement
a cust
 
 ### Reliability
 
-Storm guarantees that every spout tuple will be fully processed by the topology. It does
this by tracking the tree of tuples triggered by every spout tuple and determining when that
tree of tuples has been successfully completed. Every topology has a "message timeout" associated
with it. If Storm fails to detect that a spout tuple has been completed within that timeout,
then it fails the tuple and replays it later. 
+Storm guarantees that every spout tuple will be fully processed by the topology. It does
this by tracking the tree of tuples triggered by every spout tuple and determining when that
tree of tuples has been successfully completed. Every topology has a "message timeout" associated
with it. If Storm fails to detect that a spout tuple has been completed within that timeout,
then it fails the tuple and replays it later.
 
 To take advantage of Storm's reliability capabilities, you must tell Storm when new edges
in a tuple tree are being created and tell Storm whenever you've finished processing an individual
tuple. These are done using the [OutputCollector](javadocs/org/apache/storm/task/OutputCollector.html)
object that bolts use to emit tuples. Anchoring is done in the `emit` method, and you declare
that you're finished with a tuple using the `ack` method.
 
-This is all explained in much more detail in [Guaranteeing message processing](Guaranteeing-message-processing.html).

+This is all explained in much more detail in [Guaranteeing message processing](Guaranteeing-message-processing.html).
 
 ### Tasks
 


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