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From da...@apache.org
Subject [1/3] beam-site git commit: Update the capability matrix for state and timers
Date Wed, 08 Feb 2017 18:29:02 GMT
Repository: beam-site
Updated Branches:
  refs/heads/asf-site 903fd8288 -> e1dd10a94


Update the capability matrix for state and timers


Project: http://git-wip-us.apache.org/repos/asf/beam-site/repo
Commit: http://git-wip-us.apache.org/repos/asf/beam-site/commit/e347f09f
Tree: http://git-wip-us.apache.org/repos/asf/beam-site/tree/e347f09f
Diff: http://git-wip-us.apache.org/repos/asf/beam-site/diff/e347f09f

Branch: refs/heads/asf-site
Commit: e347f09fe4ff38c03b04434f3e30dd879a8dc9cd
Parents: 903fd82
Author: Kenneth Knowles <klk@google.com>
Authored: Wed Feb 8 07:45:18 2017 -0800
Committer: Kenneth Knowles <klk@google.com>
Committed: Wed Feb 8 07:45:18 2017 -0800

----------------------------------------------------------------------
 src/_data/capability-matrix.yml | 40 +++++++++++++++++-------------------
 1 file changed, 19 insertions(+), 21 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/beam-site/blob/e347f09f/src/_data/capability-matrix.yml
----------------------------------------------------------------------
diff --git a/src/_data/capability-matrix.yml b/src/_data/capability-matrix.yml
index 48d2abd..f2e58ac 100644
--- a/src/_data/capability-matrix.yml
+++ b/src/_data/capability-matrix.yml
@@ -199,26 +199,25 @@ categories:
       - name: Keyed State
         values:
           - class: model
-            jira: BEAM-25
-            l1: 'No'
+            l1: 'Yes'
             l2: storage per key, per window
             l3: Allows fine-grained access to per-key, per-window persistent state. Necessary
for certain use cases (e.g. high-volume windows which store large amounts of data, but typically
only access small portions of it; complex state machines; etc.) that are not easily or efficiently
addressed via <tt>Combine</tt> or <tt>GroupByKey</tt>+<tt>ParDo</tt>.

           - class: dataflow
-            l1: 'No'
-            l2: pending model support
-            l3: Dataflow already supports keyed state internally, so adding support for this
should be easy once the Beam model exposes it.
+            l1: 'Partially'
+            l2: non-merging windows
+            l3: Keyed state is fully supported for non-merging windows.
           - class: flink
-            l1: 'No'
-            l2: pending model support
-            l3: Flink already supports keyed state, so adding support for this should be
easy once the Beam model exposes it.
+            l1: 'Partially'
+            l2: streaming, non-merging windows
+            l3: Keyed state is supported in streaming mode for non-merging windows.
           - class: spark
             l1: 'No'
-            l2: pending model support
+            l2: not implemented
             l3: Spark supports keyed state with mapWithState() so support shuold be straight
forward.
           - class: apex
             l1: 'No'
-            l2: pending model support
-            l3: Apex supports keyed state, so adding support for this should be easy once
the Beam model exposes it.
+            l2: not implemented
+            l3: Apex supports keyed state, so adding support for this should be easy.
 
   - description: Where in event time?
     anchor: where
@@ -563,25 +562,24 @@ categories:
       - name: Timers
         values:
           - class: model
-            jira: BEAM-27
-            l1: 'No'
+            l1: 'Yes'
             l2: delayed processing callbacks
             l3: A fine-grained mechanism for performing work at some point in the future,
in either the event-time or processing-time domain. Useful for orchestrating delayed events,
timeouts, etc in complex state per-key, per-window state machines.
           - class: dataflow
-            l1: 'No'
-            l2: pending model support
-            l3: Dataflow already supports timers internally, so adding support for this should
be easy once the Beam model exposes it.
+            l1: 'Partially'
+            l2: non-merging windows
+            l3: Dataflow supports timers in non-merging windows.
           - class: flink
-            l1: 'No'
-            l2: pending model support
-            l3: Flink already supports timers internally, so adding support for this should
be easy once the Beam model exposes it.
+            l1: 'Partially'
+            l2: streaming, non-merging windows
+            l3: The Flink runner support timers in non-merging windows when run in streaming
mode.
           - class: spark
             l1: 'No'
-            l2: pending model support
+            l2: not implemented
             l3: ''
           - class: apex
             l1: 'No'
-            l2: pending model support
+            l2: not implemented
             l3: ''
 
   - description: How do refinements relate?


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