[
https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=395357&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-395357
]
ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------
Author: ASF GitHub Bot
Created on: 29/Feb/20 01:03
Start Date: 29/Feb/20 01:03
Worklog Time Spent: 10m
Work Description: pabloem commented on pull request #10497: [BEAM-8335]
Add the ReverseTestStream
URL: https://github.com/apache/beam/pull/10497#discussion_r385983264
##########
File path: sdks/python/apache_beam/runners/direct/transform_evaluator.py
##########
@@ -432,6 +439,45 @@ def finish_bundle(self):
self, self.bundles, [], None, {None: self._watermark})
+class PairWithTimingEvaluator(_TransformEvaluator):
+ """TransformEvaluator for the PairWithTiming transform.
+
+ This transform takes an element as an input and outputs
+ KV(element, `TimingInfo`). Where the `TimingInfo` contains both the
+ processing time timestamp and watermark.
+ """
+ def __init__(
+ self,
+ evaluation_context,
+ applied_ptransform,
+ input_committed_bundle,
+ side_inputs):
+ assert not side_inputs
+ super(PairWithTimingEvaluator, self).__init__(
+ evaluation_context,
+ applied_ptransform,
+ input_committed_bundle,
+ side_inputs)
+
+ def start_bundle(self):
+ main_output = list(self._outputs)[0]
+ self.bundle = self._evaluation_context.create_bundle(main_output)
+
+ def process_element(self, element):
+ watermark_manager = self._evaluation_context._watermark_manager
+ watermarks = watermark_manager.get_watermarks(self._applied_ptransform)
Review comment:
For performance, it may be worth considering evaluating watermark and
processing time once, rather than on every element.
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Issue Time Tracking
-------------------
Worklog Id: (was: 395357)
Time Spent: 78h (was: 77h 50m)
> Add streaming support to Interactive Beam
> -----------------------------------------
>
> Key: BEAM-8335
> URL: https://issues.apache.org/jira/browse/BEAM-8335
> Project: Beam
> Issue Type: Improvement
> Components: runner-py-interactive
> Reporter: Sam Rohde
> Assignee: Sam Rohde
> Priority: Major
> Time Spent: 78h
> Remaining Estimate: 0h
>
> This issue tracks the work items to introduce streaming support to the
> Interactive Beam experience. This will allow users to:
> * Write and run a streaming job in IPython
> * Automatically cache records from unbounded sources
> * Add a replay experience that replays all cached records to simulate the
> original pipeline execution
> * Add controls to play/pause/stop/step individual elements from the cached
> records
> * Add ability to inspect/visualize unbounded PCollections
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