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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=336958&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-336958
]
ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------
Author: ASF GitHub Bot
Created on: 31/Oct/19 17:56
Start Date: 31/Oct/19 17:56
Worklog Time Spent: 10m
Work Description: rohdesamuel commented on issue #9954: [BEAM-8335] Add
the PTuple
URL: https://github.com/apache/beam/pull/9954#issuecomment-548496431
> Can you show some examples of how this would be used? Would this be
exposed to users at all? Java has a PCollectionTuple that is used in transforms
like CoGBK, and Flatten. In Python we use a tuple containing PCollections e.g.
`(pcoll1, pcoll2, pcoll3) | Flatten()`.
>
> How would `PTuple` be used?
`PTuple`s will be used like:
```
class SomeCustomTransform(PTransform):
def expand(self, pcoll):
def my_multi_do_fn(x):
if isinstance(x, int):
yield pvalue.TaggedOutput('number', x)
if isinstance(x, str):
yield pvalue.TaggedOutput('string', x)
def printer(x):
print(x)
yield x
outputs = pcoll | beam.ParDo(my_multi_do_fn).with_outputs()
return pvalue.PTuple({
'number': output.number | beam.ParDo(printer),
'string': output.string | beam.ParDo(printer)
})
p = beam.Pipeline()
main = p | SomeCustomTransform()
# Prints out each element that is a number.
numbers = main.number | beam.ParDo(...)
# Prints out each element that is a string.
strings = main.string | beam.ParDo(...)
```
This is a fundamentally different and necessary type than what is available
in the SDK. It allows for referencing an arbitrary amount of PCollections by
name each with a different producer.
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Issue Time Tracking
-------------------
Worklog Id: (was: 336958)
Time Spent: 13h 10m (was: 13h)
> 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: 13h 10m
> 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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