[ https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=389648&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-389648 ]
ASF GitHub Bot logged work on BEAM-8335: ---------------------------------------- Author: ASF GitHub Bot Created on: 19/Feb/20 21:42 Start Date: 19/Feb/20 21:42 Worklog Time Spent: 10m Work Description: KevinGG commented on pull request #10899: [BEAM-8335] Background Caching job URL: https://github.com/apache/beam/pull/10899#discussion_r381561361 ########## File path: sdks/python/apache_beam/runners/interactive/options/capture_control.py ########## @@ -15,6 +15,16 @@ # limitations under the License. # +"""Module to control how Interactive Beam captures data from sources for +deterministic replayable PCollection evaluation and pipeline runs. + +For internal use only; no backwards-compatibility guarantees. +""" + +# pytype: skip-file Review comment: According to Boyuan and the [PR](https://github.com/apache/beam/commit/7547ac6b273e6e2ffe7d69775606e14c0fd455b2), type checking is still in development, not stable and may cause surprised failures. So it's added to all py files. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org Issue Time Tracking ------------------- Worklog Id: (was: 389648) Time Spent: 63h 40m (was: 63.5h) > 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: 63h 40m > 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 -- This message was sent by Atlassian Jira (v8.3.4#803005)