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ASF GitHub Bot logged work on BEAM-7926: ---------------------------------------- Author: ASF GitHub Bot Created on: 07/Oct/19 20:13 Start Date: 07/Oct/19 20:13 Worklog Time Spent: 10m Work Description: KevinGG commented on pull request #9741: [BEAM-7926] Visualize PCollection URL: https://github.com/apache/beam/pull/9741 1. Added pcoll_visualization module to visualize materialized PCollection data. 2. A visualization mainly consists of 3 parts: facets-dive, facets-overview and data-table. 3. The visualization is always async. It has 2 modes: one-shot and dynamical plotting. 4. One-shot visualization renders the visualization as HTML statically. 5. Dynamical plotting polls materialized data, initializes a visualization and then updates the visualization continuously. 6. It's the pipeline state, i.e., whether the PCollection materialization is being updated that decides if the visualization is dynamical plotting or one-shot. It's not the boundedness of PCollection that decides the visualization mode. However, when engineering for Interactive Beam, it's alright to always use the dynamical plotting mode as long as the InteractiveRunner(s) manages jobs and tracks the pipeline(job) results correctly. Failing to terminate a visualization job might cause resource leak. 7. The materialized PCollection data goes through the following process flow: cache -> element list -> normalization -> dataframe -> HTMLs/scripts. 8. A visualization is always self-contained. Meaning it controls when the visualization starts and ends by itself. Once visualized, the visualization is anchored within the notebook cell's output area. Code in other cells can affect the visualization in the cell but will not change the existing visualization's position in the notebook. Multiple visualize(pcoll) calls will render multiple independent distinct visualization instances/jobs. Each visualization runs in its own thread outside of the notebook main thread. 8. Unittest added focusing on the above visualization logic other than the visualization UI (those should belong to Facets, pandas and jQuery, we'll trust them work as intended). Integration tests can be added later. 9. Each visualization job regularly queries interactive environment for running pipeline(job) results implicitly to determine the default visualization end condition. It's based on the limitation that within current interactive environment, at a time, at most one job is in non-terminated state for an end user defined pipeline instance (in whatever state). The end user could also use the handle returned by visualize() to stop() the visualization job manually. ------------------------ Thank you for your contribution! 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For queries about this service, please contact Infrastructure at: us...@infra.apache.org Issue Time Tracking ------------------- Worklog Id: (was: 324584) Remaining Estimate: 0h Time Spent: 10m > Visualize PCollection with Interactive Beam > ------------------------------------------- > > Key: BEAM-7926 > URL: https://issues.apache.org/jira/browse/BEAM-7926 > Project: Beam > Issue Type: New Feature > Components: runner-py-interactive > Reporter: Ning Kang > Assignee: Ning Kang > Priority: Major > Time Spent: 10m > Remaining Estimate: 0h > > Support auto plotting / charting of materialized data of a given PCollection > with Interactive Beam. > Say an Interactive Beam pipeline defined as > p = create_pipeline() > pcoll = p | 'Transform' >> transform() > The use can call a single function and get auto-magical charting of the data > as materialized pcoll. > e.g., visualize(pcoll) -- This message was sent by Atlassian Jira (v8.3.4#803005)