mapel | A dead-simple image-rendering DSL

I don't think it's possible to do "out-of-box" with a current implementation of of XmlIO since it returns a PCollection where T is a type of your xml record and, if I'm not mistaken, there is no way to add a file name there. Though, you still can try to "reimplement" a ReadFiles and XmlSource in a way that it will return parsed payload and input file metadata.

Yes, this is a very normal performance factor between Python and Java. In fact, for many programs the factor can be 10x or much more.

The details of the program can radically change the relative performance. Here are some things to consider:

• Profiling the Dataflow job (official docs)
• Profiling a Dataflow pipeline (medium blog)
• Profiling Apache Beam Python pipelines (another medium blog)
• Profiling Python (general Cloud Profiler docs)
• How can I profile a Python Dataflow job? (previous StackOverflow question on profiling Python job)

If you prefer Python for its concise syntax or library ecosystem, the approach to achieve speed is to use optimized C libraries or Cython for the core processing, for example using pandas/numpy/etc. If you use Beam's new Pandas-compatible dataframe API you will automatically get this benefit.

This is easy. I found a Stack Overflow question related to Leaflet usage in LitElement.

My answer is similar as this, but need to do some changes, because I am creating a web component (widget).

Sorry for not directly responding to your described error, but I would not use esri-loader with newer versions of ArcGIS for JavaScript API. Why not npm as ES modules which do not require a separate script loader?

Build with ES Module

This way you can do simple imports like this:

import WebMap from "@arcgis/core/WebMap";

Here are the initial setup instructions:

Install instructions

Finally, here is a sample react app from Esri using exactly that:

Esri React App example

You can use the trigger “Window.ClosingBehavior”. You need to specify under which conditions a final pane will be created when a window is permanently closed. You can use these options:

• FIRE_ALWAYS: Always Fire the last Pane.

• FIRE_IF_NON_EMPTY: Only Fire the last pane if there is new data since previous firing.

You can see this example.

JdbcIO.read() just creates a reading PTransform, it does not actually do any reading. To do the read, it must be applied to the pipeline object (as you have in your first example) which produces a PCollection of records. PTransforms are not meant to be used within a DoFn, DoFns act on individual elements, not PCollections of elements.

If you are trying to remove anonomous classes, you could write your code as follows

While the error message seems to imply that the list of strings is what needs encoding, it is actually the JsonNode. I just had to read a little further down in the error message, as the opening statement is a bit deceiving as to where the issue is:

Currently this cannot be done in the same pipeline with BigQueryIO.writeTableRows() since it produces a terminal output (PDone). I have some suggestions though.

• I suspect BigQuery write failing is a rare occurrence. In this case can you delete corresponding Datastore data from a secondary job/process.
• Have you considered a CDC solution that is better suited for writing incremental change data. For example see the Dataflow template here.

Taking a deeper look in the beam code, I found that the Session windows are MergingWindow and state cannot be maintained across merged windows, hence I faced the mentioned exception.

Later, I implemented the use case using GlobalWindows and State + Timer.

Timer is used to reset the counter if no new messages for same session_id for 2 mins.

Ref: https://beam.apache.org/blog/timely-processing