draft [humble] Add computation of size contribution to info verb (backport #1726) (backport #1872)

[mergify]

Addresses #1601 feature request (Show size contribution of each topic with ros2 bag info). This is a test draft.

Output of ros2 bag info test_bag -v --size-contribution:

Files:             test_bag.mcap
Bag size:          2.6 GiB
Storage id:        mcap
ROS Distro:        unknown
Duration:          39.541s
Start:             Jun 19 2024 23:40:38.345 (1718833238.345)
End:               Jun 19 2024 23:41:17.886 (1718833277.886)
Messages:          2310
Topic information: Topic: /parameter_events | Type: rcl_interfaces/msg/ParameterEvent | Count: 0 | Serialization Format: cdr
                   Topic: /velodyne_points | Type: sensor_msgs/msg/PointCloud2 | Count: 765 | Size Contribution: 557.0 MiB | Serialization Format: cdr
                   Topic: /events/read_split | Type: rosbag2_interfaces/msg/ReadSplitEvent | Count: 0 | Serialization Format: cdr
                   Topic: /image_raw_1 | Type: sensor_msgs/msg/Image | Count: 763 | Size Contribution: 1.0 GiB | Serialization Format: cdr
                   Topic: /image_raw_2 | Type: sensor_msgs/msg/Image | Count: 763 | Size Contribution: 1.0 GiB | Serialization Format: cdr
                   Topic: /events/write_split | Type: rosbag2_interfaces/msg/WriteSplitEvent | Count: 0 | Serialization Format: cdr
                   Topic: /rosout | Type: rcl_interfaces/msg/Log | Count: 19 | Size Contribution: 4.9 KiB | Serialization Format: cdr
Service:           0
Service information:

The total size contribution of each topic is computed by sequentially reading every message in the rosbag. As mentioned in #1601, this approach can be slow.

In a first test A (previous output), the computation of the size contribution took ~520ms for a bag with 2310 messages, 2.6GiB large, 39.5s long, with two sensor_msgs/msg/Image topics with 763 messages each, and one sensor_msgs/msg/PointCloud2 topic with 765 messages.

In a second test B, the size computation took ~78ms for a bag with 14577 messages, 5.2MiB large, 74.4s long, with one sensor_msgs/msg/Imu topic with 14559 messages.

So to me, it seems the computation time is not simply dependent on the number of messages, but on their types and individual sizes too. As a test, I was curious about skipping the message serialization step inside the reader. I tried a brute modification of the mcap_storage interface to directly access the messageView.message.dataSize variable while skipping the message serialization step. However, this only resulted in a 15-30% improvement in computation time.

As a test, removing the actual size computation code and just reading the rosbag in an empty while loop doesn't really change the timing (only real difference was in test B, 78ms->68ms).

In rosbag2_py/_info.cpp, the new function compute_topics_size_contribution can be combined with the existing read_service_info to avoid reading the rosbag twice.

@MichaelOrlov looking forward to your feedback and suggested changes.

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This is an automatic backport of pull request #1726 done by [Mergify](https://mergify.com).

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This is an automatic backport of pull request #1872 done by [Mergify](https://mergify.com).

[mergify]

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	deleted by us:   docs/design/rosbag2_record_replay_service.md
	both modified:   ros2bag/ros2bag/verb/info.py
	both modified:   rosbag2_cpp/include/rosbag2_cpp/info.hpp
	both modified:   rosbag2_cpp/include/rosbag2_cpp/storage_options.hpp
	both modified:   rosbag2_cpp/src/rosbag2_cpp/info.cpp
	deleted by us:   rosbag2_py/rosbag2_py/_info.pyi
	both modified:   rosbag2_py/src/rosbag2_py/_info.cpp
	both modified:   rosbag2_py/src/rosbag2_py/format_bag_metadata.cpp
	both modified:   rosbag2_py/src/rosbag2_py/format_bag_metadata.hpp
	deleted by us:   rosbag2_py/src/rosbag2_py/format_service_info.cpp
	both modified:   rosbag2_tests/test/rosbag2_tests/test_rosbag2_info_end_to_end.cpp

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