518 lines
24 KiB
Markdown
518 lines
24 KiB
Markdown
# ROS 2 tracing
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Design document for ROS 2 tracing, instrumentation, and analysis effort.
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## Introduction
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Tracing allows to record run-time data from a system, both for system data (e.g., when a process
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is being scheduled, or when I/O occurs) and for user-defined data. This package helps with
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user-defined trace data within the ROS 2 framework, e.g. to trace when messages arrive,
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when timers fire, when callbacks are being run, etc.
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## Goals and requirements
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### Goals
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1. Provide low-overhead tools and resources for robotics software development based on ROS 2.
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2. Make tracing easier to use with ROS.
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### Requirements: instrumentation
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Instrumentation should be built around the main uses of ROS 2, and should include relevant information:
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1. Overall
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1. When creating a publisher/subscriber/service/client/etc., appropriate references should be kept in order to correlate with other tracepoints related to the same instance.
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1. Publishers & subscriptions
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1. When creating a publisher/subscription, the effective topic name should be included (i.e. including namespace and after remapping).
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2. When publishing a message, some sort of message identifier should be included in the tracepoint so it can be tracked through DDS up to the subscriber's side.
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3. Callbacks (subscription, service, client, timer)
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1. Callback function symbol should be included, whenever possible.
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2. Information about callback execution (e.g. start & end) should be available.
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4. Timers
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1. Information about the period should be available.
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5. Executors
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1. Information about spin cycles & periods should be available.
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6. Others
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1. Provide generic tracepoints for user code.
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### Requirements: analysis & visualization
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Analyses process trace data. They should be general enough to be useful for different use-cases, e.g.:
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* Callback duration
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* Time between callbacks (between two callback starts and/or a callback end and a start)
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* Message age (as the difference between processing time and message timestamp)
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* Message size
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* Memory usage
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* Execution time/proportion accross a process' nodes/components
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* Interruptions (noting that these may be more useful as time-based metrics instead of overall statistics):
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* scheduling events during a callback
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* delay between the moment a thread becomes ready and when it's actually scheduled
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* CPU cycles
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with mean, stdev, etc. when applicable.
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Generic tracepoints for ROS 2 user code could be applied to a user-provided model for higher-level behaviour statistics and visualization.
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### Tools/accessibility
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To make tracing ROS 2 more accessible and easier to adopt, we can put effort into integrating LTTng session setup & recording into the ROS 2 launch system.
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This might include converting existing `tracetools` scripts to more flexible Python scripts, and then plugging that into the launch system.
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## Instrumentation design
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This section includes information about ROS 2's design & architecture through descriptions of the main execution flows. The instrumentation can then be built around that.
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### Flow description
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#### Process creation
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In the call to `rclcpp::init()`, a process-specific `rclcpp::Context` object is fetched and CLI arguments are parsed. Much of the work is actually done by `rcl` through a call to `rcl_init()`. This call processes the `rcl_context_t` handle, which is wrapped by the `Context` object. Also, inside this call, `rcl` calls `rmw_init()` to process the `rmw` context (`rmw_context_t`) as well. This `rmw` handle is itself part of the `rcl_context_t` handle.
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This has to be done once per process, and usually at the very beginning. The components that are then instanciated share this context.
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```mermaid
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sequenceDiagram
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participant process
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participant rclcpp
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participant Context
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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process->>rclcpp: rclcpp::init(argc, argv)
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Note over rclcpp: fetches process-specific Context object
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rclcpp->>Context: init(argc, argv)
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Note over Context: allocates rcl_context_t handle
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Context->>rcl: rcl_init(out rcl_context_t)
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Note over rcl: validates & processes rcl_context_t handle
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rcl->>rmw: rmw_init(out rmw_context_t)
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Note over rmw: validates & processes rmw_context_t handle
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rcl-->>tracetools: TP(rcl_init, rcl_context_t *)
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```
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#### Node/component creation
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In ROS 2, a process can contain multiple nodes. These are sometimes referred to as "components."
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These components are instanciated by the containing process. They are usually classes that extend `rclcpp::Node`, so that the node initialization work is done by the parent constructor.
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This parent constructor will allocate its own `rcl_node_t` handle and call `rcl_node_init()`, which will validate the node name/namespace. `rcl` will also call `rmw_create_node()` to get the node's `rmw` handle (`rmw_node_t`). This will be used later by publishers and subscriptions.
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```mermaid
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sequenceDiagram
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participant process
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participant Component
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participant rclcpp
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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process->>Component: Component()
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Component->>rclcpp: : Node(node_name, namespace)
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Note over rclcpp: allocates rcl_node_t handle
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rclcpp->>rcl: rcl_node_init(out rcl_node_t, node_name, namespace)
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Note over rcl: validates node name/namespace
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Note over rcl: populates rcl_note_t
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rcl->>rmw: rmw_create_node(node_name, local_namespace) : rmw_node_t
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Note over rmw: creates rmw_node_t handle
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rcl-->>tracetools: TP(rcl_node_init, rcl_node_t *, rmw_node_t *, node_name, namespace)
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```
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#### Publisher creation
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The component calls `create_publisher()`, a `rclcpp::Node` method for convenience. That ends up creating an `rclcpp::Publisher` object which extends `rclcpp::PublisherBase`. The latter allocates an `rcl_publisher_t` handle, fetches the corresponding `rcl_node_t` handle, and calls `rcl_publisher_init()` in its constructor. `rcl` does topic name expansion/remapping/validation. It creates an `rmw_publisher_t` handle by calling `rmw_create_publisher()` of the given `rmw` implementation and associates with the node's `rmw_node_t` handle and the publisher's `rcl_publisher_t` handle.
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If intra-process publishing/subscription is enabled, it will be set up after creating the publisher object, through a call to `PublisherBase::setup_intra_process()`, which calls `rcl_publisher_init()`.
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```mermaid
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sequenceDiagram
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participant Component
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participant rclcpp
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participant Publisher
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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Component->>rclcpp: create_publisher(topic_name, options, use_intra_process)
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Note over rclcpp: (...)
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rclcpp->>Publisher: Publisher(topic_name, options)
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Note over Publisher: allocates rcl_publisher_t handle
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Publisher->>rcl: rcl_publisher_init(out rcl_publisher_t, rcl_node_t, topic_name, options)
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Note over rcl: populates rcl_publisher_t
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rcl->>rmw: rmw_create_publisher(rmw_node_t, topic_name, qos_options) : rmw_publisher_t
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Note over rmw: creates rmw_publisher_t handle
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rcl-->>tracetools: TP(rcl_publisher_init, rcl_node_t *, rcl_publisher_t *, rmw_publisher_t *, topic_name, depth)
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opt use_intra_process
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rclcpp->>Publisher: setup_intra_process()
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Publisher->>rcl: rcl_publisher_init(...)
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end
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```
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#### Subscription creation
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Subscription creation is done in a very similar manner.
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The componenent calls `create_publisher()`, which ends up creating an `rclcpp::Subscription` object which extends `rclcpp::SubscriptionBase`. The latter allocates an `rcl_subscription_t` handle, fetches its `rcl_node_t` handle, and calls `rcl_subscription_init()` in its constructor. `rcl` does topic name expansion/remapping/validation. It creates an `rmw_subscription_t` handle by calling `rmw_create_subscription()` of the given `rmw` implementation and associates it with the node's `rmw_node_t` handle and the subscription's `rcl_subscription_t` handle.
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If intra-process publishing/subscription is enabled, it will be set up after creating the subscription object, through a call to `Subscription::setup_intra_process()`, which calls `rcl_subscription_init()`. This is very similar to a normal (inter-process) subscription, but it sets some flags for later.
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```mermaid
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sequenceDiagram
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participant Component
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participant rclcpp
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participant Subscription
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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Component->>rclcpp: create_subscription(topic_name, callback, options, use_intra_process)
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Note over rclcpp: (...)
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rclcpp->>Subscription: Subscription(topic_name, callback, options)
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Note over Subscription: allocates rcl_subscription_t handle
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Subscription->>rcl: rcl_subscription_init(out rcl_subscription_t, rcl_node_t, topic_name, options)
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Note over rcl: populates rcl_subscription_t
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rcl->>rmw: rmw_create_subscription(rmw_node_t, topic_name, qos_options) : rmw_subscription_t
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Note over rmw: creates rmw_subscription_t handle
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rcl-->>tracetools: TP(rcl_subscription_init, rcl_node_t *, rcl_subscription_t *, rmw_subscription_t *, topic_name, depth)
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opt use_intra_process
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rclcpp->>Subscription: setup_intra_process()
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Subscription->>rcl: rcl_subscription_init(...)
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end
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rclcpp-->>tracetools: TP(rclcpp_subscription_callback_added, rcl_subscription_t *, &any_callback)
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```
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#### Executors
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An `rclcpp::executor::Executor` object is created for a given process. It can be a `SingleThreadedExecutor` or a `MultiThreadedExecutor`.
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Components are instanciated, usually as a `shared_ptr` through `std::make_shared<Component>()`, then added to the executor with `Executor::add_node()`.
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After all the components have been added, `Executor::spin()` is called. `SingleThreadedExecutor::spin()` simply loops forever until the process' context isn't valid anymore. It fetches the next `rclcpp::AnyExecutable` (e.g. subscription, timer, service, client), and calls `Executor::execute_any_executable()` with it. This then calls the relevant `execute*()` method (e.g. `execute_timer()`, `execute_subscription()`, `execute_intra_process_subscription()`, `execute_service()`, `execute_client()`).
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```mermaid
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sequenceDiagram
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participant process
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participant Executor
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participant tracetools
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process->>Executor: Executor()
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Note over process: instanciates components
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process->>Executor: add_node(component)
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process->>Executor: spin()
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loop until shutdown
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Executor-->>tracetools: TP(?)
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Note over Executor: get_next_executable()
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Note over Executor: execute_any_executable()
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Note over Executor: execute_*()
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end
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```
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#### Subscription callbacks
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Subscriptions are handled in the `rclcpp` layer. Callbacks are wrapped by an `rclcpp::AnySubscriptionCallback` object, which is registered when creating the `rclcpp::Subscription` object.
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In `execute_*subscription()`, the `Executor` asks the `Subscription` to allocate a message though `Subscription::create_message()`. It then calls `rcl_take*()`, which calls `rmw_take_with_info()`. If that is successful, the `Executor` then passes that on to the subscription through `rclcpp::SubscriptionBase::handle_message()`. This checks if it's the right type of subscription (i.e. inter vs. intra process), then it calls `dispatch()` on the `rclcpp::AnySubscriptionCallback` object with the message (cast to the actual type). This calls the actual `std::function` with the right signature.
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Finally, it returns the message object through `Subscription::return_message()`.
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```mermaid
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sequenceDiagram
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participant Executor
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participant Subscription
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participant AnySubscriptionCallback
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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Note over Executor: execute_subscription()
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Executor->>Subscription: create_message(): std::shared_ptr<void>
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Executor->>rcl: rcl_take*(rcl_subscription_t, out msg) : ret
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rcl->>rmw: rmw_take_with_info(rmw_subscription_t, out msg, out taken)
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Note over rmw: copies available message to msg if there is one
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opt RCL_RET_OK == ret
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Executor->>Subscription: handle_message(msg)
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Note over Subscription: casts msg to its actual type
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Subscription->>AnySubscriptionCallback: dispatch(typed_msg)
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AnySubscriptionCallback-->>tracetools: TP(callback_start, this, is_intra_process)
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Note over AnySubscriptionCallback: std::function(...)
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AnySubscriptionCallback-->>tracetools: TP(callback_end, this)
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end
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Executor->>Subscription: return_message(msg)
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```
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#### Message publishing
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To publish a message, an object is first allocated and then populated by the `Component` (or equivalent). Then, the message is sent to the `Publisher` through `publish()`. This then passes that on to `rcl`, which itself passes it to `rmw`.
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TODO add inter- vs. intra-process execution flow
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TODO talk about IntraProcessManager stuff?
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```mermaid
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sequenceDiagram
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participant Component
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participant Publisher
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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Note over Component: creates a msg
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Component->>Publisher: publish(msg)
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Note over Publisher: ...
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Publisher->>rcl: rcl_publish(rcl_publisher_t, msg)
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rcl->>rmw: rmw_publish(rmw_publisher_t, msg)
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rmw-->>tracetools: TP(?)
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```
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#### Service creation
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Service server creation is similar to subscription creation. The `Component` calls `create_service()` which ends up creating a `rclcpp::Service`. In its constructor, it allocates a `rcl_service_t` handle, then calls `rcl_service_init()`. This processes the handle and validates the service name. It calls `rmw_create_service()` to get the corresponding `rmw_service_t` handle.
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```mermaid
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sequenceDiagram
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participant Component
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participant rclcpp
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participant Service
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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Component->>rclcpp: create_service(service_name, callback)
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Note over rclcpp: (...)
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rclcpp->>Service: Service(rcl_node_t, service_name, callback, options)
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Note over Service: allocates a rcl_service_t handle
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Service->>rcl: rcl_service_init(out rcl_service_t, rcl_node_t, service_name, options)
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Note over rcl: validates & processes service handle
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rcl->>rmw: rmw_create_service(rmw_node_t, service_name, qos_options) : rmw_service_t
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Note over rmw: creates rmw_service_t handle
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rcl-->>tracetools: TP(rcl_service_init, rcl_node_t *, rcl_service_t *, rmw_service_t *, service_name)
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Service-->>tracetools: TP(rclcpp_service_callback_added, rcl_service_t *, &any_callback)
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```
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#### Service callbacks
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Service callbacks are similar to subscription callbacks. In `execute_service()`, the `Executor` allocates request header and request objects. It then calls `rcl_take_request()` and passes them along with the service handle.
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`rcl` calls `rmw_take_request()`. If those are successful, then the `Executor` calls `handle_request()` on the `Service`. This casts the request to its actual type, allocates a response object, and calls `dispatch()` on its `AnyServiceCallback` object, which calls the actual `std::function` with the right signature.
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For the service response, `Service` calls `rcl_send_response()` which calls `rmw_send_response()`.
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```mermaid
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sequenceDiagram
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participant Executor
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participant Service
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participant AnyServiceCallback
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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Note over Executor: execute_service()
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Note over Executor: allocates request header and request
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Executor->>rcl: rcl_take_request(rcl_service, out request_header, out request) : ret
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rcl->>rmw: rmw_take_request(rmw_service_t, out request_header, out request, out taken)
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opt RCL_RET_OK == ret
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Executor->>Service: handle_request(request_header, request)
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Note over Service: casts request to its actual type
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Note over Service: allocates a response object
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Service->>AnyServiceCallback: dispatch(request_header, typed_request, response)
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AnyServiceCallback-->>tracetools: TP(callback_start, this)
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Note over AnyServiceCallback: std::function(...)
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AnyServiceCallback-->>tracetools: TP(callback_end, this)
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Service->>rcl: rcl_send_response(rcl_service_t, request_header, response)
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rcl->>rmw: rmw_send_response(rmw_service_t, request_header, response)
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end
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```
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#### Client creation
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Client creation is similar to publisher creation. The `Component` calls `create_client()` which ends up creating a `rclcpp::Client`. In its constructor, it allocates a `rcl_client_t` handle, then calls `rcl_client_init()`. This validates and processes the handle. It also calls `rmw_create_client()` which creates the `rmw_client_t` handle.
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```mermaid
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sequenceDiagram
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participant Component
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participant Node
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participant Client
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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Component->>Node: create_client(service_name, options)
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Node->>Client: Client(service_name, options)
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Note over Client: allocates a rcl_client_t handle
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Client->>rcl: rcl_client_init(out rcl_client_t, rcl_node_t, service_name, options)
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Note over rcl: validates and processes rcl_client_t handle
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rcl->>rmw: rmw_create_client(rmw_node_t, service_name, qos_options) : rmw_client_t
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Note over rmw: creates rmw_client_t handle
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rcl-->>tracetools: TP(rcl_client_init, rcl_node_t *, rcl_client_t *, rmw_client_t *, service_name)
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```
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#### Client request
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A client request has multiple steps. The `Component` (or the owner of the `Client`) first creates a request object. It then calls `Client::async_send_request()` with the request. It can also provide a callback, but it's optional. The `Client` passes that on to `rcl` by calling `rcl_send_request()`. `rcl` generates a sequence number and assigns it to the request, then calls `rmw_send_request()`. Once this is done, the `Client` puts this sequence number in an internal map along with the created promise and future objects, and the callback (which might simply be empty).
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At this point, the `Client` could simply let its callback be called. It can also use the future object returned by `async_send_request()`, and call `rclcpp::spin_until_future_complete()`. This waits until the future object is ready, or until timeout, and returns.
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If this last call was successful, then the `Component` can get the result and do something with it.
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```mermaid
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sequenceDiagram
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participant Component
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participant Executor
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participant Client
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participant rclcpp
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participant rcl
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participant rmw
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participant tracetools
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Note over rmw: (implementation)
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Note over Component: creates request
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Component->>Client: async_send_request(request[, callback]) : result_future
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Client->>rcl: rcl_send_request(rcl_client_t, request, out sequence_number)
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Note over rcl: assigns sequence_number
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rcl-->>tracetools: TP?(rcl_send_request, rcl_client_t *, sequence_number)
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rcl->>rmw: rmw_send_request(rmw_client_t, request, sequence_number)
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Note over Client: puts sequence_number in a map with promise+callback+future
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Component->>rclcpp: spin_until_future_complete(result_future) : result_status
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Note over Executor: execute_client()
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Note over Executor: creates request_header and response objects
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Executor->>rcl: rcl_take_response(rcl_client_t, out request_header, out response) : ret
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rcl-->>tracetools: TP?()
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rcl->>rmw: rmw_take_response(rmw_client_t, out request_header, out response, out taken)
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opt RCL_RET_OK == ret
|
|
Executor->>Client: handle_response(request_header, response)
|
|
Note over Client: gets sequence_number from request_header
|
|
Client-->>tracetools: TP?()
|
|
Note over Client: gets promise+callback+future from its map
|
|
Note over Client: callback(future)
|
|
end
|
|
|
|
rclcpp->>Component: ready or timeout
|
|
opt SUCCESS == result_status
|
|
Note over Component: result_future.get() : result
|
|
Note over Component: do something with result
|
|
end
|
|
```
|
|
|
|
#### Timer creation
|
|
|
|
Timer creation is similar to subscription creation. The `Component` calls `create_service()` which ends up creating a `rclcpp::WallTimer`. In its constructor, it creates a `rclcpp::Clock` object, which (for a `WallTimer`) is simply a nanosecond clock. It then allocates a `rcl_timer_t` handle, then calls `rcl_timer_init()`. This processes the handle and validates the period.
|
|
|
|
Note that `rcl_timer_init()` can take a callback as a parameter, but right now that feature is not used anywhere (`nullptr` is given), and callbacks are instead handled in the `rclcpp` layer.
|
|
|
|
```mermaid
|
|
sequenceDiagram
|
|
participant Component
|
|
participant Node
|
|
participant WallTimer
|
|
participant rcl
|
|
participant tracetools
|
|
|
|
Component->>Node: create_wall_timer(period, callback)
|
|
Node->>WallTimer: WallTimer(period, callback, Context)
|
|
Note over WallTimer: creates a Clock object
|
|
Note over WallTimer: allocates a rcl_timer_t handle
|
|
WallTimer->>rcl: rcl_timer_init(out rcl_timer_t, Clock, rcl_context_t, period)
|
|
Note over rcl: validates and processes rcl_timer_t handle
|
|
rcl-->>tracetools: TP(rcl_timer_init, rcl_timer_t *, period)
|
|
WallTimer-->>tracetools: TP(rclcpp_timer_callback_added, rcl_timer_t *, &callback)
|
|
```
|
|
|
|
#### Timer callbacks
|
|
|
|
Timer callbacks are similar to susbcription callbacks. In `execute_timer()`, the `Executor` calls `execute_callback()` on the `WallTimer`. The timer then calls `rcl_timer_call()` with its `rcl_timer_t` handle and checks if the callback should be called.
|
|
|
|
If it that is the case, then the timer will call the actual `std::function`. Depending on the `std::function` that was given when creating the timer, it will either call the callback without any parameters or it will pass a reference of itself.
|
|
|
|
```mermaid
|
|
sequenceDiagram
|
|
participant Executor
|
|
participant WallTimer
|
|
participant rcl
|
|
participant tracetools
|
|
|
|
Note over Executor: execute_timer()
|
|
Executor->>WallTimer: execute_callback()
|
|
WallTimer->>rcl: rcl_timer_call(rcl_timer_t) : ret
|
|
Note over rcl: validates and updates timer
|
|
opt RCL_RET_TIMER_CANCELED != ret && RCL_RET_OK == ret
|
|
WallTimer-->>tracetools: TP(callback_start, &callback)
|
|
Note over WallTimer: std::function(...)
|
|
WallTimer-->>tracetools: TP(callback_end, &callback)
|
|
end
|
|
```
|
|
|
|
## Design & implementation notes
|
|
|
|
### Targeted tools/dependencies
|
|
|
|
The targeted tools or dependencies are:
|
|
|
|
* LTTng for tracing
|
|
* pandas and Jupyter for analysis & visualization
|
|
|
|
### Design
|
|
|
|
The plan is to use LTTng with a ROS wrapper package like `tracetools` for ROS 1. The suggested setup is:
|
|
|
|
* a tracing package (e.g. `tracetools`) wraps calls to LTTng
|
|
* ROS 2 is instrumented with calls to the tracing package, therefore it becomes a dependency and ships with the core stack
|
|
* by default, the tracing package's functions are empty -- they do not do anything
|
|
* if users wants to enable tracing, they need to
|
|
* install LTTng
|
|
* compile the tracing package from source, setting the right compile flag(s)
|
|
* overlay it on top of their ROS 2 installation
|
|
* use other package(s) for analysis and visualization
|
|
|
|
## Architecture
|
|
|
|
|
|
|
|
### Timeline
|
|
|
|
The first goal is to statically instrument ROS 2, aiming for it to be in the ROS 2 E-turtle release (Nov 2019).
|
|
|
|
This includes transposing the existing ROS 1 instrumentation to ROS 2, wherever applicable. This step may not include instrumenting DDS implementations, and thus may be limited to the layer(s) right before `rmw`.
|
|
|
|
### Notes on client libraries
|
|
|
|
ROS offer a client library (`rcl`) written in C as the base for any language-specific implementation, such as `rclcpp` and `rclpy`.
|
|
|
|
However, `rcl` is obviously fairly basic, and still does leave a fair amount of implementation work up to the client libraries. For example, callbacks are not handled in `rcl`, and are left to the client library implementations.
|
|
|
|
This means that some instrumentation work will have to be re-done for every client library that we want to trace. We cannot simply instrument `rcl`, nor can we only instrument the base `rmw` interface if we want to dig into that.
|
|
|
|
This effort should first focus on `rcl` and `rclcpp` , but `rclpy` should eventually be added and supported.
|
|
|
|
### ROS 1/2 compatibility
|
|
|
|
We could look into making analyses work on both ROS 1 and ROS 2, through a common instrumentation interface (or other abstraction).
|