carbon_core/pipeline.rs
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//! Defines the `Pipeline` struct and related components for processing blockchain data updates.
//!
//! The `Pipeline` module is central to the `carbon-core` framework, offering a flexible and extensible
//! data processing architecture that supports various blockchain data types, including account updates,
//! transaction details, and account deletions. The pipeline integrates multiple data sources and
//! processing pipes to handle and transform incoming data, while recording performance metrics for
//! monitoring and analysis.
//!
//! # Overview
//!
//! This module provides the `Pipeline` struct, which orchestrates data flow from multiple sources,
//! processes it through designated pipes, and captures metrics at each stage. The pipeline is highly
//! customizable and can be configured with various components to suit specific data handling requirements.
//!
//! ## Key Components
//!
//! - **Datasources**: Provide raw data updates, which may include account or transaction details.
//! - **Account, Instruction, and Transaction Pipes**: Modular units that decode and process specific
//! types of data. Account pipes handle account updates, instruction pipes process instructions
//! within transactions, and transaction pipes manage complete transaction records.
//! - **Metrics**: Collects data on pipeline performance, such as processing times and error rates,
//! providing insights into operational efficiency.
//!
//! # Fields and Configuration
//!
//! - **datasources**: A list of `Datasource` objects that act as the sources for account and transaction data.
//! - **account_pipes**: A collection of pipes for processing account updates.
//! - **account_deletion_pipes**: Pipes responsible for handling account deletion events.
//! - **instruction_pipes**: Used to process instructions within transactions.
//! - **transaction_pipes**: For handling full transactions.
//! - **metrics**: A vector of `Metrics` implementations that gather and report on performance data.
//! - **metrics_flush_interval**: Specifies how frequently metrics are flushed. Defaults to 5 seconds if unset.
//!
//! ## Notes
//!
//! - Each pipe and data source must implement the appropriate traits (`Datasource`, `AccountPipes`, `Metrics`, etc.).
//! - The `Pipeline` is designed for concurrent operation, with `Arc` and `Box` wrappers ensuring safe, shared access.
//! - Proper metric collection and flushing are essential for monitoring pipeline performance, especially in production environments.
use crate::{
account::{AccountDecoder, AccountMetadata, AccountPipe, AccountPipes, DecodedAccount},
account_deletion::{AccountDeletionPipe, AccountDeletionPipes},
collection::InstructionDecoderCollection,
datasource::{AccountDeletion, Datasource, Update, UpdateType},
error::{CarbonResult, Error},
instruction::{
DecodedInstruction, InstructionDecoder, InstructionMetadata, InstructionPipe,
InstructionPipes, NestedInstruction,
},
metrics::{Metrics, MetricsCollection},
processor::Processor,
schema::TransactionSchema,
transaction::{TransactionPipe, TransactionPipes},
transformers,
};
use core::time;
use serde::de::DeserializeOwned;
use std::{sync::Arc, time::Instant};
use tokio_util::sync::CancellationToken;
/// Defines the shutdown behavior for the pipeline.
///
/// `ShutdownStrategy` determines how the pipeline will behave when it receives a shutdown signal.
/// It supports two modes:
///
/// - `Immediate`: Stops the entire pipeline, including all tasks, instantly.
/// - `ProcessPending`: Terminates the data sources, then completes processing of any updates
/// currently pending in the pipeline. This is the default behavior.
///
/// # Variants
///
/// - `Immediate`: Immediately stops all pipeline activity without processing any remaining updates.
/// - `ProcessPending`: Gracefully terminates the data sources and allows the pipeline to finish
/// processing updates that are still in progress or queued.
///
/// # Notes
///
/// - `ProcessPending` is the default variant, enabling the pipeline to ensure that no updates
/// are lost during shutdown.
///
#[derive(Default, PartialEq, Debug)]
pub enum ShutdownStrategy {
/// Stop the whole pipeline immediately.
Immediate,
/// Terminate the datasource(s) and finish processing all pending updates.
#[default]
ProcessPending,
}
/// Represents the primary data processing pipeline in the `carbon-core` framework.
///
/// The `Pipeline` struct is responsible for orchestrating the flow of data from various
/// sources, processing it through multiple pipes (for accounts, transactions, instructions,
/// and account deletions), and recording metrics at each stage. This flexible design
/// allows for customized data processing, handling a variety of update types with minimal
/// boilerplate code.
///
/// ## Overview
///
/// A `Pipeline` instance includes collections of data sources and processing pipes, enabling
/// users to configure the pipeline to handle diverse types of blockchain-related data. Each
/// pipe is responsible for decoding, processing, and routing specific data types, while the
/// metrics system records relevant statistics.
///
/// ### Key Concepts
///
/// - **Datasources**: These provide the raw data, such as account updates, transaction details,
/// and account deletions.
/// - **Pipes**: Modular units that handle specific data types:
/// - `AccountPipes` for account updates.
/// - `AccountDeletionPipes` for account deletions.
/// - `InstructionPipes` for instruction data within transactions.
/// - `TransactionPipes` for entire transaction payloads.
/// - **Metrics**: Collect performance data, enabling real-time insights and efficient monitoring.
///
/// ## Fields
///
/// - `datasources`: A vector of data sources (`Datasource` implementations) that provide
/// the data for processing. Each data source must be wrapped in an `Arc` for safe,
/// concurrent access.
/// - `account_pipes`: A vector of `AccountPipes`, each responsible for handling account updates.
/// - `account_deletion_pipes`: A vector of `AccountDeletionPipes` to handle deletion events.
/// - `instruction_pipes`: A vector of `InstructionPipes` for processing instructions within
/// transactions. These pipes work with nested instructions and are generically defined
/// to support varied instruction types.
/// - `transaction_pipes`: A vector of `TransactionPipes` responsible for processing
/// complete transaction payloads.
/// - `metrics`: A vector of `Metrics` implementations to record and track performance data.
/// Each metrics instance is managed within an `Arc` to ensure thread safety.
/// - `metrics_flush_interval`: An optional interval, in seconds, defining how frequently
/// metrics should be flushed. If `None`, the default interval is used.
///
/// ## Example
///
/// ```rust
///
/// carbon_core::pipeline::Pipeline::builder()
/// .datasource(transaction_crawler)
/// .metrics(Arc::new(LogMetrics::new()))
/// .metrics(Arc::new(PrometheusMetrics::new()))
/// .instruction(
/// TestProgramDecoder,
/// TestProgramProcessor
/// )
/// .account(
/// TestProgramDecoder,
/// TestProgramAccountProcessor
/// )
/// .transaction(TEST_SCHEMA.clone(), TestProgramTransactionProcessor)
/// .account_deletions(TestProgramAccountDeletionProcessor)
/// .build()?
/// .run()
/// .await?;
/// ```
///
/// ## Notes
///
/// - Ensure that each data source and pipe implements the required traits, such as
/// `Datasource`, `AccountPipes`, and `Metrics`, as appropriate.
/// - The pipeline is designed for concurrent operation, utilizing `Arc` and `Box`
/// types to handle shared ownership and trait object storage.
/// - The `metrics_flush_interval` controls how frequently the pipeline's metrics
/// are flushed. If `None`, a default interval (usually 5 seconds) is used.
pub struct Pipeline {
pub datasources: Vec<Arc<dyn Datasource + Send + Sync>>,
pub account_pipes: Vec<Box<dyn AccountPipes>>,
pub account_deletion_pipes: Vec<Box<dyn AccountDeletionPipes>>,
pub instruction_pipes: Vec<Box<dyn for<'a> InstructionPipes<'a>>>,
pub transaction_pipes: Vec<Box<dyn for<'a> TransactionPipes<'a>>>,
pub metrics: Arc<MetricsCollection>,
pub metrics_flush_interval: Option<u64>,
pub shutdown_strategy: ShutdownStrategy,
}
impl Pipeline {
/// Creates a new `PipelineBuilder` instance for constructing a `Pipeline`.
///
/// The `builder` method returns a `PipelineBuilder` that allows you to configure
/// and customize the pipeline components before building the final `Pipeline` object.
/// This approach provides a flexible and type-safe way to assemble a pipeline
/// by specifying data sources, processing pipes, and metrics.
///
/// # Example
///
/// ```rust
/// carbon_core::pipeline::Pipeline::builder()
/// .datasource(transaction_crawler)
/// .metrics(Arc::new(LogMetrics::new()))
/// .metrics(Arc::new(PrometheusMetrics::new()))
/// .instruction(
/// TestProgramDecoder,
/// TestProgramProcessor
/// )
/// // ...
/// ```
///
/// # Returns
///
/// Returns a `PipelineBuilder` instance with empty collections for data sources,
/// pipes, and metrics. You can then configure each component using the builder pattern.
///
pub fn builder() -> PipelineBuilder {
log::trace!("Pipeline::builder()");
PipelineBuilder {
datasources: Vec::new(),
account_pipes: Vec::new(),
account_deletion_pipes: Vec::new(),
instruction_pipes: Vec::new(),
transaction_pipes: Vec::new(),
metrics: MetricsCollection::default(),
metrics_flush_interval: None,
shutdown_strategy: ShutdownStrategy::default(),
}
}
/// Runs the `Pipeline`, processing updates from data sources and handling metrics.
///
/// The `run` method initializes the pipeline’s metrics system and starts listening for
/// updates from the configured data sources. It checks the types of updates provided
/// by each data source to ensure that the required data types are available for
/// processing. The method then enters a loop where it processes each update received
/// from the data sources in turn, logging and updating metrics based on the success
/// or failure of each operation.
///
/// # How it Works
///
/// - Initializes metrics and sets up an interval for periodic metric flushing.
/// - Spawns tasks for each data source to continuously consume updates.
/// - Processes updates according to their type (e.g., Account, Transaction, or AccountDeletion).
/// - Records performance metrics such as update processing times, and tracks success and failure counts.
///
/// # Errors
///
/// The method returns an `Err` variant if:
/// - Required update types (e.g., `AccountUpdate`, `AccountDeletion`, `Transaction`) are not
/// provided by any data source, causing a mismatch in expected data processing capabilities.
/// - A data source encounters an error while consuming updates.
/// - An error occurs during metrics flushing or processing of updates.
///
/// # Example
///
/// ```rust
/// use carbon_core::Pipeline;
///
/// let mut pipeline = Pipeline::builder()
/// .datasource(MyDatasource::new())
/// .metrics(MyMetrics::new())
/// .build()
/// .expect("Failed to build pipeline");
///
/// // Running the pipeline asynchronously
/// tokio::spawn(async move {
/// if let Err(e) = pipeline.run().await {
/// eprintln!("Pipeline run error: {:?}", e);
/// }
/// });
/// ```
///
/// # Notes
///
/// - This method is asynchronous and should be awaited within a Tokio runtime environment.
/// - The pipeline monitors metrics and flushes them based on the configured `metrics_flush_interval`.
/// - The `run` method operates in an infinite loop, handling updates until a termination condition occurs.
///
pub async fn run(&mut self) -> CarbonResult<()> {
log::info!("starting pipeline. num_datasources: {}, num_metrics: {}, num_account_pipes: {}, num_account_deletion_pipes: {}, num_instruction_pipes: {}, num_transaction_pipes: {}",
self.datasources.len(),
self.metrics.metrics.len(),
self.account_pipes.len(),
self.account_deletion_pipes.len(),
self.instruction_pipes.len(),
self.transaction_pipes.len(),
);
log::trace!("run(self)");
let update_types: Vec<UpdateType> = self
.datasources
.iter()
.map(|datasource| datasource.update_types())
.flatten()
.collect();
if !self.account_pipes.is_empty() && !update_types.contains(&UpdateType::AccountUpdate) {
return Err(Error::MissingUpdateTypeInDatasource(
UpdateType::AccountUpdate,
));
}
if !self.account_deletion_pipes.is_empty()
&& !update_types.contains(&UpdateType::AccountDeletion)
{
return Err(Error::MissingUpdateTypeInDatasource(
UpdateType::AccountDeletion,
));
}
if (!self.instruction_pipes.is_empty() || !self.transaction_pipes.is_empty())
&& !update_types.contains(&UpdateType::Transaction)
{
return Err(Error::MissingUpdateTypeInDatasource(
UpdateType::Transaction,
));
}
self.metrics.initialize_metrics().await?;
let (update_sender, mut update_receiver) = tokio::sync::mpsc::unbounded_channel::<Update>();
let datasource_cancellation_token = CancellationToken::new();
for datasource in &self.datasources {
let datasource_cancellation_token_clone = datasource_cancellation_token.clone();
let sender_clone = update_sender.clone();
let datasource_clone = Arc::clone(datasource);
let metrics_collection = self.metrics.clone();
tokio::spawn(async move {
if let Err(e) = datasource_clone
.consume(
&sender_clone,
datasource_cancellation_token_clone,
metrics_collection,
)
.await
{
log::error!("error consuming datasource: {:?}", e);
}
});
}
let mut interval = tokio::time::interval(time::Duration::from_secs(
self.metrics_flush_interval.unwrap_or(5),
));
loop {
tokio::select! {
_ = tokio::signal::ctrl_c() => {
log::trace!("received SIGINT, shutting down.");
datasource_cancellation_token.cancel();
if self.shutdown_strategy == ShutdownStrategy::Immediate {
log::info!("shutting down the pipeline immediately.");
self.metrics.flush_metrics().await?;
self.metrics.shutdown_metrics().await?;
break;
} else {
log::info!("shutting down the pipeline after processing pending updates.");
}
}
_ = interval.tick() => {
self.metrics.flush_metrics().await?;
}
update = update_receiver.recv() => {
match update {
Some(update) => {
self
.metrics.increment_counter("updates_received", 1)
.await?;
let start = Instant::now();
let process_result = self.process(update.clone()).await;
let time_taken = start.elapsed().as_millis();
self
.metrics.record_histogram("updates_processing_times", time_taken as f64)
.await?;
match process_result {
Ok(_) => {
self
.metrics.increment_counter("updates_successful", 1)
.await?;
log::trace!("processed update")
}
Err(error) => {
log::error!("error processing update ({:?}): {:?}", update, error);
self.metrics.increment_counter("updates_failed", 1).await?;
}
};
self
.metrics.increment_counter("updates_processed", 1)
.await?;
self
.metrics.update_gauge("updates_queued", update_receiver.len() as f64)
.await?;
}
None => {
log::info!("update_receiver closed, shutting down.");
self.metrics.flush_metrics().await?;
self.metrics.shutdown_metrics().await?;
break;
}
}
}
}
}
log::info!("pipeline shutdown complete.");
Ok(())
}
/// Processes a single update and routes it through the appropriate pipeline stages.
///
/// The `process` method takes an `Update` and determines its type, then routes it
/// through the corresponding pipes for handling account updates, transactions, or
/// account deletions. It also records metrics for processed updates, providing
/// insights into the processing workload and performance.
///
/// ## Functionality
///
/// - **Account Updates**: Passes account updates through the `account_pipes`. Each
/// pipe processes the account metadata and the updated account state.
/// - **Transaction Updates**: Extracts transaction metadata and instructions, nests
/// them if needed, and routes them through `instruction_pipes` and `transaction_pipes`.
/// - **Account Deletions**: Sends account deletion events through the `account_deletion_pipes`.
///
/// The method also updates metrics counters for each type of update, tracking how many
/// updates have been processed in each category.
///
/// # Parameters
///
/// - `update`: An `Update` variant representing the type of data received. This can be
/// an `Account`, `Transaction`, or `AccountDeletion`, each triggering different
/// processing logic within the pipeline.
///
/// # Returns
///
/// Returns a `CarbonResult<()>`, indicating `Ok(())` on successful processing or an
/// error if processing fails at any stage.
///
/// # Notes
///
/// - This method is asynchronous and should be awaited within a Tokio runtime.
/// - Each type of update (account, transaction, account deletion) requires its own
/// set of pipes, so ensure that appropriate pipes are configured based on the
/// data types expected from the data sources.
/// - Metrics are recorded after each successful processing stage to track processing
/// volumes and identify potential bottlenecks in real-time.
///
/// # Errors
///
/// Returns an error if any of the pipes fail during processing, or if an issue arises
/// while incrementing counters or updating metrics. Handle errors gracefully to ensure
/// continuous pipeline operation.
///
async fn process(&mut self, update: Update) -> CarbonResult<()> {
log::trace!("process(self, update: {:?})", update);
match update {
Update::Account(account_update) => {
let account_metadata = AccountMetadata {
slot: account_update.slot,
pubkey: account_update.pubkey,
};
for pipe in self.account_pipes.iter_mut() {
pipe.run(
(account_metadata.clone(), account_update.account.clone()),
self.metrics.clone(),
)
.await?;
}
self.metrics
.increment_counter("account_updates_processed", 1)
.await?;
}
Update::Transaction(transaction_update) => {
let transaction_metadata =
transformers::extract_transaction_metadata(&transaction_update)?;
let instructions_with_metadata: Vec<(
InstructionMetadata,
solana_sdk::instruction::Instruction,
)> = transformers::extract_instructions_with_metadata(
&transaction_metadata,
&transaction_update,
)?;
let nested_instructions =
transformers::nest_instructions(instructions_with_metadata);
for pipe in self.instruction_pipes.iter_mut() {
for nested_instruction in nested_instructions.iter().cloned() {
pipe.run(&nested_instruction, self.metrics.clone()).await?;
}
}
for pipe in self.transaction_pipes.iter_mut() {
pipe.run(&nested_instructions, self.metrics.clone()).await?;
}
self.metrics
.increment_counter("transaction_updates_processed", 1)
.await?;
}
Update::AccountDeletion(account_deletion) => {
for pipe in self.account_deletion_pipes.iter_mut() {
pipe.run(account_deletion.clone(), self.metrics.clone())
.await?;
}
self.metrics
.increment_counter("account_deletions_processed", 1)
.await?;
}
};
Ok(())
}
}
/// A builder for constructing a `Pipeline` instance with customized data sources, processing pipes, and metrics.
///
/// The `PipelineBuilder` struct offers a flexible way to assemble a `Pipeline` by allowing
/// configuration of its components, such as data sources, account and transaction pipes,
/// deletion handling, and metrics. Using the builder pattern, you can add the desired elements
/// incrementally and then finalize with a call to `build`.
///
/// ## Overview
///
/// The `PipelineBuilder` supports the following components:
/// - **Datasources**: Sources of data updates, such as account information and transactions.
/// - **Account Pipes**: For processing account updates from data sources.
/// - **Account Deletion Pipes**: For handling account deletion updates.
/// - **Instruction Pipes**: For handling instructions associated with transactions.
/// - **Transaction Pipes**: For handling full transaction data.
/// - **Metrics**: Collects and reports performance data, such as update processing times.
/// - **Metrics Flush Interval**: Optional interval defining how often to flush metrics data.
///
/// Each component can be added through method chaining, enhancing code readability and maintainability.
///
/// # Example
///
/// ```rust
/// carbon_core::pipeline::Pipeline::builder()
/// .datasource(transaction_crawler)
/// .metrics(Arc::new(LogMetrics::new()))
/// .metrics(Arc::new(PrometheusMetrics::new()))
/// .instruction(
/// TestProgramDecoder,
/// TestProgramProcessor
/// )
/// // ...
/// ```
///
/// # Fields
///
/// - `datasources`: A collection of `Datasource` objects wrapped in `Arc` for shared ownership
/// across threads. Each `Datasource` provides updates to the pipeline.
/// - `account_pipes`: A collection of `AccountPipes` to handle account updates.
/// - `account_deletion_pipes`: A collection of `AccountDeletionPipes` for processing account deletions.
/// - `instruction_pipes`: A collection of `InstructionPipes` to process instructions in transactions.
/// - `transaction_pipes`: A collection of `TransactionPipes` to process full transaction data.
/// - `metrics`: A vector of `Metrics` implementations for tracking pipeline performance.
/// - `metrics_flush_interval`: An optional interval (in seconds) for flushing metrics data.
/// If not set, a default flush interval will be used.
///
/// # Returns
///
/// After configuring the builder, call `build` to create a `Pipeline` instance.
/// The builder will return a `CarbonResult<Pipeline>`, which will either contain the
/// configured pipeline or an error if configuration failed.
///
/// # Notes
///
/// - The builder pattern allows for method chaining, making it easy to incrementally
/// add components to the `Pipeline`.
/// - Ensure that each component matches the data and update types expected by your application.
///
pub struct PipelineBuilder {
pub datasources: Vec<Arc<dyn Datasource + Send + Sync>>,
pub account_pipes: Vec<Box<dyn AccountPipes>>,
pub account_deletion_pipes: Vec<Box<dyn AccountDeletionPipes>>,
pub instruction_pipes: Vec<Box<dyn for<'a> InstructionPipes<'a>>>,
pub transaction_pipes: Vec<Box<dyn for<'a> TransactionPipes<'a>>>,
pub metrics: MetricsCollection,
pub metrics_flush_interval: Option<u64>,
pub shutdown_strategy: ShutdownStrategy,
}
impl PipelineBuilder {
/// Creates a new `PipelineBuilder` with empty collections for datasources, pipes, and metrics.
///
/// This method initializes a `PipelineBuilder` instance, allowing you to configure each component
/// of a `Pipeline` before building it. The builder pattern offers flexibility in adding data
/// sources, account and transaction handling pipes, deletion processing, and metrics collection
/// features.
///
/// # Example
///
/// ```rust
/// let builder = PipelineBuilder::new();
/// ```
///
pub fn new() -> Self {
log::trace!("PipelineBuilder::new()");
Self {
datasources: Vec::new(),
account_pipes: Vec::new(),
account_deletion_pipes: Vec::new(),
instruction_pipes: Vec::new(),
transaction_pipes: Vec::new(),
shutdown_strategy: ShutdownStrategy::default(),
metrics: MetricsCollection::default(),
metrics_flush_interval: None,
}
}
/// Adds a datasource to the pipeline.
///
/// The datasource is responsible for providing updates, such as account and transaction
/// data, to the pipeline. Multiple datasources can be added to handle various types of updates.
///
/// # Parameters
///
/// - `datasource`: The data source to add, implementing the `Datasource` trait.
///
/// # Example
///
/// ```rust
/// let builder = PipelineBuilder::new()
/// .datasource(MyDatasource::new());
/// ```
///
pub fn datasource(mut self, datasource: impl Datasource + Send + Sync + 'static) -> Self {
log::trace!("datasource(self, datasource: {:?})", stringify!(datasource));
self.datasources.push(Arc::new(datasource));
self
}
/// Sets the shutdown strategy for the pipeline.
///
/// This method configures how the pipeline should handle shutdowns. The shutdown strategy
/// defines whether the pipeline should terminate immediately or continue processing pending
/// updates after terminating the data sources.
///
/// # Parameters
///
/// - `shutdown_strategy`: A variant of [`ShutdownStrategy`] that determines how the pipeline
/// should handle shutdowns.
///
/// # Returns
///
/// Returns `Self`, allowing for method chaining.
///
/// # Notes
///
/// - Use `ShutdownStrategy::Immediate` to stop the entire pipeline instantly, including all
/// active processing tasks.
/// - Use `ShutdownStrategy::ProcessPending` (the default) to terminate data sources first
/// and allow the pipeline to finish processing any updates that are still pending.
///
pub fn shutdown_strategy(mut self, shutdown_strategy: ShutdownStrategy) -> Self {
log::trace!(
"shutdown_strategy(self, shutdown_strategy: {:?})",
shutdown_strategy
);
self.shutdown_strategy = shutdown_strategy;
self
}
/// Adds an account pipe to process account updates.
///
/// Account pipes decode and process updates to accounts within the pipeline. This method
/// requires both an `AccountDecoder` and a `Processor` to handle decoded account data.
///
/// # Parameters
///
/// - `decoder`: An `AccountDecoder` that decodes the account data.
/// - `processor`: A `Processor` that processes the decoded account data.
///
/// # Example
///
/// ```rust
/// let builder = PipelineBuilder::new()
/// .account(MyAccountDecoder, MyAccountProcessor);
/// ```
///
pub fn account<T: Send + Sync + 'static>(
mut self,
decoder: impl for<'a> AccountDecoder<'a, AccountType = T> + Send + Sync + 'static,
processor: impl Processor<InputType = (AccountMetadata, DecodedAccount<T>)>
+ Send
+ Sync
+ 'static,
) -> Self {
log::trace!(
"account(self, decoder: {:?}, processor: {:?})",
stringify!(decoder),
stringify!(processor)
);
self.account_pipes.push(Box::new(AccountPipe {
decoder: Box::new(decoder),
processor: Box::new(processor),
}));
self
}
/// Adds an account deletion pipe to handle account deletion events.
///
/// Account deletion pipes process deletions of accounts, with a `Processor` to handle
/// the deletion events as they occur.
///
/// # Parameters
///
/// - `processor`: A `Processor` that processes account deletion events.
///
/// # Example
///
/// ```rust
/// let builder = PipelineBuilder::new()
/// .account_deletions(MyAccountDeletionProcessor);
/// ```
///
pub fn account_deletions(
mut self,
processor: impl Processor<InputType = AccountDeletion> + Send + Sync + 'static,
) -> Self {
log::trace!(
"account_deletions(self, processor: {:?})",
stringify!(processor)
);
self.account_deletion_pipes
.push(Box::new(AccountDeletionPipe {
processor: Box::new(processor),
}));
self
}
/// Adds an instruction pipe to process instructions within transactions.
///
/// Instruction pipes decode and process individual instructions,
/// enabling specialized handling of various instruction types.
///
/// # Parameters
///
/// - `decoder`: An `InstructionDecoder` for decoding instructions from transaction data.
/// - `processor`: A `Processor` that processes decoded instruction data.
///
/// # Example
///
/// ```rust
/// let builder = PipelineBuilder::new()
/// .instruction(MyDecoder, MyInstructionProcessor);
/// ```
///
pub fn instruction<T: Send + Sync + 'static>(
mut self,
decoder: impl for<'a> InstructionDecoder<'a, InstructionType = T> + Send + Sync + 'static,
processor: impl Processor<
InputType = (
InstructionMetadata,
DecodedInstruction<T>,
Vec<NestedInstruction>,
),
> + Send
+ Sync
+ 'static,
) -> Self {
log::trace!(
"instruction(self, decoder: {:?}, processor: {:?})",
stringify!(decoder),
stringify!(processor)
);
self.instruction_pipes.push(Box::new(InstructionPipe {
decoder: Box::new(decoder),
processor: Box::new(processor),
}));
self
}
/// Adds a transaction pipe for processing full transaction data.
///
/// This method requires a transaction schema for decoding and a `Processor` to handle
/// the processed transaction data.
///
/// # Parameters
///
/// - `schema`: A `TransactionSchema` used to match and interpret transaction data.
/// - `processor`: A `Processor` that processes the decoded transaction data.
///
/// # Example
///
/// ```rust
/// let builder = PipelineBuilder::new()
/// .transaction(MY_SCHEMA.clone(), MyTransactionProcessor);
/// ```
///
pub fn transaction<T, U>(
mut self,
schema: TransactionSchema<T>,
processor: impl Processor<InputType = U> + Send + Sync + 'static,
) -> Self
where
T: InstructionDecoderCollection + 'static,
U: DeserializeOwned + Send + Sync + 'static,
{
log::trace!(
"transaction(self, schema: {:?}, processor: {:?})",
stringify!(schema),
stringify!(processor)
);
self.transaction_pipes
.push(Box::new(TransactionPipe::<T, U>::new(schema, processor)));
self
}
/// Adds a metrics component to the pipeline for performance tracking.
///
/// This component collects and reports on pipeline metrics, providing insights into
/// performance and operational statistics.
///
/// # Parameters
///
/// - `metrics`: An instance of a `Metrics` implementation, used to gather and report metrics.
///
/// # Example
///
/// ```rust
/// let builder = PipelineBuilder::new()
/// .metrics(Arc::new(LogMetrics::new()));
/// ```
///
pub fn metrics(mut self, metrics: Arc<dyn Metrics>) -> Self {
log::trace!("metrics(self, metrics: {:?})", stringify!(metrics));
self.metrics.metrics.push(metrics);
self
}
/// Sets the interval for flushing metrics data.
///
/// This value defines the frequency, in seconds, at which metrics data is flushed
/// from memory. If not set, a default interval is used.
///
/// # Parameters
///
/// - `interval`: The flush interval for metrics, in seconds.
///
/// # Example
///
/// ```rust
/// let builder = PipelineBuilder::new()
/// .metrics_flush_interval(60);
/// ```
///
pub fn metrics_flush_interval(mut self, interval: u64) -> Self {
log::trace!("metrics_flush_interval(self, interval: {:?})", interval);
self.metrics_flush_interval = Some(interval);
self
}
/// Builds and returns a `Pipeline` configured with the specified components.
///
/// After configuring the `PipelineBuilder` with data sources, pipes, and metrics,
/// call this method to create the final `Pipeline` instance ready for operation.
///
/// # Returns
///
/// Returns a `CarbonResult<Pipeline>` containing the configured `Pipeline`, or an error
/// if any part of the configuration is invalid.
///
/// # Example
///
/// ```rust
/// carbon_core::pipeline::Pipeline::builder()
/// .datasource(transaction_crawler)
/// .metrics(Arc::new(LogMetrics::new()))
/// .metrics(Arc::new(PrometheusMetrics::new()))
/// .instruction(
/// TestProgramDecoder,
/// TestProgramProcessor
/// )
/// .account(
/// TestProgramDecoder,
/// TestProgramAccountProcessor
/// )
/// .transaction(TEST_SCHEMA.clone(), TestProgramTransactionProcessor)
/// .account_deletions(TestProgramAccountDeletionProcessor)
/// .build()?
/// ```
///
pub fn build(self) -> CarbonResult<Pipeline> {
log::trace!("build(self)");
Ok(Pipeline {
datasources: self.datasources,
account_pipes: self.account_pipes,
account_deletion_pipes: self.account_deletion_pipes,
instruction_pipes: self.instruction_pipes,
transaction_pipes: self.transaction_pipes,
shutdown_strategy: self.shutdown_strategy,
metrics: Arc::new(self.metrics),
metrics_flush_interval: self.metrics_flush_interval,
})
}
}