Source Architecture

1. Overview

1.1 Problem Background

Data sources in distributed systems present several challenges:

• Parallelism: How to read data in parallel from a single source?
• Fault Tolerance: How to resume from where we left off after failures?
• Dynamic Assignment: How to handle worker failures and redistribute work?
• Bounded vs Unbounded: How to unify batch and streaming sources?
• Backpressure: How to handle slow downstream processing?

1.2 Design Goals

SeaTunnel's Source API aims to:

1. Enable Parallel Reading: Support split-based parallelism for scalability
2. Ensure Fault Tolerance: Checkpoint split state for exactly-once processing
3. Separate Coordination from Execution: Enumerator (master) and Reader (worker) separation
4. Support Dynamic Assignment: Reassign splits on failures or imbalance
5. Unify Batch and Streaming: Single API for both bounded and unbounded sources

1.3 Applicable Scenarios

• File-based sources (local files, HDFS, S3, OSS)
• Database sources (MySQL, PostgreSQL, Oracle, JDBC-compatible)
• Message queue sources (Kafka, Pulsar, RabbitMQ)
• CDC sources (MySQL CDC, PostgreSQL CDC, Oracle CDC)
• Stream sources (Socket, HTTP, custom protocols)

2. Architecture Design

2.1 Overall Architecture

2.2 Core Components

SeaTunnelSource (Factory Interface)

The top-level interface that serves as a factory for creating readers and enumerators.

public interface SeaTunnelSource<T, SplitT extends SourceSplit, StateT extends Serializable>
    extends Serializable {

    /**
     * Get source boundedness (BOUNDED for batch, UNBOUNDED for streaming)
     */
    Boundedness getBoundedness();

    /**
     * Create SourceReader (called on worker)
     */
    SourceReader<T, SplitT> createReader(SourceReader.Context readerContext) throws Exception;

    /**
     * Split serializer used for network transfer and checkpointing.
     */
    Serializer<SplitT> getSplitSerializer();

    /**
     * Create SourceSplitEnumerator (called on master)
     */
    SourceSplitEnumerator<SplitT, StateT> createEnumerator(
        SourceSplitEnumerator.Context<SplitT> enumeratorContext) throws Exception;

    /**
     * Restore SourceSplitEnumerator from checkpoint (called on master)
     */
    SourceSplitEnumerator<SplitT, StateT> restoreEnumerator(
        SourceSplitEnumerator.Context<SplitT> enumeratorContext,
        StateT checkpointState) throws Exception;

    /**
     * Enumerator-state serializer used for checkpointing.
     */
    Serializer<StateT> getEnumeratorStateSerializer();

    /**
     * Get output schema (CatalogTable list, supports multi-table)
     */
    List<CatalogTable> getProducedCatalogTables();
}

Key Methods:

• getBoundedness(): Indicates if source is bounded (batch) or unbounded (stream)
• createReader(): Factory for reader instances (one per worker task)
• createEnumerator(): Factory for enumerator (single instance on master)
• restoreEnumerator(): Restore enumerator from checkpoint state
• getProducedCatalogTables(): Defines output schema (supports multi-table)
• getSplitSerializer() / getEnumeratorStateSerializer(): Split/enumerator-state serializers for network transfer and checkpointing

SourceSplit (Minimal Serializable Unit)

Represents a partitionable unit of data.

public interface SourceSplit extends Serializable {
    /**
     * Unique identifier for this split
     */
    String splitId();
}

Implementation Examples:

// File-based split
public class FileSplit implements SourceSplit {
    private final String splitId;
    private final String filePath;
    private final long startOffset;
    private final long length;
}

// JDBC-based split (query range)
public class JdbcSourceSplit implements SourceSplit {
    private final String splitId;
    private final String query;
    private final Object[] queryParams;
}

// Kafka-based split (partition)
public class KafkaSourceSplit implements SourceSplit {
    private final String splitId;
    private final String topic;
    private final int partition;
    private final long startOffset;
}

Design Notes:

• Splits must be serializable for network transfer
• Split state (e.g., current offset) stored separately in reader state
• Splits can be reassigned to different readers

2.3 Interaction Flow

Initial Startup Flow

Checkpoint Flow

Failure Recovery Flow

3. Key Implementations

3.1 SourceSplitEnumerator Interface

The enumerator runs on the master side and coordinates split assignment.

public interface SourceSplitEnumerator<SplitT extends SourceSplit, StateT>
    extends AutoCloseable, CheckpointListener {

    /**
     * Called when enumerator starts
     */
    void open();

    /**
     * Executes split discovery and background coordination logic.
     *
     * Note: run() and snapshotState() may be invoked concurrently by different threads.
     */
    void run() throws Exception;

    /**
     * Add a split back to the enumerator for reassignment (typically after reader failure).
     */
    void addSplitsBack(List<SplitT> splits, int subtaskId);

    /**
     * Current number of unassigned splits.
     */
    int currentUnassignedSplitSize();

    /**
     * Called when a reader requests more splits.
     */
    void handleSplitRequest(int subtaskId);

    /**
     * Called when a reader registers.
     */
    void registerReader(int subtaskId);

    /**
     * Snapshot enumerator state for checkpoint
     */
    StateT snapshotState(long checkpointId) throws Exception;

    /**
     * Handle custom event from reader
     */
    default void handleSourceEvent(int subtaskId, SourceEvent sourceEvent) {}

    /**
     * Close enumerator
     */
    void close() throws IOException;

    /**
     * Context for interacting with framework
     */
    interface Context<SplitT extends SourceSplit> {
        int currentParallelism();
        Set<Integer> registeredReaders();
        void assignSplit(int subtaskId, List<SplitT> splits);
        void signalNoMoreSplits(int subtaskId);
        void sendEventToSourceReader(int subtaskId, SourceEvent event);
    }
}

Key Responsibilities:

• Split Discovery: Generate splits from data source (files, partitions, shards)
• Assignment Strategy: Decide which splits go to which readers
• Dynamic Handling: Handle reader registration, split requests, failures
• State Management: Snapshot remaining splits and assignment state

Implementation Example:

public class JdbcSourceSplitEnumerator implements SourceSplitEnumerator<JdbcSourceSplit, JdbcSourceState> {

    private final Queue<JdbcSourceSplit> pendingSplits = new LinkedList<>();
    private final Set<String> assignedSplits = new HashSet<>();
    private final Context<JdbcSourceSplit> context;

    @Override
    public void run() throws Exception {
        // Discover splits by querying database metadata
        List<JdbcSourceSplit> splits = generateSplitsByPartition();
        pendingSplits.addAll(splits);
    }

    @Override
    public void handleSplitRequest(int subtaskId) {
        // Assign next available split
        JdbcSourceSplit split = pendingSplits.poll();
        if (split != null) {
            context.assignSplit(subtaskId, Collections.singletonList(split));
            assignedSplits.add(split.splitId());
        } else {
            context.signalNoMoreSplits(subtaskId);
        }
    }

    @Override
    public void addSplitsBack(List<JdbcSourceSplit> splits, int subtaskId) {
        // Reclaim splits from failed reader
        pendingSplits.addAll(splits);
        splits.forEach(split -> assignedSplits.remove(split.splitId()));
    }

    @Override
    public JdbcSourceState snapshotState(long checkpointId) {
        // Save remaining splits and assignment info
        return new JdbcSourceState(new ArrayList<>(pendingSplits), assignedSplits);
    }
}

3.2 SourceReader Interface

The reader runs on workers and performs actual data reading.

public interface SourceReader<T, SplitT extends SourceSplit>
    extends AutoCloseable, CheckpointListener {

    /**
     * Called when reader starts
     */
    void open() throws Exception;

    /**
     * Poll next batch of records (non-blocking or timeout)
     */
    void pollNext(Collector<T> output) throws Exception;

    /**
     * Snapshot reader state for checkpoint (typically the current splits/positions).
     */
    List<SplitT> snapshotState(long checkpointId) throws Exception;

    /**
     * Add newly assigned splits.
     */
    void addSplits(List<SplitT> splits);

    /**
     * Signal no more splits will be assigned.
     */
    void handleNoMoreSplits();

    /**
     * Handle custom event from enumerator
     */
    default void handleSourceEvent(SourceEvent sourceEvent) {}

    /**
     * Close reader
     */
    void close() throws IOException;

    /**
     * Context for interacting with framework
     */
    interface Context {
        int getIndexOfSubtask();
        Boundedness getBoundedness();
        void signalNoMoreElement();
        void sendSplitRequest();
        void sendSourceEventToEnumerator(SourceEvent sourceEvent);
    }
}

Key Responsibilities:

• Data Reading: Pull records from assigned splits
• Progress Tracking: Track offset/position within each split
• State Management: Snapshot split progress for recovery
• Split Management: Handle split assignment, completion, and removal

Implementation Example:

public class JdbcSourceReader implements SourceReader<SeaTunnelRow, JdbcSourceSplit> {

    private final Queue<JdbcSourceSplit> pendingSplits = new LinkedList<>();
    private JdbcSourceSplit currentSplit;
    private ResultSet currentResultSet;

    @Override
    public void pollNext(Collector<SeaTunnelRow> output) throws Exception {
        if (currentResultSet == null) {
            // Fetch next split
            currentSplit = pendingSplits.poll();
            if (currentSplit == null) {
                context.sendSplitRequest(); // Request more splits
                return;
            }
            // Execute query for current split
            currentResultSet = executeQuery(currentSplit);
        }

        // Read batch of rows
        int count = 0;
        while (currentResultSet.next() && count++ < BATCH_SIZE) {
            SeaTunnelRow row = convertToRow(currentResultSet);
            output.collect(row);
        }

        // Check if split completed
        if (!currentResultSet.next()) {
            currentResultSet.close();
            currentResultSet = null;
            currentSplit = null;
        }
    }

    @Override
    public void addSplits(List<JdbcSourceSplit> splits) {
        pendingSplits.addAll(splits);
    }

    @Override
    public List<JdbcSourceState> snapshotState(long checkpointId) {
        // Save current split and offset
        List<JdbcSourceState> states = new ArrayList<>();
        if (currentSplit != null) {
            states.add(new JdbcSourceState(currentSplit, currentRow));
        }
        pendingSplits.forEach(split ->
            states.add(new JdbcSourceState(split, 0)));
        return states;
    }
}

3.3 SourceEvent (Custom Communication)

Allows enumerator and reader to exchange custom messages.

public interface SourceEvent extends Serializable {
}

// Example: Reader notifies enumerator of discovered partitions
public class PartitionDiscoveredEvent implements SourceEvent {
    private final List<String> newPartitions;
}

// Example: Enumerator notifies reader of configuration change
public class ConfigChangeEvent implements SourceEvent {
    private final Map<String, String> newConfig;
}

Use Cases:

• Dynamic partition discovery (Kafka, HDFS)
• Runtime configuration changes
• Custom coordination logic

3.4 Code References

API Interfaces:

• SeaTunnelSource.java
• SourceSplitEnumerator.java
• SourceReader.java
• SourceSplit.java

Example Implementations:

• JDBC Source: seatunnel-connectors-v2/connector-jdbc/src/main/java/org/apache/seatunnel/connectors/seatunnel/jdbc/source/
• Kafka Source: seatunnel-connectors-v2/connector-kafka/src/main/java/org/apache/seatunnel/connectors/seatunnel/kafka/source/
• File Source: seatunnel-connectors-v2/connector-file/connector-file-base/src/main/java/org/apache/seatunnel/connectors/seatunnel/file/source/

4. Design Considerations

4.1 Design Trade-offs

Enumerator-Reader Separation

Pros:

• Clean separation of coordination (master) and execution (worker)
• Enumerator can reassign splits without reader knowledge
• Centralized coordination simplifies split assignment logic
• Fault tolerance: enumerator and reader fail independently

Cons:

• Additional network communication (split assignment messages)
• More complex API for connector developers
• Potential bottleneck if enumerator is slow

Mitigation:

• Asynchronous split assignment
• Batch split requests/assignments
• Lazy split discovery

Split Granularity

Coarse-grained splits (few large splits):

• Pro: Less coordination overhead
• Con: Poor load balancing, longer recovery time

Fine-grained splits (many small splits):

• Pro: Better load balancing, faster recovery
• Con: Higher coordination overhead

Guideline: Choose split granularity based on source capabilities, expected parallelism, and checkpoint/recovery cost.

4.2 Performance Considerations

Batch Reading

@Override
public void pollNext(Collector<SeaTunnelRow> output) throws Exception {
    // Read batch instead of single record
    for (int i = 0; i < BATCH_SIZE && hasNext(); i++) {
        output.collect(readNextRow());
    }
}

Benefits:

• Amortize per-record overhead
• Better CPU cache utilization
• Reduce lock contention

Non-blocking Poll

@Override
public void pollNext(Collector<SeaTunnelRow> output) throws Exception {
    // Return immediately if no data available
    if (!hasNext()) {
        return; // Framework will call again later
    }
    output.collect(readNextRow());
}

Benefits:

• Avoid blocking worker thread
• Enable backpressure handling
• Better resource utilization

Connection Pooling

public class JdbcSourceReader {
    private final HikariDataSource dataSource; // Connection pool

    @Override
    public void pollNext(Collector<SeaTunnelRow> output) {
        try (Connection conn = dataSource.getConnection()) {
            // Reuse pooled connections
        }
    }
}

4.3 Extensibility

Custom Split Assignment Strategy

public class CustomEnumerator implements SourceSplitEnumerator<...> {

    @Override
    public void handleSplitRequest(int subtaskId) {
        // Custom logic: assign splits based on data locality
        JdbcSourceSplit split = findClosestSplit(subtaskId);
        context.assignSplit(subtaskId, Collections.singletonList(split));
    }

    private JdbcSourceSplit findClosestSplit(int subtaskId) {
        // Check worker location and assign split on same rack/region
        WorkerLocation location = getWorkerLocation(subtaskId);
        return pendingSplits.stream()
            .filter(split -> split.location().equals(location))
            .findFirst()
            .orElse(pendingSplits.poll());
    }
}

Dynamic Split Discovery

public class KafkaSourceSplitEnumerator {

    @Override
    public void run() throws Exception {
        // Discover initial partitions
        discoverPartitions();

        // Periodically check for new partitions
        scheduledExecutor.scheduleAtFixedRate(
            this::discoverPartitions,
            60, 60, TimeUnit.SECONDS
        );
    }

    private void discoverPartitions() {
        List<TopicPartition> newPartitions = kafkaAdmin.listPartitions();
        // Assign new partitions to readers
        assignNewPartitions(newPartitions);
    }
}

5. Best Practices

5.1 Usage Recommendations

1. Split Sizing

• Files: split by file/offset ranges according to file format and I/O characteristics
• Databases: split by primary key / partition key ranges (or other stable predicates)
• Message queues: use native partitions (e.g., Kafka partitions)

2. State Management

• Keep split/reader state small and stable across versions
• Use offsets/positions instead of buffered data
• Serialize efficiently (Kryo, Protobuf)

3. Error Handling

@Override
public void pollNext(Collector<SeaTunnelRow> output) throws Exception {
    try {
        // Read data
    } catch (TransientException e) {
        // Retry transient errors
        Thread.sleep(1000);
        retry();
    } catch (FatalException e) {
        // Fatal errors should propagate
        throw e;
    }
}

4. Resource Management

@Override
public void close() throws IOException {
    // Always close resources
    if (resultSet != null) resultSet.close();
    if (connection != null) connection.close();
    if (dataSource != null) dataSource.close();
}

5.2 Common Pitfalls

1. Blocking pollNext()

// ❌ BAD: Blocks indefinitely
public void pollNext(Collector<SeaTunnelRow> output) {
    while (true) {
        Record record = queue.take(); // Blocks until data available
        output.collect(record);
    }
}

// ✅ GOOD: Non-blocking or timeout
public void pollNext(Collector<SeaTunnelRow> output) {
    Record record = queue.poll(100, TimeUnit.MILLISECONDS);
    if (record != null) {
        output.collect(record);
    }
}

2. Large State

// ❌ BAD: Buffer entire split in state
public class BadReaderState {
    private List<SeaTunnelRow> bufferedRows; // May be huge!
}

// ✅ GOOD: Only track offset
public class GoodReaderState {
    private long currentOffset; // Small and efficient
}

3. Forgetting to Request Splits

// ❌ BAD: Reader never gets splits
public void pollNext(Collector<SeaTunnelRow> output) {
    if (pendingSplits.isEmpty()) {
        return; // Oops, should request more splits!
    }
}

// ✅ GOOD: Explicitly request splits
public void pollNext(Collector<SeaTunnelRow> output) {
    if (pendingSplits.isEmpty()) {
        context.sendSplitRequest();
        return;
    }
}

5.3 Debugging Tips

1. Enable Debug Logging

private static final Logger LOG = LoggerFactory.getLogger(JdbcSourceReader.class);

public void pollNext(Collector<SeaTunnelRow> output) {
    LOG.debug("Polling split: {}, offset: {}", currentSplit.splitId(), currentOffset);
    // ...
}

2. Track Metrics

public class JdbcSourceReader {
    private long recordsRead = 0;
    private long bytesRead = 0;

    public void pollNext(Collector<SeaTunnelRow> output) {
        SeaTunnelRow row = readRow();
        recordsRead++;
        bytesRead += row.getBytesSize();
        output.collect(row);
    }
}

3. Test Split Reassignment

// Simulate reader failure to test split recovery
@Test
public void testSplitReassignment() {
    // Assign splits to reader 0
    enumerator.handleSplitRequest(0);

    // Simulate reader 0 failure
    enumerator.addSplitsBack(assignedSplits, 0);

    // New reader 1 should get those splits
    enumerator.registerReader(1);
    enumerator.handleSplitRequest(1);

    // Verify splits were reassigned
    assertThat(assignedSplits).isNotEmpty();
}

6. Related Resources

• Architecture Overview
• Design Philosophy
• Sink Architecture
• Checkpoint Mechanism
• How to Create Your Connector

7. References

Example Connectors

• Simple Source: FakeSource (generates test data)
• File Source: FileSource (local/HDFS/S3 files)
• Database Source: JdbcSource (JDBC-compatible databases)
• Streaming Source: KafkaSource (Apache Kafka)
• CDC Source: MySQLCDCSource (MySQL binlog)

Further Reading

• Apache Flink FLIP-27: "Refactored Source API"
• Kafka Consumer: Consumer Groups and Partition Assignment