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tessl/maven-org-apache-flink--flink-table-api-java-bridge

Java bridge for seamless integration between Flink's Table/SQL API and DataStream API, enabling conversion between streams and tables with unified batch and stream processing.

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mavenpkg:maven/org.apache.flink/flink-table-api-java-bridge@2.1.x

To install, run

npx @tessl/cli install tessl/maven-org-apache-flink--flink-table-api-java-bridge@2.1.0

index.mddocs/

Apache Flink Table API Java Bridge

The Apache Flink Table API Java Bridge provides seamless integration between Flink's Table/SQL API and the DataStream API for Java applications. This module enables developers to convert between DataStreams and Tables, create StreamTableEnvironments for unified batch and stream processing, and leverage SQL queries on streaming data with comprehensive connector support.

Package Information

  • Package Name: flink-table-api-java-bridge
  • Package Type: Maven
  • Group ID: org.apache.flink
  • Language: Java
  • Installation: Add to Maven dependencies: 
    <dependency>
  <groupId>org.apache.flink</groupId>
  <artifactId>flink-table-api-java-bridge</artifactId>
  <version>2.1.0</version>
</dependency>

Core Imports

import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.api.bridge.java.StreamStatementSet;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.streaming.api.datastream.DataStream;

Basic Usage

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.types.Row;

// Create execution environment and table environment
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

// Convert DataStream to Table
DataStream<Row> dataStream = env.fromElements(
    Row.of("Alice", 25),
    Row.of("Bob", 30)
);
Table table = tableEnv.fromDataStream(dataStream);

// Execute SQL on the table
Table result = tableEnv.sqlQuery("SELECT * FROM " + table + " WHERE f1 > 25");

// Convert Table back to DataStream
DataStream<Row> resultStream = tableEnv.toDataStream(result);

// Execute the pipeline
env.execute("Table API Bridge Example");

Architecture

The Flink Table API Java Bridge is built around several key components:

  • StreamTableEnvironment: Central context for bridging Table API and DataStream API operations
  • Stream-Table Conversion: Bidirectional conversion utilities between DataStreams and Tables
  • Schema Management: Type-safe schema definitions and transformations with watermark support
  • Built-in Connectors: Testing and development connectors (blackhole, datagen, print)
  • Legacy Support: Backward compatibility for existing table sources and sinks
  • Watermark Strategies: Time-based event processing with configurable watermark assignment

Capabilities

Stream Table Environment

Core environment for creating and managing tables that integrate with DataStream API. Provides unified context for both batch and streaming operations.

public interface StreamTableEnvironment extends TableEnvironment {
    static StreamTableEnvironment create(StreamExecutionEnvironment executionEnvironment);
    static StreamTableEnvironment create(StreamExecutionEnvironment executionEnvironment, EnvironmentSettings settings);
    
    <T> Table fromDataStream(DataStream<T> dataStream);
    <T> Table fromDataStream(DataStream<T> dataStream, Schema schema);
    <T> Table fromDataStream(DataStream<T> dataStream, Expression... fields); // @Deprecated
    
    <T> void createTemporaryView(String path, DataStream<T> dataStream);
    <T> void createTemporaryView(String path, DataStream<T> dataStream, Schema schema);
    <T> void createTemporaryView(String path, DataStream<T> dataStream, Expression... fields); // @Deprecated
    
    DataStream<Row> toDataStream(Table table);
    <T> DataStream<T> toDataStream(Table table, Class<T> targetClass);
    <T> DataStream<T> toDataStream(Table table, AbstractDataType<?> targetDataType);
    
    <T> DataStream<T> toAppendStream(Table table, Class<T> clazz); // @Deprecated
    <T> DataStream<T> toAppendStream(Table table, TypeInformation<T> typeInfo); // @Deprecated
    <T> DataStream<Tuple2<Boolean, T>> toRetractStream(Table table, Class<T> clazz); // @Deprecated
    <T> DataStream<Tuple2<Boolean, T>> toRetractStream(Table table, TypeInformation<T> typeInfo); // @Deprecated
    
    StreamStatementSet createStatementSet();
}

Stream Table Environment

Changelog Stream Processing

Advanced stream processing with support for changelog semantics including inserts, updates, and deletes.

public interface StreamTableEnvironment extends TableEnvironment {
    Table fromChangelogStream(DataStream<Row> dataStream);
    Table fromChangelogStream(DataStream<Row> dataStream, Schema schema);
    Table fromChangelogStream(DataStream<Row> dataStream, Schema schema, ChangelogMode changelogMode);
    
    DataStream<Row> toChangelogStream(Table table);
    DataStream<Row> toChangelogStream(Table table, Schema targetSchema);
    DataStream<Row> toChangelogStream(Table table, Schema targetSchema, ChangelogMode changelogMode);
}

Changelog Processing

DataStream Connector Providers

Provider interfaces for advanced connector development that integrate directly with DataStream API.

public interface DataStreamScanProvider extends ScanTableSource.ScanRuntimeProvider, ParallelismProvider {
    DataStream<RowData> produceDataStream(ProviderContext providerContext, StreamExecutionEnvironment execEnv);
}

public interface DataStreamSinkProvider extends DynamicTableSink.SinkRuntimeProvider, ParallelismProvider {
    DataStreamSink<?> consumeDataStream(ProviderContext providerContext, DataStream<RowData> dataStream);
    Optional<Integer> getParallelism();
}

DataStream Connectors

Built-in Test Connectors

Ready-to-use connectors for development, testing, and debugging table applications.

// BlackHole connector - discards all data for performance testing
CREATE TABLE sink_table (...) WITH ('connector' = 'blackhole');

// DataGen connector - generates test data
CREATE TABLE source_table (...) WITH (
    'connector' = 'datagen',
    'rows-per-second' = '100',
    'fields.user_id.kind' = 'sequence',
    'fields.name.kind' = 'random'
);

// Print connector - outputs data to console for debugging  
CREATE TABLE debug_table (...) WITH ('connector' = 'print');

Built-in Connectors

Watermark Strategies

Time-based event processing with configurable watermark assignment strategies for handling out-of-order events.

public abstract class PeriodicWatermarkAssigner {
    public abstract void nextTimestamp(long timestamp);
    public abstract Watermark getWatermark();
    public abstract Map<String, String> toProperties();
}

public final class BoundedOutOfOrderTimestamps extends PeriodicWatermarkAssigner {
    public BoundedOutOfOrderTimestamps(long delay);
}

public final class AscendingTimestamps extends PeriodicWatermarkAssigner {
    public AscendingTimestamps();
}

Watermark Strategies

Statement Set Operations

Batch execution optimization for multiple table operations with shared planning and execution.

public interface StreamStatementSet extends StatementSet {
    StreamStatementSet add(TablePipeline tablePipeline);
    StreamStatementSet addInsertSql(String statement);
    StreamStatementSet addInsert(String targetPath, Table table);
    StreamStatementSet addInsert(String targetPath, Table table, boolean overwrite);
    StreamStatementSet addInsert(TableDescriptor targetDescriptor, Table table);
    StreamStatementSet addInsert(TableDescriptor targetDescriptor, Table table, boolean overwrite);
    StreamStatementSet printExplain(ExplainDetail... extraDetails);
    
    void attachAsDataStream();
    
    // Inherited from StatementSet:
    // TableResult execute();
    // CompiledPlan compilePlan(); // @Experimental
    // String explain(ExplainDetail... extraDetails);
    // String explain(ExplainFormat format, ExplainDetail... extraDetails);
}

Statement Sets

Procedure Context

Context for stored procedure execution with access to StreamExecutionEnvironment.

public interface ProcedureContext {
    StreamExecutionEnvironment getExecutionEnvironment();
}

public class DefaultProcedureContext implements ProcedureContext {
    // Default implementation
}

Procedures

Types

Core Schema Types

import org.apache.flink.table.api.Schema;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.TableDescriptor;
import org.apache.flink.table.api.TableResult;
import org.apache.flink.table.api.CompiledPlan;
import org.apache.flink.table.api.ExplainDetail;
import org.apache.flink.table.api.ExplainFormat;
import org.apache.flink.table.connector.ChangelogMode;
import org.apache.flink.types.Row;
import org.apache.flink.types.RowKind;

DataStream Integration Types

import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.DataStreamSink;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.table.types.AbstractDataType;
import org.apache.flink.table.types.DataType;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.table.expressions.Expression;

Connector Provider Types

import org.apache.flink.table.connector.ProviderContext;
import org.apache.flink.table.connector.ParallelismProvider;
import org.apache.flink.table.data.RowData;
import java.util.Optional;