Apache Flink SQL ORC Format Connector

import org.apache.flink.orc.OrcFileFormatFactory;
import org.apache.flink.orc.writer.OrcBulkWriterFactory;
import org.apache.flink.orc.vector.RowDataVectorizer;

// SQL/Table API format factory
import org.apache.flink.orc.OrcFileFormatFactory;

// DataStream API writing
import org.apache.flink.orc.writer.OrcBulkWriterFactory;
import org.apache.flink.orc.vector.RowDataVectorizer;

// Filter pushdown
import org.apache.flink.orc.OrcFilters;

// Input formats and readers
import org.apache.flink.orc.OrcColumnarRowFileInputFormat;
import org.apache.flink.orc.AbstractOrcFileInputFormat;

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
StreamTableEnvironment tEnv = StreamTableEnvironment.create(env);

// Create table with ORC format
tEnv.executeSql(
    "CREATE TABLE orc_table (" +
    "  user_id BIGINT," +
    "  item_id BIGINT," +
    "  category_id BIGINT," +
    "  behavior STRING," +
    "  ts TIMESTAMP(3)" +
    ") WITH (" +
    "  'connector' = 'filesystem'," +
    "  'path' = 'file:///path/to/orc/files'," +
    "  'format' = 'orc'" +
    ")"
);

// Query the ORC table
tEnv.executeSql("SELECT user_id, COUNT(*) FROM orc_table GROUP BY user_id").print();

import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.core.fs.Path;
import org.apache.flink.orc.vector.RowDataVectorizer;
import org.apache.flink.orc.writer.OrcBulkWriterFactory;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink;
import org.apache.flink.table.data.RowData;
import org.apache.flink.table.types.logical.BigIntType;
import org.apache.flink.table.types.logical.VarCharType;

// Create vectorizer for schema
String schema = "struct<user_id:bigint,item_id:bigint,behavior:varchar(50)>";
RowDataVectorizer vectorizer = new RowDataVectorizer(schema, new LogicalType[]{
    new BigIntType(), new BigIntType(), new VarCharType(50)
});

// Create ORC writer factory
OrcBulkWriterFactory<RowData> writerFactory = new OrcBulkWriterFactory<>(vectorizer);

// Create file sink
StreamingFileSink<RowData> sink = StreamingFileSink
    .forBulkFormat(new Path("file:///path/to/output"), writerFactory)
    .build();

// Write data stream to ORC files
DataStream<RowData> dataStream = // ... your data stream
dataStream.addSink(sink);

public class OrcFileFormatFactory implements BulkReaderFormatFactory, BulkWriterFormatFactory {
    public static final String IDENTIFIER = "orc";
    
    public String factoryIdentifier();
    public Set<ConfigOption<?>> requiredOptions();
    public Set<ConfigOption<?>> optionalOptions();
    public BulkDecodingFormat<RowData> createDecodingFormat(DynamicTableFactory.Context context, ReadableConfig formatOptions);
    public EncodingFormat<BulkWriter.Factory<RowData>> createEncodingFormat(DynamicTableFactory.Context context, ReadableConfig formatOptions);
}

public class OrcBulkWriterFactory<T> implements BulkWriter.Factory<T> {
    public OrcBulkWriterFactory(Vectorizer<T> vectorizer);
    public OrcBulkWriterFactory(Vectorizer<T> vectorizer, Configuration writerConfiguration);
    public OrcBulkWriterFactory(Vectorizer<T> vectorizer, Properties writerProperties, Configuration hadoopConfiguration);
    
    public BulkWriter<T> create(FSDataOutputStream out) throws IOException;
}

public abstract class Vectorizer<T> {
    public Vectorizer(String schema);
    public TypeDescription getSchema();
    public void addUserMetadata(String key, ByteBuffer value);
    public abstract void vectorize(T element, VectorizedRowBatch batch) throws IOException;
}

public class OrcFilters {
    public static Predicate toOrcPredicate(Expression expression);
    
    public abstract static class Predicate implements Serializable { }
    public static class Equals extends BinaryPredicate { }
    public static class LessThan extends BinaryPredicate { }
    public static class LessThanEquals extends BinaryPredicate { }
    public static class IsNull extends ColumnPredicate { }
    public static class Between extends ColumnPredicate { }
    public static class In extends ColumnPredicate { }
}

// Input format for reading ORC files
public abstract class AbstractOrcFileInputFormat<T, BatchT, SplitT> implements BulkFormat<T, SplitT> {
    public AbstractOrcFileInputFormat(
        Path[] filePaths,
        TypeDescription schema,
        int[] selectedFields,
        List<Predicate> conjunctPredicates,
        int batchSize,
        Configuration orcConfig,
        SerializableHadoopConfigWrapper hadoopConfigWrapper
    );
    
    public boolean isSplittable();
    public abstract TypeInformation<T> getProducedType();
}

// Concrete implementation for RowData
public class OrcColumnarRowFileInputFormat<BatchT, SplitT> extends AbstractOrcFileInputFormat<RowData, BatchT, SplitT> {
    public static <SplitT extends FileSourceSplit> OrcColumnarRowFileInputFormat<VectorizedRowBatch, SplitT> 
        createPartitionedFormat(
            Configuration orcConfig,
            RowType tableType,
            SerializableHadoopConfigWrapper hadoopConfigWrapper,
            List<String> partitionKeys,
            PartitionFieldExtractor<SplitT> extractor,
            List<Predicate> conjunctPredicates,
            int batchSize,
            boolean caseSensitive
        );
}

// Version compatibility interface
public interface OrcShim<BATCH> extends Serializable {
    RecordReader createRecordReader(
        Configuration conf, 
        TypeDescription schema, 
        int[] selectedFields,
        List<OrcFilters.Predicate> conjunctPredicates,
        org.apache.flink.core.fs.Path path, 
        long splitStart, 
        long splitLength
    ) throws IOException;
    OrcVectorizedBatchWrapper<BATCH> createBatchWrapper(TypeDescription schema, int batchSize);
    boolean nextBatch(RecordReader reader, BATCH batch) throws IOException;
    
    static OrcShim<VectorizedRowBatch> defaultShim();
    static OrcShim<VectorizedRowBatch> createShim(String hiveDependencyVersion);
}