java - hive - 读写orc文件

读取orc文件

    @Test
    public void readOrc() throws IOException {
        Configuration conf = new Configuration();
        Reader reader = OrcFile.createReader(new Path("/tmp/Orc.orc"),
                OrcFile.readerOptions(conf));
        RecordReader rows = reader.rows();
        VectorizedRowBatch batch = reader.getSchema().createRowBatch();
        while (rows.nextBatch(batch)) {
            System.out.println(batch.toString());
        }
        rows.close();
    }

写orc文件---一行

    @Test
    public void writeLine3() throws IOException {
        Configuration conf = new Configuration();
        TypeDescription schema = TypeDescription.fromString("struct<x:int,y:int>");
        Writer writer = OrcFile.createWriter(new Path("/tmp/Orc.orc"),
                OrcFile.writerOptions(conf)
                        .setSchema(schema));
        VectorizedRowBatch batch = schema.createRowBatch();
        LongColumnVector x = (LongColumnVector) batch.cols[0];
        LongColumnVector y = (LongColumnVector) batch.cols[1];
        int row = batch.size++;
        x.vector[row] = 2;
        y.vector[row] = 2 * 3;
        if (batch.size != 0) {
            writer.addRowBatch(batch);
            batch.reset();
        }
        writer.close();
    }

写orc文件--多行

    @Test
    public void writeLine2() throws IOException {
        String[] lines = new String[]{"1,a,aa", "2,b,bb", "3,c,cc", "4,d,dd", "1,a,aa", "2,b,bb", "3,c,cc", "4,d,dd", "1,a,aa", "2,b,bb", "3,c,cc", "4,d,dd", "1,a,aa", "2,b,bb", "3,c,cc", "4,d,dd"};
//        String[] lines = new String[]{"1,2,4", "1,2,3", "1,2,3", "1,2,3", "1,2,3", "1,2,3", "1,2,3", "1,2,3"};


        Configuration conf = new Configuration();
        TypeDescription schema = TypeDescription.fromString("struct<field1:String,field2:String,field3:String>");
//        TypeDescription schema = TypeDescription.fromString("struct<field1:int,field2:int,field3:int>");
        Writer writer = OrcFile.createWriter(new Path("/tmp/Orc.orc"),
                OrcFile.writerOptions(conf)
                        .setSchema(schema).overwrite(true));
        VectorizedRowBatch batch = schema.createRowBatch();
        List<? super ColumnVector> columnVectors = new ArrayList<>();

        for (int i = 0; i < batch.numCols; i++) {
            columnVectors.add(batch.cols[i]);
        }

        for (String line : lines) {
            String[] columns = line.split(",");
            System.out.println(batch.size);
            int row = batch.size++;
            for (int i = 0; i < columns.length; i++) {
                switch (columnVectors.get(i).getClass().getName()) {
                    case "org.apache.hadoop.hive.ql.exec.vector.BytesColumnVector":
                        BytesColumnVector bytesColumnVector = BytesColumnVector.class.cast(columnVectors.get(i));
                        bytesColumnVector.setVal(row, columns[i].getBytes(), 0, columns[i].getBytes().length);
                        break;
                    case "org.apache.hadoop.hive.ql.exec.vector.LongColumnVector":
                        LongColumnVector longColumnVector = LongColumnVector.class.cast(columnVectors.get(i));
                        longColumnVector.vector[row] = Long.parseLong(columns[i]);
                        break;
                    case "org.apache.hadoop.hive.ql.exec.vector.Decimal64ColumnVector":
                        Decimal64ColumnVector decimal64ColumnVector = Decimal64ColumnVector.class.cast(columnVectors.get(i));
                        decimal64ColumnVector.set(row, HiveDecimal.create(columns[i]));
                        break;
                    case "org.apache.hadoop.hive.ql.exec.vector.DecimalColumnVector":
                        DecimalColumnVector decimalColumnVector = DecimalColumnVector.class.cast(columnVectors.get(i));
                        decimalColumnVector.set(row, HiveDecimal.create(columns[i]));
                        break;
                    case "org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector":
                        DoubleColumnVector doubleColumnVector = DoubleColumnVector.class.cast(columnVectors.get(i));
                        doubleColumnVector.vector[row] = Double.parseDouble(columns[i]);
                        break;
                    case "org.apache.hadoop.hive.ql.exec.vector.TimestampColumnVector":
                        TimestampColumnVector timestampColumnVector = TimestampColumnVector.class.cast(columnVectors.get(i));
                        timestampColumnVector.set(row, java.sql.Timestamp.valueOf(columns[i]));
                        break;
                }
                if (batch.size == batch.getMaxSize()) {
                    writer.addRowBatch(batch);
                    batch.reset();
                }
            }
        }
        if (batch.size != 0) {
            writer.addRowBatch(batch);
            batch.reset();
        }
        writer.close();

    }

 

引用jar

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hive.ql.exec.vector.BytesColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.ColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.LongColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.orc.*;
import org.junit.Test;

import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;