Java Code Examples for org.apache.orc.Writer#close()

The following examples show how to use org.apache.orc.Writer#close() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source File: SqlInterpreterTest.java    From zeppelin with Apache License 2.0 5 votes vote down vote up 
public File createORCFile(int[] values) throws IOException {
  File file = File.createTempFile("zeppelin-flink-input", ".orc");
  file.delete();
  Path path = new Path(file.getAbsolutePath());
  Configuration conf = new Configuration();
  conf.set("orc.compress", "snappy");
  TypeDescription schema = TypeDescription.fromString("struct<msg:int>");
  Writer writer = OrcFile.createWriter(path,
          OrcFile.writerOptions(conf)
                  .setSchema(schema));
  VectorizedRowBatch batch = schema.createRowBatch();
  LongColumnVector x = (LongColumnVector) batch.cols[0];
  for (int i = 0; i < values.length; ++i) {
    int row = batch.size++;
    x.vector[row] = values[i];
    // If the batch is full, write it out and start over.
    if (batch.size == batch.getMaxSize()) {
      writer.addRowBatch(batch);
      batch.reset();
    }
  }
  if (batch.size != 0) {
    writer.addRowBatch(batch);
    batch.reset();
  }
  writer.close();
  return file;
}
Example 2
Source File: TestAvroToOrcRecordConverter.java    From datacollector with Apache License 2.0 5 votes vote down vote up 
@Test
public void recordConversion() throws IOException {
  Path outputFilePath = new Path(createTempFile());

  Schema.Parser schemaParser = new Schema.Parser();
  Schema schema = schemaParser.parse(
      "{\"type\": \"record\", \"name\": \"MyRecord\", \"fields\": [{\"name\": \"first\", \"type\": \"int\"},{" +
          "\"name\": \"second\", \"type\": {\"type\": \"record\", \"name\": \"MySubRecord\", \"fields\":" +
          " [{\"name\": \"sub1\", \"type\": \"string\"}, {\"name\": \"sub2\", \"type\": \"int\"}] } }, {\"name\":" +
          " \"somedate\", \"type\": { \"type\" : \"int\", \"logicalType\": \"date\"} } ]}"
  );

  TypeDescription orcSchema = AvroToOrcSchemaConverter.getOrcSchema(schema);

  Writer orcWriter = AvroToOrcRecordConverter.createOrcWriter(
      new Properties(),
      new Configuration(),
      outputFilePath,
      orcSchema
  );

  GenericRecord avroRecord = new GenericData.Record(schema);
  avroRecord.put("first", 1);
  avroRecord.put("somedate", 17535);

  GenericData.Record subRecord = new GenericData.Record(schema.getField("second").schema());
  subRecord.put("sub1", new Utf8("value1"));
  subRecord.put("sub2", 42);

  avroRecord.put("second", subRecord);

  VectorizedRowBatch batch = orcSchema.createRowBatch();

  AvroToOrcRecordConverter.addAvroRecord(batch, avroRecord, orcSchema, 1000, orcWriter);
  orcWriter.addRowBatch(batch);
  batch.reset();
  orcWriter.close();

  // TODO: add code to read the ORC file and validate the contents
}
Example 3
Source File: TestAvroToOrcRecordConverter.java    From datacollector with Apache License 2.0 4 votes vote down vote up 
@Test
public void unionTypeConversions() throws IOException {
  final Path outputFilePath = new Path(createTempFile());

  final Schema.Parser schemaParser = new Schema.Parser();
  final Schema schema = schemaParser.parse(TestAvroToOrcRecordConverter.class.getResourceAsStream("avro_union_types.json"));

  final TypeDescription orcSchema = AvroToOrcSchemaConverter.getOrcSchema(schema);

  final Writer orcWriter = AvroToOrcRecordConverter.createOrcWriter(
      new Properties(),
      new Configuration(),
      outputFilePath,
      orcSchema
  );

  final GenericRecord avroRecord1 = new GenericData.Record(schema);
  avroRecord1.put("nullableInteger", 87);
  avroRecord1.put("integerOrString", "someString");
  avroRecord1.put("nullableStringOrInteger", "nonNullString");
  avroRecord1.put("justLong", 57844942331l);

  final GenericRecord avroRecord2 = new GenericData.Record(schema);
  avroRecord2.put("nullableInteger", null);
  avroRecord2.put("integerOrString", 16);
  avroRecord2.put("nullableStringOrInteger", null);
  avroRecord2.put("justLong", 758934l);

  final VectorizedRowBatch batch = orcSchema.createRowBatch();

  AvroToOrcRecordConverter.addAvroRecord(batch, avroRecord1, orcSchema, 1000, orcWriter);
  AvroToOrcRecordConverter.addAvroRecord(batch, avroRecord2, orcSchema, 1000, orcWriter);
  orcWriter.addRowBatch(batch);
  batch.reset();
  orcWriter.close();

  try (OrcToSdcRecordConverter sdcRecordConverter = new OrcToSdcRecordConverter(outputFilePath)) {

    final Record record1 = RecordCreator.create();
    boolean populated = sdcRecordConverter.populateRecord(record1);
    assertThat(populated, equalTo(true));
    assertSdcRecordMatchesAvro(record1, avroRecord1, null);

    final Record record2 = RecordCreator.create();
    populated = sdcRecordConverter.populateRecord(record2);
    assertThat(populated, equalTo(true));
    assertSdcRecordMatchesAvro(
        record2,
        avroRecord2,
        ImmutableMap.<String, Matcher<Field>>builder()
            .put("nullableInteger", Matchers.intFieldWithNullValue())
            .put("nullableStringOrInteger", Matchers.stringFieldWithNullValue())
            .build()
    );
  }
}
Example 4
Source File: OrcColumnarRowSplitReaderNoHiveTest.java    From flink with Apache License 2.0 4 votes vote down vote up 
@Override
protected void prepareReadFileWithTypes(String file, int rowSize) throws IOException {
	// NOTE: orc has field name information, so name should be same as orc
	TypeDescription schema =
			TypeDescription.fromString(
					"struct<" +
							"f0:float," +
							"f1:double," +
							"f2:timestamp," +
							"f3:tinyint," +
							"f4:smallint" +
							">");

	org.apache.hadoop.fs.Path filePath = new org.apache.hadoop.fs.Path(file);
	Configuration conf = new Configuration();

	Writer writer =
			OrcFile.createWriter(filePath,
					OrcFile.writerOptions(conf).setSchema(schema));

	VectorizedRowBatch batch = schema.createRowBatch(rowSize);
	DoubleColumnVector col0 = (DoubleColumnVector) batch.cols[0];
	DoubleColumnVector col1 = (DoubleColumnVector) batch.cols[1];
	TimestampColumnVector col2 = (TimestampColumnVector) batch.cols[2];
	LongColumnVector col3 = (LongColumnVector) batch.cols[3];
	LongColumnVector col4 = (LongColumnVector) batch.cols[4];

	col0.noNulls = false;
	col1.noNulls = false;
	col2.noNulls = false;
	col3.noNulls = false;
	col4.noNulls = false;
	for (int i = 0; i < rowSize - 1; i++) {
		col0.vector[i] = i;
		col1.vector[i] = i;

		Timestamp timestamp = toTimestamp(i);
		col2.time[i] = timestamp.getTime();
		col2.nanos[i] = timestamp.getNanos();

		col3.vector[i] = i;
		col4.vector[i] = i;
	}

	col0.isNull[rowSize - 1] = true;
	col1.isNull[rowSize - 1] = true;
	col2.isNull[rowSize - 1] = true;
	col3.isNull[rowSize - 1] = true;
	col4.isNull[rowSize - 1] = true;

	batch.size = rowSize;
	writer.addRowBatch(batch);
	batch.reset();
	writer.close();
}
Example 5
Source File: OrcColumnarRowSplitReaderTest.java    From flink with Apache License 2.0 4 votes vote down vote up 
protected void prepareReadFileWithTypes(String file, int rowSize) throws IOException {
	// NOTE: orc has field name information, so name should be same as orc
	TypeDescription schema =
			TypeDescription.fromString(
					"struct<" +
							"f0:float," +
							"f1:double," +
							"f2:timestamp," +
							"f3:tinyint," +
							"f4:smallint" +
							">");

	org.apache.hadoop.fs.Path filePath = new org.apache.hadoop.fs.Path(file);
	Configuration conf = new Configuration();

	Writer writer =
			OrcFile.createWriter(filePath,
					OrcFile.writerOptions(conf).setSchema(schema));

	VectorizedRowBatch batch = schema.createRowBatch(rowSize);
	DoubleColumnVector col0 = (DoubleColumnVector) batch.cols[0];
	DoubleColumnVector col1 = (DoubleColumnVector) batch.cols[1];
	TimestampColumnVector col2 = (TimestampColumnVector) batch.cols[2];
	LongColumnVector col3 = (LongColumnVector) batch.cols[3];
	LongColumnVector col4 = (LongColumnVector) batch.cols[4];

	col0.noNulls = false;
	col1.noNulls = false;
	col2.noNulls = false;
	col3.noNulls = false;
	col4.noNulls = false;
	for (int i = 0; i < rowSize - 1; i++) {
		col0.vector[i] = i;
		col1.vector[i] = i;

		Timestamp timestamp = toTimestamp(i);
		col2.time[i] = timestamp.getTime();
		col2.nanos[i] = timestamp.getNanos();

		col3.vector[i] = i;
		col4.vector[i] = i;
	}

	col0.isNull[rowSize - 1] = true;
	col1.isNull[rowSize - 1] = true;
	col2.isNull[rowSize - 1] = true;
	col3.isNull[rowSize - 1] = true;
	col4.isNull[rowSize - 1] = true;

	batch.size = rowSize;
	writer.addRowBatch(batch);
	batch.reset();
	writer.close();
}
Example 6
Source File: ORCRecordExtractorTest.java    From incubator-pinot with Apache License 2.0 4 votes vote down vote up 
/**
 * Create an ORC input file using the input records
 */
@Override
protected void createInputFile()
    throws IOException {
  TypeDescription schema = TypeDescription.fromString(
      "struct<user_id:int,firstName:string,lastName:string,bids:array<int>,campaignInfo:string,cost:double,timestamp:bigint>");
  Writer writer = OrcFile.createWriter(new Path(_dataFile.getAbsolutePath()),
      OrcFile.writerOptions(new Configuration()).setSchema(schema));

  int numRecords = _inputRecords.size();
  VectorizedRowBatch rowBatch = schema.createRowBatch(numRecords);
  LongColumnVector userIdVector = (LongColumnVector) rowBatch.cols[0];
  userIdVector.noNulls = false;
  BytesColumnVector firstNameVector = (BytesColumnVector) rowBatch.cols[1];
  firstNameVector.noNulls = false;
  BytesColumnVector lastNameVector = (BytesColumnVector) rowBatch.cols[2];
  ListColumnVector bidsVector = (ListColumnVector) rowBatch.cols[3];
  bidsVector.noNulls = false;
  LongColumnVector bidsElementVector = (LongColumnVector) bidsVector.child;
  bidsElementVector.ensureSize(6, false);
  BytesColumnVector campaignInfoVector = (BytesColumnVector) rowBatch.cols[4];
  DoubleColumnVector costVector = (DoubleColumnVector) rowBatch.cols[5];
  LongColumnVector timestampVector = (LongColumnVector) rowBatch.cols[6];

  for (int i = 0; i < numRecords; i++) {
    Map<String, Object> record = _inputRecords.get(i);

    Integer userId = (Integer) record.get("user_id");
    if (userId != null) {
      userIdVector.vector[i] = userId;
    } else {
      userIdVector.isNull[i] = true;
    }
    String firstName = (String) record.get("firstName");
    if (firstName != null) {
      firstNameVector.setVal(i, StringUtils.encodeUtf8(firstName));
    } else {
      firstNameVector.isNull[i] = true;
    }
    lastNameVector.setVal(i, StringUtils.encodeUtf8((String) record.get("lastName")));
    List<Integer> bids = (List<Integer>) record.get("bids");
    if (bids != null) {
      bidsVector.offsets[i] = bidsVector.childCount;
      bidsVector.lengths[i] = bids.size();
      for (int bid : bids) {
        bidsElementVector.vector[bidsVector.childCount++] = bid;
      }
    } else {
      bidsVector.isNull[i] = true;
    }
    campaignInfoVector.setVal(i, StringUtils.encodeUtf8((String) record.get("campaignInfo")));
    costVector.vector[i] = (double) record.get("cost");
    timestampVector.vector[i] = (long) record.get("timestamp");

    rowBatch.size++;
  }

  writer.addRowBatch(rowBatch);
  rowBatch.reset();
  writer.close();
}