Avro is a row or record oriented serialization protocol (i.e., not columnar-oriented). Example of reading writing Parquet in java without BigData tools. public class ParquetReaderWriterWithAvro { private static final Logger LOGGER = LoggerFactory . getLogger( ParquetReaderWriterWithAvro .

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The following examples show how to use org.apache.parquet.avro.AvroParquetWriter. These examples are extracted from open source projects. 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. AvroParquetWriter. Code Index Add Codota to your IDE (free) How to use.

Then you can run the … 2018-05-22 2017-02-18 2018-06-07 Codota search - find any Java class or method The builder for org.apache.parquet.avro.AvroParquetWriter accepts an OutputFile instance whereas the builder for org.apache.parquet.avro.AvroParquetReader accepts an InputFile instance.

byteofffset: 21 line: This is a Hadoop MapReduce program file. No need to deal with Spark or Hive in order to create a Parquet file, just some lines of Java.

* @return the value of the field with the given name, or null if not set. */ public Object get AvroParquetWriter dataFileWriter = AvroParquetWriter(path, schema); dataFileWriter.write(record); You probabaly gonna ask, why not just use protobuf to parquet example-format, which contains the Avro description of the primary data record we are using (User) example-code, which contains the actual code that executes the queries; There are two ways to specify a schema for Avro records: via a description in JSON format or via the IDL. We chose the latter since it is easier to comprehend. The builder for org.apache.parquet.avro.AvroParquetWriter accepts an OutputFile instance whereas the builder for org.apache.parquet.avro.AvroParquetReader accepts an InputFile instance. This example illustrates writing Avro format data to Parquet. Avro is a row or record oriented serialization protocol (i.e., not columnar-oriented). Example of reading writing Parquet in java without BigData tools. public class ParquetReaderWriterWithAvro { private static final Logger LOGGER = LoggerFactory .

Why? Because you may need to consume some data which is not controlled by you.
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This example illustrates writing Avro format data to Parquet. Avro is a row or record oriented serialization protocol (i.e., not columnar-oriented). 2016-11-19 2017-11-23 The following examples show how to use org.apache.parquet.hadoop.ParquetWriter.These examples are extracted from open source projects. 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. throws IOException { final ParquetReader.Builder readerBuilder = AvroParquetReader.builder(path).withConf(conf); Example 1.

A simple AvroParquetWriter is instancied with the default options, like a block size of 128MB and a page size of 1MB. Snappy has been used as compression codec and an Avro schema has been defined: This example shows how you can read a Parquet file using MapReduce.
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/** * @param writer The actual Proto + Parquet writer * @param temporaryHdfsPath The path to which the writer will output events * @param finalHdfsDir The directory to write the final output to (renamed from temporaryHdfsPath) You will need version 2.8.1 for this example (due to parquet-avro 1.9.0). Copy these files to C:\hadoop-2.8.1\bin on the target machine. Add a new System Variable (not user variable) called: … ParquetWriter< ExampleMessage > writer = AvroParquetWriter. < ExampleMessage > builder(new Path (parquetFile)).withConf(conf) // conf set to use 3-level lists.withDataModel(model) // use the protobuf data model.withSchema(schema) // Avro schema for the protobuf data.build(); FileInputStream protoStream = new FileInputStream (new File (protoFile)); try Java Code Examples parquet.avro.AvroParquetWriter, Create a data file that gets exported to the db.

* @param numRecords how many records to write to the file. */ protected void createParquetFile(int numRecords, The AvroParquetWriter already depends on Hadoop, so even if this extra dependency is unacceptable to you it may not be a big deal to others: You can use an AvroParquetWriter to stream Schema schema = new Schema.Parser().parse(Resources.getResource("map.avsc").openStream()); File tmp = File.createTempFile(getClass().getSimpleName(), ".tmp"); tmp.deleteOnExit(); tmp.delete(); Path file = new Path (tmp.getPath()); AvroParquetWriter writer = new AvroParquetWriter(file, schema); // Write a record with an empty map. public AvroParquetWriter (Path file, Schema avroSchema, CompressionCodecName compressionCodecName, int blockSize, int pageSize) throws IOException {super (file, AvroParquetWriter. < T > writeSupport(avroSchema, SpecificData. get()), compressionCodecName, blockSize, pageSize);} /* * Create a new {@link AvroParquetWriter}. * * @param file The example-format, which contains the Avro description of the primary data record we are using (User) example-code, which contains the actual code that executes the queries; There are two ways to specify a schema for Avro records: via a description in JSON format or via the IDL. We chose the latter since it is easier to comprehend.

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.