Java Code Examples for parquet.hadoop.ParquetOutputFormat

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Example 1

Project: iow-hadoop-streaming   File: ParquetAsTextOutputFormat.java View source code

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7 votes

privatestaticCompressionCodecName getCodec(JobConf conf){CompressionCodecName codec;if(ParquetOutputFormat.isCompressionSet(conf)){// explicit parquet config
          codec =ParquetOutputFormat.getCompression(conf);}elseif(getCompressOutput(conf)){// from hadoop config// find the right codecClass<?> codecClass = getOutputCompressorClass(conf,DefaultCodec.class);
          LOG.info("Compression set through hadoop codec: "+ codecClass.getName());
          codec =CompressionCodecName.fromCompressionCodec(codecClass);}else{
          codec =CompressionCodecName.UNCOMPRESSED;}

        LOG.info("Compression: "+ codec.name());return codec;}

Example 2

Project: tajo   File: ParquetAppender.java View source code

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6 votes

/**
 * Creates a new ParquetAppender.
 *
 * @param conf Configuration properties.
 * @param schema The table schema.
 * @param meta The table metadata.
 * @param workDir The path of the Parquet file to write to.
 */publicParquetAppender(Configuration conf,TaskAttemptId taskAttemptId,Schema schema,TableMeta meta,Path workDir)throwsIOException{super(conf, taskAttemptId, schema, meta, workDir);this.blockSize =Integer.parseInt(
      meta.getOption(ParquetOutputFormat.BLOCK_SIZE,StorageConstants.PARQUET_DEFAULT_BLOCK_SIZE));this.pageSize =Integer.parseInt(
      meta.getOption(ParquetOutputFormat.PAGE_SIZE,StorageConstants.PARQUET_DEFAULT_PAGE_SIZE));this.compressionCodecName =CompressionCodecName.fromConf(
      meta.getOption(ParquetOutputFormat.COMPRESSION,StorageConstants.PARQUET_DEFAULT_COMPRESSION_CODEC_NAME));this.enableDictionary =Boolean.parseBoolean(
      meta.getOption(ParquetOutputFormat.ENABLE_DICTIONARY,StorageConstants.PARQUET_DEFAULT_IS_DICTIONARY_ENABLED));this.validating =Boolean.parseBoolean(
      meta.getOption(ParquetOutputFormat.VALIDATION,StorageConstants.PARQUET_DEFAULT_IS_VALIDATION_ENABLED));}

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Example 3

Project: pbase   File: TestInputOutputFormat.java View source code

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6 votes

privatevoid runMapReduceJob(CompressionCodecName codec,Map<String,String> extraConf)throwsIOException,ClassNotFoundException,InterruptedException{Configuration conf =newConfiguration(this.conf);for(Map.Entry<String,String> entry : extraConf.entrySet()){
        conf.set(entry.getKey(), entry.getValue());}finalFileSystem fileSystem = parquetPath.getFileSystem(conf);
    fileSystem.delete(parquetPath,true);
    fileSystem.delete(outputPath,true);{
        writeJob =newJob(conf,"write");TextInputFormat.addInputPath(writeJob, inputPath);
        writeJob.setInputFormatClass(TextInputFormat.class);
        writeJob.setNumReduceTasks(0);ParquetOutputFormat.setCompression(writeJob, codec);ParquetOutputFormat.setOutputPath(writeJob, parquetPath);
        writeJob.setOutputFormatClass(ParquetOutputFormat.class);
        writeJob.setMapperClass(readMapperClass);ParquetOutputFormat.setWriteSupportClass(writeJob,MyWriteSupport.class);GroupWriteSupport.setSchema(MessageTypeParser.parseMessageType(writeSchema),
                writeJob.getConfiguration());
        writeJob.submit();
        waitForJob(writeJob);}{
        conf.set(ReadSupport.PARQUET_READ_SCHEMA, readSchema);
        readJob =newJob(conf,"read");

        readJob.setInputFormatClass(ParquetInputFormat.class);ParquetInputFormat.setReadSupportClass(readJob,MyReadSupport.class);ParquetInputFormat.setInputPaths(readJob, parquetPath);
        readJob.setOutputFormatClass(TextOutputFormat.class);TextOutputFormat.setOutputPath(readJob, outputPath);
        readJob.setMapperClass(writeMapperClass);
        readJob.setNumReduceTasks(0);
        readJob.submit();
        waitForJob(readJob);}}

Example 4

Project: pbase   File: CodecConfigTest.java View source code

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6 votes

publicvoid shouldUseParquetFlagToSetCodec(String codecNameStr,CompressionCodecName expectedCodec)throwsIOException{//Test mapreduce APIJob job =newJob();Configuration conf = job.getConfiguration();
        conf.set(ParquetOutputFormat.COMPRESSION, codecNameStr);TaskAttemptContext task =ContextUtil.newTaskAttemptContext(conf,newTaskAttemptID(newTaskID(newJobID("test",1),false,1),1));Assert.assertEquals(CodecConfig.from(task).getCodec(), expectedCodec);//Test mapred APIJobConf jobConf =newJobConf();
        jobConf.set(ParquetOutputFormat.COMPRESSION, codecNameStr);Assert.assertEquals(CodecConfig.from(jobConf).getCodec(), expectedCodec);}

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Example 5

Project: pbase   File: DeprecatedParquetOutputFormat.java View source code

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6 votes

publicRecordWriterWrapper(ParquetOutputFormat<V> realOutputFormat,FileSystem fs,JobConf conf,String name,Progressable progress)throwsIOException{CompressionCodecName codec = getCodec(conf);String extension = codec.getExtension()+".parquet";Path file = getDefaultWorkFile(conf, name, extension);try{
        realWriter =(ParquetRecordWriter<V>) realOutputFormat.getRecordWriter(conf, file, codec);}catch(InterruptedException e){Thread.interrupted();thrownewIOException(e);}}

Example 6

Project: tajo-cdh   File: ParquetAppender.java View source code

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6 votes

/**
 * Creates a new ParquetAppender.
 *
 * @param conf Configuration properties.
 * @param schema The table schema.
 * @param meta The table metadata.
 * @param path The path of the Parquet file to write to.
 */publicParquetAppender(Configuration conf,Schema schema,TableMeta meta,Path path)throwsIOException{super(conf, schema, meta, path);this.blockSize =Integer.parseInt(
      meta.getOption(ParquetOutputFormat.BLOCK_SIZE));this.pageSize =Integer.parseInt(
      meta.getOption(ParquetOutputFormat.PAGE_SIZE));this.compressionCodecName =CompressionCodecName.fromConf(
      meta.getOption(ParquetOutputFormat.COMPRESSION));this.enableDictionary =Boolean.parseBoolean(
      meta.getOption(ParquetOutputFormat.ENABLE_DICTIONARY));this.validating =Boolean.parseBoolean(
      meta.getOption(ParquetOutputFormat.VALIDATION));}

Example 7

Project: tajo-cdh   File: StorageUtil.java View source code

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6 votes

publicstaticOptions newPhysicalProperties(CatalogProtos.StoreType type){Options options =newOptions();if(CatalogProtos.StoreType.CSV == type){
    options.put(CSVFILE_DELIMITER, DEFAULT_FIELD_DELIMITER);}elseif(CatalogProtos.StoreType.RCFILE == type){
    options.put(RCFILE_SERDE, DEFAULT_BINARY_SERDE);}elseif(CatalogProtos.StoreType.SEQUENCEFILE == type){
    options.put(SEQUENCEFILE_SERDE, DEFAULT_TEXT_SERDE);
    options.put(SEQUENCEFILE_DELIMITER, DEFAULT_FIELD_DELIMITER);}elseif(type ==CatalogProtos.StoreType.PARQUET){
    options.put(ParquetOutputFormat.BLOCK_SIZE, PARQUET_DEFAULT_BLOCK_SIZE);
    options.put(ParquetOutputFormat.PAGE_SIZE, PARQUET_DEFAULT_PAGE_SIZE);
    options.put(ParquetOutputFormat.COMPRESSION, PARQUET_DEFAULT_COMPRESSION_CODEC_NAME);
    options.put(ParquetOutputFormat.ENABLE_DICTIONARY, PARQUET_DEFAULT_IS_DICTIONARY_ENABLED);
    options.put(ParquetOutputFormat.VALIDATION, PARQUET_DEFAULT_IS_VALIDATION_ENABLED);}return options;}

Example 8

Project: hadoop-arch-book   File: JavaSessionize.java View source code

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5 votes

publicstaticvoid main(String[] args)throwsException{if(args.length ==0){System.err.println("Usage: JavaSessionize <master> [input file]");System.exit(1);}System.out.println("Output:"+ outputPath);JavaSparkContext jsc =newJavaSparkContext(args[0],"JavaSessionize",System.getenv("SPARK_HOME"),JavaSparkContext.jarOfClass(JavaSessionize.class));JavaRDD<String> dataSet =(args.length ==2)? jsc.textFile(args[1]): jsc.parallelize(testLines);// @formatter:offJavaPairRDD<String,SerializableLogLine> parsed = dataSet.map(newPairFunction<String,String,SerializableLogLine>(){// @formatter:on@OverridepublicTuple2<String,SerializableLogLine> call(String s)throwsException{returnnewTuple2<String,SerializableLogLine>(getIP(s),
                            getFields(s));}});// This groups clicks by IP addressJavaPairRDD<String,List<SerializableLogLine>> grouped = parsed
            .groupByKey();JavaPairRDD<String,List<SerializableLogLine>> sessionized = grouped
            .mapValues(newFunction<List<SerializableLogLine>,List<SerializableLogLine>>(){@OverridepublicList<SerializableLogLine> call
                        (List<SerializableLogLine> logLines)throwsException{return sessionize(logLines);}});

    sessionized.foreach(newVoidFunction<Tuple2<String,List<SerializableLogLine>>>(){@Overridepublicvoid call(Tuple2<String,List<SerializableLogLine>>
                                 stringListTuple2)throwsException{System.out.println("IP: "+ stringListTuple2._1());for(SerializableLogLine line : stringListTuple2._2()){System.out.println(line);}}});// right now sessionize is an RDD of pairs: <String,List<LogLine>>.// We want to output an RDD of <String,LogLine>// First, grab the Lists, then flatten them,// then pair them with something empty to make Hadoop happy// @formatter:offJavaRDD<List<SerializableLogLine>> nokeys = sessionized.map(newFunction<Tuple2<String,List<SerializableLogLine>>,List<SerializableLogLine>>(){// @formatter:on@OverridepublicList<SerializableLogLine> call(Tuple2<String,List<SerializableLogLine>> stringListTuple2)throwsException{return stringListTuple2._2();}});// @formatter:offJavaRDD<SerializableLogLine> flatLines = nokeys.flatMap(newFlatMapFunction<List<SerializableLogLine>,SerializableLogLine>(){// @formatter:on@OverridepublicIterable<SerializableLogLine> call
                (List<SerializableLogLine> serializableLogLines)throwsException{return serializableLogLines;}});JavaPairRDD<Void,SerializableLogLine> outputPairs = flatLines.map
            (newPairFunction<SerializableLogLine,Void,SerializableLogLine>(){@OverridepublicTuple2<Void,SerializableLogLine> call
                        (SerializableLogLine
                                 serializableLogLine)throwsException{returnnewTuple2<Void,SerializableLogLine>(null,
                            serializableLogLine);}});Job job =newJob();ParquetOutputFormat.setWriteSupportClass(job,AvroWriteSupport.class);AvroParquetOutputFormat.setSchema(job,LogLine.SCHEMA$);//dummy instance, because that's the only way to get the class of a// parameterized typeParquetOutputFormat<LogLine> pOutput =newParquetOutputFormat<LogLine>();//System.out.println("job write support - " +//        job.getConfiguration().get("parquet.write.support.class") +//        " job schema - " +  job.getConfiguration().get("parquet// .avro.schema"))  ;

    outputPairs.saveAsNewAPIHadoopFile(outputPath,//pathVoid.class,//key classLogLine.class,//value class
            pOutput.getClass(),//output format class
            job.getConfiguration());//configuration}

Example 9

Project: tajo   File: HiveCatalogStore.java View source code

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5 votes

@Overridepublicfinalvoid createTable(finalCatalogProtos.TableDescProto tableDescProto){HiveCatalogStoreClientPool.HiveCatalogStoreClient client =null;TableDesc tableDesc =newTableDesc(tableDescProto);String[] splitted =CatalogUtil.splitFQTableName(tableDesc.getName());String databaseName = splitted[0];String tableName = splitted[1];try{
    client = clientPool.getClient();

    org.apache.hadoop.hive.metastore.api.Table table =new org.apache.hadoop.hive.metastore.api.Table();
    table.setDbName(databaseName);
    table.setTableName(tableName);
    table.setParameters(newHashMap<>(tableDesc.getMeta().getOptions().getAllKeyValus()));// TODO: set owner//table.setOwner();StorageDescriptor sd =newStorageDescriptor();
    sd.setSerdeInfo(newSerDeInfo());
    sd.getSerdeInfo().setParameters(newHashMap<>());
    sd.getSerdeInfo().setName(table.getTableName());//If tableType is a managed-table, the location is hive-warehouse dir// and it will be wrong path in output committing
    table.setTableType(TableType.EXTERNAL_TABLE.name());
    table.putToParameters("EXTERNAL","TRUE");Path tablePath =newPath(tableDesc.getUri());FileSystem fs = tablePath.getFileSystem(conf);if(fs.isFile(tablePath)){
      LOG.warn("A table path is a file, but HiveCatalogStore does not allow a file path.");
      sd.setLocation(tablePath.getParent().toString());}else{
      sd.setLocation(tablePath.toString());}// set column informationList<Column> columns = tableDesc.getSchema().getRootColumns();ArrayList<FieldSchema> cols =newArrayList<>(columns.size());for(Column eachField : columns){
      cols.add(newFieldSchema(eachField.getSimpleName(),HiveCatalogUtil.getHiveFieldType(eachField.getDataType()),""));}
    sd.setCols(cols);// set partition keysif(tableDesc.hasPartition()&& tableDesc.getPartitionMethod().getPartitionType().equals(PartitionType.COLUMN)){List<FieldSchema> partitionKeys =newArrayList<>();for(Column eachPartitionKey : tableDesc.getPartitionMethod().getExpressionSchema().getRootColumns()){
        partitionKeys.add(newFieldSchema(eachPartitionKey.getSimpleName(),HiveCatalogUtil.getHiveFieldType(eachPartitionKey.getDataType()),""));}
      table.setPartitionKeys(partitionKeys);}if(tableDesc.getMeta().getDataFormat().equalsIgnoreCase(BuiltinStorages.RCFILE)){StorageFormatDescriptor descriptor = storageFormatFactory.get(IOConstants.RCFILE);
      sd.setInputFormat(descriptor.getInputFormat());
      sd.setOutputFormat(descriptor.getOutputFormat());String serde = tableDesc.getMeta().getOption(StorageConstants.RCFILE_SERDE);if(StorageConstants.DEFAULT_TEXT_SERDE.equals(serde)){
        sd.getSerdeInfo().setSerializationLib(ColumnarSerDe.class.getName());}else{
        sd.getSerdeInfo().setSerializationLib(LazyBinaryColumnarSerDe.class.getName());}if(tableDesc.getMeta().getOptions().containsKey(StorageConstants.RCFILE_NULL)){
        table.putToParameters(serdeConstants.SERIALIZATION_NULL_FORMAT,StringEscapeUtils.unescapeJava(tableDesc.getMeta().getOption(StorageConstants.RCFILE_NULL)));}}elseif(tableDesc.getMeta().getDataFormat().equals(BuiltinStorages.TEXT)){// TextFileStorageFormatDescriptor has deprecated class. so the class name set directly
      sd.setInputFormat(TextInputFormat.class.getName());
      sd.setOutputFormat(HiveIgnoreKeyTextOutputFormat.class.getName());
      sd.getSerdeInfo().setSerializationLib(LazySimpleSerDe.class.getName());String fieldDelimiter = tableDesc.getMeta().getOption(StorageConstants.TEXT_DELIMITER,StorageConstants.DEFAULT_FIELD_DELIMITER);// User can use an unicode for filed delimiter such as \u0001, \001.// In this case, java console will convert this value into "\\u001".// And hive will un-espace this value again.// As a result, user can use right field delimiter.// So, we have to un-escape this value.
      sd.getSerdeInfo().putToParameters(serdeConstants.SERIALIZATION_FORMAT,StringEscapeUtils.unescapeJava(fieldDelimiter));
      sd.getSerdeInfo().putToParameters(serdeConstants.FIELD_DELIM,StringEscapeUtils.unescapeJava(fieldDelimiter));
      table.getParameters().remove(StorageConstants.TEXT_DELIMITER);if(tableDesc.getMeta().containsOption(StorageConstants.TEXT_NULL)){
        table.putToParameters(serdeConstants.SERIALIZATION_NULL_FORMAT,StringEscapeUtils.unescapeJava(tableDesc.getMeta().getOption(StorageConstants.TEXT_NULL)));
        table.getParameters().remove(StorageConstants.TEXT_NULL);}}elseif(tableDesc.getMeta().getDataFormat().equalsIgnoreCase(BuiltinStorages.SEQUENCE_FILE)){StorageFormatDescriptor descriptor = storageFormatFactory.get(IOConstants.SEQUENCEFILE);
      sd.setInputFormat(descriptor.getInputFormat());
      sd.setOutputFormat(descriptor.getOutputFormat());String serde = tableDesc.getMeta().getOption(StorageConstants.SEQUENCEFILE_SERDE);if(StorageConstants.DEFAULT_TEXT_SERDE.equals(serde)){
        sd.getSerdeInfo().setSerializationLib(LazySimpleSerDe.class.getName());String fieldDelimiter = tableDesc.getMeta().getOption(StorageConstants.SEQUENCEFILE_DELIMITER,StorageConstants.DEFAULT_FIELD_DELIMITER);// User can use an unicode for filed delimiter such as \u0001, \001.// In this case, java console will convert this value into "\\u001".// And hive will un-espace this value again.// As a result, user can use right field delimiter.// So, we have to un-escape this value.
        sd.getSerdeInfo().putToParameters(serdeConstants.SERIALIZATION_FORMAT,StringEscapeUtils.unescapeJava(fieldDelimiter));
        sd.getSerdeInfo().putToParameters(serdeConstants.FIELD_DELIM,StringEscapeUtils.unescapeJava(fieldDelimiter));
        table.getParameters().remove(StorageConstants.SEQUENCEFILE_DELIMITER);}else{
        sd.getSerdeInfo().setSerializationLib(LazyBinarySerDe.class.getName());}if(tableDesc.getMeta().containsOption(StorageConstants.SEQUENCEFILE_NULL)){
        table.putToParameters(serdeConstants.SERIALIZATION_NULL_FORMAT,StringEscapeUtils.unescapeJava(tableDesc.getMeta().getOption(StorageConstants.SEQUENCEFILE_NULL)));
        table.getParameters().remove(StorageConstants.SEQUENCEFILE_NULL);}}elseif(tableDesc.getMeta().getDataFormat().equalsIgnoreCase(BuiltinStorages.PARQUET)){StorageFormatDescriptor descriptor = storageFormatFactory.get(IOConstants.PARQUET);
      sd.setInputFormat(descriptor.getInputFormat());
      sd.setOutputFormat(descriptor.getOutputFormat());
      sd.getSerdeInfo().setSerializationLib(descriptor.getSerde());if(tableDesc.getMeta().containsOption(ParquetOutputFormat.COMPRESSION)){
        table.putToParameters(ParquetOutputFormat.COMPRESSION,
            tableDesc.getMeta().getOption(ParquetOutputFormat.COMPRESSION));}}else{thrownewUnsupportedException(tableDesc.getMeta().getDataFormat()+" in HivecatalogStore");}

    sd.setSortCols(newArrayList<>());

    table.setSd(sd);
    client.getHiveClient().createTable(table);}catch(Throwable t){thrownewTajoInternalError(t);}finally{if(client !=null) client.release();}}

Example 10

Project: clickstream-tutorial   File: JavaSessionize.java View source code

Vote up

5 votes

publicstaticvoid main(String[] args)throwsException{if(args.length ==0){System.err.println("Usage: JavaSessionize <master> [input file]");System.exit(1);}String outputPath;if(args.length ==3){
        outputPath = args[2];}else{
        outputPath =newFile(temp,"output").getAbsolutePath();}System.out.println("Output:"+ outputPath);JavaSparkContext jsc =newJavaSparkContext(args[0],"JavaSessionize",System.getenv("SPARK_HOME"),JavaSparkContext.jarOfClass(JavaSessionize.class));JavaRDD<String> dataSet =(args.length ==2)? jsc.textFile(args[1]): jsc.parallelize(testLines);JavaPairRDD<String,SerializableLogLine> parsed = dataSet.mapToPair
            (newPairFunction<String,String,SerializableLogLine>(){@OverridepublicTuple2<String,SerializableLogLine> call(String s)throwsException{returnnewTuple2<String,SerializableLogLine>(getIP(s),
                            getFields(s));}});// This groups clicks by IP addressJavaPairRDD<String,Iterable<SerializableLogLine>> grouped = parsed
            .groupByKey();JavaPairRDD<String,Iterable<SerializableLogLine>> sessionized =
            grouped.mapValues(newFunction<Iterable<SerializableLogLine>,Iterable<SerializableLogLine>>(){@OverridepublicIterable<SerializableLogLine> call
                        (Iterable<SerializableLogLine> logLines)throwsException{return sessionize(logLines);}});

    sessionized.foreach(newVoidFunction<Tuple2<String,Iterable<SerializableLogLine>>>(){@Overridepublicvoid call(Tuple2<String,Iterable<SerializableLogLine>>
                                 stringListTuple2)throwsException{System.out.println("IP: "+ stringListTuple2._1());for(SerializableLogLine line : stringListTuple2._2()){System.out.println(line);}}});// right now sessionize is an RDD of pairs: <String,List<LogLine>>.// We want to output an RDD of <String,LogLine>// First, grab the Lists, then flatten them,// then pair them with something empty to make Hadoop happyJavaRDD<Iterable<SerializableLogLine>> nokeys = sessionized.map(newFunction<Tuple2<String,Iterable<SerializableLogLine>>,Iterable<SerializableLogLine>>(){@OverridepublicIterable<SerializableLogLine> call(Tuple2<String,Iterable<SerializableLogLine>> stringListTuple2)throwsException{return stringListTuple2._2();}});// @formatter:offJavaRDD<SerializableLogLine> flatLines = nokeys.flatMap(newFlatMapFunction<Iterable<SerializableLogLine>,SerializableLogLine>(){// @formatter:on@OverridepublicIterable<SerializableLogLine> call
                (Iterable<SerializableLogLine> serializableLogLines)throwsException{return serializableLogLines;}});JavaPairRDD<Void,SerializableLogLine> outputPairs = flatLines
            .mapToPair(newPairFunction<SerializableLogLine,Void,SerializableLogLine>(){@OverridepublicTuple2<Void,SerializableLogLine> call
                        (SerializableLogLine
                                 serializableLogLine)throwsException{returnnewTuple2<Void,SerializableLogLine>(null,
                            serializableLogLine);}});Job job =newJob();ParquetOutputFormat.setWriteSupportClass(job,AvroWriteSupport.class);AvroParquetOutputFormat.setSchema(job,LogLine.SCHEMA$);//dummy instance, because that's the only way to get the class of a// parameterized typeParquetOutputFormat<LogLine> pOutput =newParquetOutputFormat<LogLine>();//System.out.println("job write support - " +//        job.getConfiguration().get("parquet.write.support.class") +//        " job schema - " +  job.getConfiguration().get("parquet// .avro.schema"))  ;

    outputPairs.saveAsNewAPIHadoopFile(outputPath,//pathVoid.class,//key classLogLine.class,//value class
            pOutput.getClass(),//output format class
            job.getConfiguration());//configuration}

 

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