在mapreduce中使用Parquet,根据不同的序列化方式,有不同的选择,下面以Avro为例:
使用 AvroParquetInputFormat 和 AvroParquetOutputFormat
@Override
public int run(String[] strings)throws Exception {
Path inputPath =new Path(strings[0]);
Path outputPath =new Path(strings[1]);
Job job = Job.getInstance(getConf(),"AvroParquetMapReduce");
job.setJarByClass(getClass());
job.setInputFormatClass(AvroParquetInputFormat.class);
AvroParquetInputFormat.setInputPaths(job,inputPath);
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
job.setOutputFormatClass(AvroParquetOutputFormat.class);
FileOutputFormat.setOutputPath(job,outputPath);
AvroParquetOutputFormat.setSchema(job,StockAvg.SCHEMA$);return job.waitForCompletion(true) ?0 :1;
}
staticclassMapextendsMapper<Void,Stock,Text,DoubleWritable>{@Overrideprotected void map(Void key, Stock value, Context context)throws IOException, InterruptedException {
context.write(new Text(value.getSymbol().toString()),new DoubleWritable(value.getOpen()));
}
}
staticclassReduceextendsReducer<Text,DoubleWritable,Void,StockAvg> {@Overrideprotected void reduce(Text key, Iterable<DoubleWritable> values, Context context)throws IOException, InterruptedException {
Mean mean =new Mean();for (DoubleWritableval :values){
mean.increment(val.get());
}
StockAvg avg =new StockAvg();
avg.setSymbol(key.toString());
avg.setAvg(mean.getResult());
context.write(null,avg);
}
}
这里的输入输出都是 Parquet文件。如果向输入是Text文件,只要不设置InputFormatClass即可。
如果改变input schema文件,Avro不能加载具体的class,会强制使用GenericData代替。
publicclassAvroProjectionParquetMapReduceextendsConfiguredimplementsTool {publicstaticvoid main(String[] args) throws Exception {
args =new String[2];
args[0] ="hdfs://hadoop:9000/user/madong/parquet-input";
args[1] ="hdfs://hadoop:9000/user/madong/parquet-output";int code = ToolRunner.run(new AvroProjectionParquetMapReduce(),args);
System.exit(code);
}
@Overridepublicint run(String[] strings) throws Exception {
Path inputPath =new Path(strings[0]);
Path outputPath =new Path(strings[1]);
Job job = Job.getInstance(getConf(),"AvroProjectionParquetMapReduce");
job.setJarByClass(AvroProjectionParquetMapReduce.class);
job.setInputFormatClass(AvroParquetInputFormat.class);
AvroParquetInputFormat.setInputPaths(job, inputPath);// predicate pushdown
AvroParquetInputFormat.setUnboundRecordFilter(job, GoogleStockFilter.class);// projection pushdown
Schema projection = Schema.createRecord(Stock.SCHEMA$.getName(),
Stock.SCHEMA$.getDoc(), Stock.SCHEMA$.getNamespace(),false);
List<Schema.Field> fields = Lists.newArrayList();for (Schema.Field field : Stock.SCHEMA$.getFields()) {if ("symbol".equals(field.name()) ||"open".equals(field.name())) {
fields.add(new Schema.Field(field.name(), field.schema(), field.doc(),
field.defaultValue(), field.order()));
}
}
projection.setFields(fields);
AvroParquetInputFormat.setRequestedProjection(job, projection);
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(DoubleWritable.class);
job.setOutputFormatClass(AvroParquetOutputFormat.class);
FileOutputFormat.setOutputPath(job, outputPath);
AvroParquetOutputFormat.setSchema(job, StockAvg.SCHEMA$);return job.waitForCompletion(true) ?0 :1;
}publicstaticclassGoogleStockFilterimplementsUnboundRecordFilter {privatefinal UnboundRecordFilter filter;public GoogleStockFilter() {
filter = ColumnRecordFilter.column("symbol", ColumnPredicates.equalTo("GOOG"));
}
@Overridepublic RecordFilter bind(Iterable<ColumnReader> readers) {return filter.bind(readers);
}
}staticclassMapextendsMapper<Void,Stock,Text,DoubleWritable> {
@Overrideprotectedvoid map(Void key, Stock value, Context context) throws IOException, InterruptedException {if (value !=null) {
context.write(new Text(value.getSymbol().toString()),new DoubleWritable(value.getOpen()));
}
}
}staticclassReduceextendsReducer<Text,DoubleWritable,Void,StockAvg> {
@Overrideprotectedvoid reduce(Text key, Iterable<DoubleWritable> values, Context context) throws IOException, InterruptedException {
Mean mean =new Mean();for (DoubleWritable val :values){
mean.increment(val.get());
}
StockAvgavg =new StockAvg();avg.setSymbol(key.toString());avg.setAvg(mean.getResult());
context.write(null,avg);
}
}
}