java - 带Avro的Mapreduce-通用解析

Question

问题陈述:

hdfs中可用avro格式的数据。

上面的avro数据的

模式也可用。

需要在map reduce中解析此Avro数据，并以相同的架构生成输出avro数据(需要清除传入的Avro数据)。

输入的avro数据可以是任何模式。

因此，要求编写一种通用映射表，该映射表可以获取任何Avro数据，但以Avro格式生成输出，并具有与传入相同的模式。

代码(经过多次尝试，这是我到达的距离)

驱动程序

public class AvroDriver extends Configured implements Tool {

    public int run(String[] args) throws Exception {
        Job job = new Job(getConf());
        job.setJarByClass(AvroMapper.class);
        job.setJobName("Avro With Xml Mapper");
        job.getConfiguration().setBoolean("mapreduce.input.fileinputformat.input.dir.recursive", true);

        //This is required to use avro-1.7.6 and above
        job.getConfiguration().set("mapreduce.job.user.classpath.first", "true");
        FileInputFormat.addInputPath(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        job.setInputFormatClass(AvroKeyInputFormat.class);
        job.setMapperClass(AvroMapper.class);
        Schema schema = new Schema.Parser().parse(new File(args[2]));
        AvroJob.setInputKeySchema(job, schema);
        job.setOutputFormatClass(AvroKeyOutputFormat.class);
        job.setMapOutputKeyClass(AvroKey.class);
        AvroJob.setOutputKeySchema(job, schema);
        job.setNumReduceTasks(0);
        return (job.waitForCompletion(true) ? 0 : 1);
    }

    public static void main(String[] args) throws Exception {
        int res = ToolRunner.run(new AvroDriver(), args);
        System.exit(res);
    }
}

映射器

public static class AvroMapper extends Mapper<AvroKey<GenericData.Record>, NullWritable, AvroKey<GenericData>, NullWritable> {

        @Override
        public void map(AvroKey<GenericData.Record> key, NullWritable value, Context context) throws IOException, InterruptedException {

            try {
                System.out.println("Specific Record - " + key);
                System.out.println("Datum :: " + key.datum());
                System.out.println("Schema :: " + key.datum().getSchema());
                List<Field> fields = key.datum().getSchema().getFields();


                GenericRecord record = new GenericData.Record(key.datum().getSchema());
                for(Field f : fields) {
                    System.out.println("Field Name - " + f.name());
                    record.put(f.name(), key.datum().get(f.name()));
                }
                System.out.println("Record - " + record);
                GenericData d = new GenericData();
                d.newRecord(record, key.datum().getSchema());
                AvroKey<GenericData> outkey = new AvroKey<GenericData>(d);

                System.out.println("Generic Record (Avro Key) - " + outkey);
                context.write(outkey, NullWritable.get());
            } catch (Exception e) {
                e.printStackTrace();
                throw new IOException(e.getMessage());
            }
        }
    }

命令

hadoop jar $jar_name $input_avro_data_path $output_path $path_to_the_input_avro_schema

Avro模式样本

{ "type" : "record", "name" : "Entity", "namespace" : "com.sample.avro", "fields".......

我在运行 map 时遇到的问题减少了

Error running child : java.lang.NullPointerException: in com.sample.avro.Entity null of com.sample.avro.Entity

org.apache.avro.file.DataFileWriter$AppendWriteException: java.lang.NullPointerException: in com.sample.avro.Entity null of com.sample.avro.Entity

环境

HDP 2.3沙箱

有什么想法吗？

更新了

我尝试了以下但相同的结果

public static class AvroMapper extends Mapper<AvroKey<GenericData.Record>, NullWritable, AvroKey<GenericData>, NullWritable> {

        @Override
        public void map(AvroKey<GenericData.Record> key, NullWritable value, Context context) throws IOException, InterruptedException {

            try {
                System.out.println("Specific Record - " + key);
                System.out.println("Datum :: " + key.datum());
                System.out.println("Schema :: " + key.datum().getSchema());
                List<Field> fields = key.datum().getSchema().getFields();

                Schema s = Schema.createRecord(key.datum().getSchema().getName(), null, key.datum().getSchema().getNamespace(), false);
                List<Field> outFields  = new ArrayList<Field>();
                for(Field f : fields) {
                    System.out.println("Field Name - " + f.name());
                    Schema.Field f1 = new Schema.Field(f.name(),Schema.create(Schema.Type.STRING), null,null);
                    outFields.add(f1);
                }
                s.setFields(outFields);

                System.out.println("Out Schema - " + s);
                GenericRecord record = new GenericData.Record(s);
                for(Field f : fields) {
                    record.put(f.name(), key.datum().get(f.name()));
                }
                System.out.println("Record - " + record);
                GenericData d = new GenericData();
                d.newRecord(record, s);
                AvroKey<GenericData> outkey = new AvroKey<GenericData>(d);
                System.out.println("Generic Record (Avro Key) - " + outkey.datum());
                context.write(outkey, NullWritable.get());
            } catch (Exception e) {
                e.printStackTrace();
            }

        }
    }

请注意，将 map 输入的Avro效果很好，但是此处出现的是Avro格式的输出。

Answer 1

最后，我找到了答案和映射器代码，如下所示。
我没有使用GenericData发出AvroKey，而是更改为发出GenericData.Record。

public static class AvroMapper extends Mapper<AvroKey<GenericData.Record>, NullWritable, AvroKey<GenericData.Record>, NullWritable> {

        @Override
        public void map(AvroKey<GenericData.Record> key, NullWritable value, Context context) throws IOException, InterruptedException {

            try {
                System.out.println("Specific Record - " + key);
                System.out.println("Datum :: " + key.datum());
                System.out.println("Schema :: " + key.datum().getSchema());
                List<Field> fields = key.datum().getSchema().getFields();

                Schema s = Schema.createRecord(key.datum().getSchema().getName(), null, key.datum().getSchema().getNamespace(), false);
                List<Field> outFields  = new ArrayList<Field>();
                for(Field f : fields) {
                    System.out.println("Field Name - " + f.name());
                    Schema.Field f1 = new Schema.Field(f.name(),Schema.create(Schema.Type.STRING), null,null);
                    outFields.add(f1);
                }
                s.setFields(outFields);

                System.out.println("Out Schema - " + s);
                GenericData.Record record = new GenericData.Record(s);
                for(Field f : fields) {
                    record.put(f.name(), key.datum().get(f.name()));
                }
                System.out.println("Record - " + record);
                AvroKey<GenericData.Record> outkey = new AvroKey<GenericData.Record>(record);
                System.out.println("Generic Record (Avro Key) - " + outkey.datum());
                context.write(outkey, NullWritable.get());
            } catch (Exception e) {
                e.printStackTrace();
                System.out.println(e);
                System.out.println(e.getMessage());
                throw new IOException(e.getMessage());
            }
        }
    }