Hadoop-TsFile

About Hadoop-TsFile-Connector

TsFile-Hadoop-Connector implements the support of Hadoop for external data sources of Tsfile type. This enables users to read, write and query Tsfile by Hadoop.

With this connector, you can

• load a single TsFile, from either the local file system or hdfs, into Hadoop
• load all files in a specific directory, from either the local file system or hdfs, into hadoop
• write data from Hadoop into TsFile

System Requirements

Hadoop Version	Java Version	TsFile Version
2.7.3	1.8	1.0.0

Note: For more information about how to download and use TsFile, please see the following link: https://github.com/apache/iotdb/tree/master/tsfile.

Data Type Correspondence

TsFile data type	Hadoop writable
BOOLEAN	BooleanWritable
INT32	IntWritable
INT64	LongWritable
FLOAT	FloatWritable
DOUBLE	DoubleWritable
TEXT	Text

TSFInputFormat Explanation

TSFInputFormat extract data from tsfile and format them into records of MapWritable.

Suppose that we want to extract data of the device named d1 which has three sensors named s1, s2, s3.

s1's type is BOOLEAN, s2's type is DOUBLE, s3's type is TEXT.

The MapWritable struct will be like:

{
    "time_stamp": 10000000,
    "device_id":  d1,
    "s1":         true,
    "s2":         3.14,
    "s3":         "middle"
}

In the Map job of Hadoop, you can get any value you want by key as following:

mapwritable.get(new Text("s1"))

Note: All keys in MapWritable are Text type.

Examples

Read Example: calculate the sum

First of all, we should tell InputFormat what kind of data we want from tsfile.

    // configure reading time enable
    TSFInputFormat.setReadTime(job, true); 
    // configure reading deviceId enable
    TSFInputFormat.setReadDeviceId(job, true); 
    // configure reading which deltaObjectIds
    String[] deviceIds = {"device_1"};
    TSFInputFormat.setReadDeviceIds(job, deltaObjectIds);
    // configure reading which measurementIds
    String[] measurementIds = {"sensor_1", "sensor_2", "sensor_3"};
    TSFInputFormat.setReadMeasurementIds(job, measurementIds);

And then,the output key and value of mapper and reducer should be specified

    // set inputformat and outputformat
    job.setInputFormatClass(TSFInputFormat.class);
    // set mapper output key and value
    job.setMapOutputKeyClass(Text.class);
    job.setMapOutputValueClass(DoubleWritable.class);
    // set reducer output key and value
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(DoubleWritable.class);

Then, the mapper and reducer class is how you deal with the MapWritable produced by TSFInputFormat class.

  public static class TSMapper extends Mapper<NullWritable, MapWritable, Text, DoubleWritable> {

    @Override
    protected void map(NullWritable key, MapWritable value,
        Mapper<NullWritable, MapWritable, Text, DoubleWritable>.Context context)
        throws IOException, InterruptedException {

      Text deltaObjectId = (Text) value.get(new Text("device_id"));
      context.write(deltaObjectId, (DoubleWritable) value.get(new Text("sensor_3")));
    }
  }

  public static class TSReducer extends Reducer<Text, DoubleWritable, Text, DoubleWritable> {

    @Override
    protected void reduce(Text key, Iterable<DoubleWritable> values,
        Reducer<Text, DoubleWritable, Text, DoubleWritable>.Context context)
        throws IOException, InterruptedException {

      double sum = 0;
      for (DoubleWritable value : values) {
        sum = sum + value.get();
      }
      context.write(key, new DoubleWritable(sum));
    }
  }

Note: For the complete code, please see the following link: https://github.com/apache/iotdb/blob/master/example/hadoop/src/main/java/org/apache/iotdb//hadoop/tsfile/TSFMRReadExample.java

Write Example: write the average into Tsfile

Except for the OutputFormatClass, the rest of configuration code for hadoop map-reduce job is almost same as above.

   job.setOutputFormatClass(TSFOutputFormat.class);
   // set reducer output key and value
   job.setOutputKeyClass(NullWritable.class);
   job.setOutputValueClass(HDFSTSRecord.class);

Then, the mapper and reducer class is how you deal with the MapWritable produced by TSFInputFormat class.

    public static class TSMapper extends Mapper<NullWritable, MapWritable, Text, MapWritable> {
        @Override
        protected void map(NullWritable key, MapWritable value,
                           Mapper<NullWritable, MapWritable, Text, MapWritable>.Context context)
                throws IOException, InterruptedException {

            Text deltaObjectId = (Text) value.get(new Text("device_id"));
            long timestamp = ((LongWritable)value.get(new Text("timestamp"))).get();
            if (timestamp % 100000 == 0) {
                context.write(deltaObjectId, new MapWritable(value));
            }
        }
    }

    /**
     * This reducer calculate the average value.
     */
    public static class TSReducer extends Reducer<Text, MapWritable, NullWritable, HDFSTSRecord> {

        @Override
        protected void reduce(Text key, Iterable<MapWritable> values,
                              Reducer<Text, MapWritable, NullWritable, HDFSTSRecord>.Context context) throws IOException, InterruptedException {
            long sensor1_value_sum = 0;
            long sensor2_value_sum = 0;
            double sensor3_value_sum = 0;
            long num = 0;
            for (MapWritable value : values) {
                num++;
                sensor1_value_sum += ((LongWritable)value.get(new Text("sensor_1"))).get();
                sensor2_value_sum += ((LongWritable)value.get(new Text("sensor_2"))).get();
                sensor3_value_sum += ((DoubleWritable)value.get(new Text("sensor_3"))).get();
            }
            HDFSTSRecord tsRecord = new HDFSTSRecord(1L, key.toString());
            DataPoint dPoint1 = new LongDataPoint("sensor_1", sensor1_value_sum / num);
            DataPoint dPoint2 = new LongDataPoint("sensor_2", sensor2_value_sum / num);
            DataPoint dPoint3 = new DoubleDataPoint("sensor_3", sensor3_value_sum / num);
            tsRecord.addTuple(dPoint1);
            tsRecord.addTuple(dPoint2);
            tsRecord.addTuple(dPoint3);
            context.write(NullWritable.get(), tsRecord);
        }
    }

Note: For the complete code, please see the following link: https://github.com/apache/iotdb/blob/master/example/hadoop/src/main/java/org/apache/iotdb//hadoop/tsfile/TSMRWriteExample.java