The Hortonworks Community Connection is now live. A completely rebuilt Q&A forum, Knowledge Base, Code Hub and more, backed by the experts in the industry.

You will be redirected here in 10 seconds. If your are not redirected, click here to visit the new site.

The legacy Hortonworks Forum is now closed. You can view a read-only version of the former site by clicking here. The site will be taken offline on January 31,2016

MapReduce Forum

Data type for precision – BigDecimal?

  • #49504
    Marco Shaw
    Participant

    **NOVICE**

    I’m playing around with some pretty simple data, but I’m struggling a bit. I’m basically pulling out a text and dollar amount field to work on sales calculations.

    My output ends up looking like this:

    San Jose 9936721.410000008
    Santa Ana 1.0050309929999959E7

    So I have a problem with precision and how the data is outputted.

    What I’ve read seems to suggest that BigDecimal is the data type I should be using for currency, but I’m struggling just a big with how to take that type and convert it into one of the Writable classes. Which Writable class should I be using? Should I be doing my calculations using BigDecimal, and then writing out the K,V as Text?

    My mapper:

    public class TotalSalesMapper extends
    	Mapper<LongWritable, Text, Text, LongWritable> {
    
    	@Override
    	public void map(LongWritable key, Text value, Context context)
        	throws IOException, InterruptedException {
    
    		String data[] = value.toString().split("\t");
    
    		if (data.length == 6) {
    			String store = data[2];
    			double cost = Double.parseDouble(data[4]);
    			//BigDecimal cost = new BigDecimal(data[4]);
    			context.write(new Text(store), new LongWritable(cost));
    		}
    		
    	}
    
    }

    My reducer:

    public class TotalSalesReducer extends
    	Reducer<Text, DoubleWritable, Text, DoubleWritable> {
    
    	@Override
    	public void reduce(Text key, Iterable<DoubleWritable> values, Context
            context)
            throws IOException, InterruptedException {
    
    		double sum = Double.MIN_VALUE;
    		for (DoubleWritable value: values) {
    		//while (values.hasNext()) {
    			sum += value.get();
    			//sum += values.next().get();
    		}
    		context.write(key, new DoubleWritable(sum));
    	}
    }

The forum ‘MapReduce’ is closed to new topics and replies.

Support from the Experts

A HDP Support Subscription connects you experts with deep experience running Apache Hadoop in production, at-scale on the most demanding workloads.

Enterprise Support »

Become HDP Certified

Real world training designed by the core architects of Hadoop. Scenario-based training courses are available in-classroom or online from anywhere in the world

Training »

Hortonworks Data Platform
The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly enterprise grade having been built, tested and hardened with enterprise rigor.
Get started with Sandbox
Hortonworks Sandbox is a self-contained virtual machine with Apache Hadoop pre-configured alongside a set of hands-on, step-by-step Hadoop tutorials.
Modern Data Architecture
Tackle the challenges of big data. Hadoop integrates with existing EDW, RDBMS and MPP systems to deliver lower cost, higher capacity infrastructure.