So the correct call should be: String valueString = new String(valueText.getBytes(), 0, valueText.getLength(), "UTF-8");
Cheers On Tue, Jul 20, 2010 at 9:23 AM, Jeff Bean <[email protected]> wrote: > data.length is the length of the byte array. > > Text.getLength() most likely returns a different value than > getBytes.length. > > Hadoop reuses box class objects like Text, so what it's probably doing is > writing over the byte array, lengthening it as necessary, and just updating > a separate length attribute. > > Jeff > > On Tue, Jul 20, 2010 at 8:56 AM, Ted Yu <[email protected]> wrote: > > > Interesting. > > String class is able to handle this scenario: > > > > 348 public String(byte[] data, String encoding) throws > > UnsupportedEncodingException { > > 349 this(data, 0, data.length, encoding); > > 350 } > > > > > > > > On Tue, Jul 20, 2010 at 6:01 AM, Jeff Bean <[email protected]> wrote: > > > > > I think the problem is here: > > > > > > String valueString = new String(valueText.getBytes(), "UTF-8"); > > > > > > Javadoc for Text says: > > > > > > *getBytes< > > > > > > http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/io/Text.html#getBytes%28%29 > > > > > > > *() > > > Returns the raw bytes; however, only data up to > > > getLength()< > > > > > > http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/io/Text.html#getLength%28%29 > > > >is > > > valid. > > > > > > So try getting the length, truncating the byte array at the value > > returned > > > by getLength() and THEN converting it to a String. > > > > > > Jeff > > > > > > On Mon, Jul 19, 2010 at 9:08 AM, Ted Yu <[email protected]> wrote: > > > > > > > For your initial question on Text.set(). > > > > Text.setCapacity() allocates new byte array. Since keepData is false, > > old > > > > data wouldn't be copied over. > > > > > > > > On Mon, Jul 19, 2010 at 8:01 AM, Peter Minearo < > > > > [email protected]> wrote: > > > > > > > > > I am already using XmlInputFormat. The input into the Map phase is > > not > > > > > the problem. The problem lays in between the Map and Reduce phase. > > > > > > > > > > BTW - The article is correct. DO NOT USE StreamXmlRecordReader. > > > > > XmlInputFormat is a lot faster. From my testing, > > StreamXmlRecordReader > > > > > took 8 minutes to read a 1 GB XML document; where as, > XmlInputFormat > > > was > > > > > under 2 minutes. (Using 2 Core, 8GB machines) > > > > > > > > > > > > > > > -----Original Message----- > > > > > From: Ted Yu [mailto:[email protected]] > > > > > Sent: Friday, July 16, 2010 9:44 PM > > > > > To: [email protected] > > > > > Subject: Re: Hadoop and XML > > > > > > > > > > From an earlier post: > > > > > > > http://oobaloo.co.uk/articles/2010/1/20/processing-xml-in-hadoop.html > > > > > > > > > > On Fri, Jul 16, 2010 at 3:07 PM, Peter Minearo < > > > > > [email protected]> wrote: > > > > > > > > > > > Moving the variable to a local variable did not seem to work: > > > > > > > > > > > > > > > > > > </PrivateRateSet>vateRateSet> > > > > > > > > > > > > > > > > > > > > > > > > public void map(Object key, Object value, OutputCollector output, > > > > > > Reporter > > > > > > reporter) throws IOException { > > > > > > Text valueText = (Text)value; > > > > > > String valueString = new > > String(valueText.getBytes(), > > > > > > "UTF-8"); > > > > > > String keyString = getXmlKey(valueString); > > > > > > Text returnKeyText = new Text(); > > > > > > Text returnValueText = new Text(); > > > > > > returnKeyText.set(keyString); > > > > > > returnValueText.set(valueString); > > > > > > output.collect(returnKeyText, returnValueText); } > > > > > > > > > > > > -----Original Message----- > > > > > > From: Peter Minearo [mailto:[email protected]] > > > > > > Sent: Fri 7/16/2010 2:51 PM > > > > > > To: [email protected] > > > > > > Subject: RE: Hadoop and XML > > > > > > > > > > > > Whoops....right after I sent it and someone else made a > suggestion; > > I > > > > > > realized what question 2 was about. I can try that, but wouldn't > > > that > > > > > > > > > > > cause Object bloat? During the Hadoop training I went through; > it > > > was > > > > > > > > > > > mentioned to reuse the returning Key and Value objects to keep > the > > > > > > number of Objects created down to a minimum. Is this not really > a > > > > > > valid point? > > > > > > > > > > > > > > > > > > > > > > > > -----Original Message----- > > > > > > From: Peter Minearo [mailto:[email protected]] > > > > > > Sent: Friday, July 16, 2010 2:44 PM > > > > > > To: [email protected] > > > > > > Subject: RE: Hadoop and XML > > > > > > > > > > > > > > > > > > I am not using multi-threaded Map tasks. Also, if I understand > > your > > > > > > second question correctly: > > > > > > "Also can you try creating the output key and values in the map > > > > > > method(method lacal) ?" > > > > > > In the first code snippet I am doing exactly that. > > > > > > > > > > > > Below is the class that runs the Job. > > > > > > > > > > > > public class HadoopJobClient { > > > > > > > > > > > > private static final Log LOGGER = > > > > > > LogFactory.getLog(Prds.class.getName()); > > > > > > > > > > > > public static void main(String[] args) { > > > > > > JobConf conf = new JobConf(Prds.class); > > > > > > > > > > > > conf.set("xmlinput.start", "<PrivateRateSet>"); > > > > > > conf.set("xmlinput.end", "</PrivateRateSet>"); > > > > > > > > > > > > conf.setJobName("PRDS Parse"); > > > > > > > > > > > > conf.setOutputKeyClass(Text.class); > > > > > > conf.setOutputValueClass(Text.class); > > > > > > > > > > > > conf.setMapperClass(PrdsMapper.class); > > > > > > conf.setReducerClass(PrdsReducer.class); > > > > > > > > > > > > conf.setInputFormat(XmlInputFormat.class); > > > > > > conf.setOutputFormat(TextOutputFormat.class); > > > > > > > > > > > > FileInputFormat.setInputPaths(conf, new > > > Path(args[0])); > > > > > > FileOutputFormat.setOutputPath(conf, new > > > > > > Path(args[1])); > > > > > > > > > > > > // Run the job > > > > > > try { > > > > > > JobClient.runJob(conf); > > > > > > } catch (IOException e) { > > > > > > LOGGER.error(e.getMessage(), e); > > > > > > } > > > > > > > > > > > > } > > > > > > > > > > > > > > > > > > } > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -----Original Message----- > > > > > > From: Soumya Banerjee [mailto:[email protected]] > > > > > > Sent: Fri 7/16/2010 2:29 PM > > > > > > To: [email protected] > > > > > > Subject: Re: Hadoop and XML > > > > > > > > > > > > Hi, > > > > > > > > > > > > Can you please share the code of the job submission client ? > > > > > > > > > > > > Also can you try creating the output key and values in the map > > > > > > method(method > > > > > > lacal) ? > > > > > > Make sure you are not using multi threaded map task > configuration. > > > > > > > > > > > > map() > > > > > > { > > > > > > private Text keyText = new Text(); > > > > > > private Text valueText = new Text(); > > > > > > > > > > > > //rest of the code > > > > > > } > > > > > > > > > > > > Soumya. > > > > > > > > > > > > On Sat, Jul 17, 2010 at 2:30 AM, Peter Minearo < > > > > > > [email protected]> wrote: > > > > > > > > > > > > > I have an XML file that has sparse data in it. I am running a > > > > > > > MapReduce Job that reads in an XML file, pulls out a Key from > > > within > > > > > > > > > > > > the XML snippet and then hands back the Key and the XML snippet > > (as > > > > > > > the Value) to the OutputCollector. The reason is to sort the > > file > > > > > > back into order. > > > > > > > Below is the snippet of code. > > > > > > > > > > > > > > public class XmlMapper extends MapReduceBase implements Mapper > { > > > > > > > > > > > > > > private Text keyText = new Text(); > > > > > > > private Text valueText = new Text(); > > > > > > > > > > > > > > @SuppressWarnings("unchecked") > > > > > > > public void map(Object key, Object value, OutputCollector > > output, > > > > > > > Reporter reporter) throws IOException { Text valueText = > > > > > > > (Text)value; > > > > > > > > > > > > > String valueString = new String(valueText.getBytes(), "UTF-8"); > > > > > > > String keyString = getXmlKey(valueString); > > > > > > > getKeyText().set(keyString); getValueText().set(valueString); > > > > > > > output.collect(getKeyText(), getValueText()); } > > > > > > > > > > > > > > > > > > > > > public Text getKeyText() { > > > > > > > return keyText; > > > > > > > } > > > > > > > > > > > > > > > > > > > > > public void setKeyText(Text keyText) { this.keyText = > keyText; > > } > > > > > > > > > > > > > > > > > > > > > public Text getValueText() { > > > > > > > return valueText; > > > > > > > } > > > > > > > > > > > > > > > > > > > > > public void setValueText(Text valueText) { this.valueText = > > > > > > > valueText; } > > > > > > > > > > > > > > > > > > > > > private String getXmlKey(String value) { > > > > > > > // Get the Key from the XML in the value. > > > > > > > } > > > > > > > > > > > > > > } > > > > > > > > > > > > > > The XML snippet from the Value is fine when it is passed into > the > > > > > > > map() method. I am not changing any data either, just pulling > > out > > > > > > > information for the key. The problem I am seeing is between > the > > > Map > > > > > > > > > > > > phase and the Reduce phase, the XML is getting munged. For > > > Example: > > > > > > > > > > > > > > </PrivateRate> > > > > > > > </PrivateRateSet>te> > > > > > > > > > > > > > > It is my understanding that Hadoop uses the same instance of > the > > > Key > > > > > > > > > > > > and Value object when calling the Map method. What changes is > > the > > > > > > > data within those instances. So, I ran an experiment where I > do > > > not > > > > > > > > > > > > have different Key or Value Text Objects. I reuse the ones > > passed > > > > > > > into the method, like below: > > > > > > > > > > > > > > public class XmlMapper extends MapReduceBase implements Mapper > { > > > > > > > > > > > > > > @SuppressWarnings("unchecked") > > > > > > > public void map(Object key, Object value, OutputCollector > > output, > > > > > > > Reporter reporter) throws IOException { Text keyText = > > (Text)key; > > > > > > > Text valueText = (Text)value; String valueString = new > > > > > > > String(valueText.getBytes(), "UTF-8"); String keyString = > > > > > > > getXmlKey(valueString); keyText.set(keyString); > > > > > > > valueText.set(valueString); output.collect(keyText, > valueText); > > } > > > > > > > > > > > > > > > > > > > > > private String getXmlKey(String value) { > > > > > > > // Get the Key from the XML in the value. > > > > > > > } > > > > > > > > > > > > > > } > > > > > > > > > > > > > > What was interesting about this is the fact that the XML was > > > getting > > > > > > > > > > > > munged within the Map Phase. When I changed over to the code > at > > > the > > > > > > > > > > > > top, the Map phase was fine. However, the Reduce phase picks > up > > > the > > > > > > > > > > > > munged XML. Trying to debug the problem, I came across this > > method > > > > > > > in > > > > > > > > > > > > > the Text Object: > > > > > > > > > > > > > > public void set(byte[] utf8, int start, int len) { > > > > > > > setCapacity(len, false); > > > > > > > System.arraycopy(utf8, start, bytes, 0, len); > > > > > > > this.length = len; > > > > > > > } > > > > > > > > > > > > > > If the "bytes" array had a length of 1000 and the "utf8" array > > has > > > a > > > > > > > > > > > > length of 500; doing a System.arraycopy() would only copy the > > first > > > > > > > 500 from "utf8" to "bytes" but leave the last 500 in "bytes" > > alone. > > > > > > > Could this be the cause of the XML munging? > > > > > > > > > > > > > > All of this leads me to a few questions: > > > > > > > > > > > > > > 1) Has anyone successfully used XML snippets as the data format > > > > > > > within > > > > > > > > > > > > > a MapReduce job; not just reading from the file but used during > > the > > > > > > > shuffle? > > > > > > > 2) Is anyone seeing this problem with XML or any other format? > > > > > > > 3) Does anyone know what is going on? > > > > > > > 4) Is this a bug? > > > > > > > > > > > > > > > > > > > > > Thanks, > > > > > > > > > > > > > > Peter > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >
