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From Apache Wiki <wikidi...@apache.org>
Subject [Hadoop Wiki] Update of "Sending_information_to_Chukwa" by AriRabkin
Date Tue, 10 Nov 2009 22:30:40 GMT
Dear Wiki user,

You have subscribed to a wiki page or wiki category on "Hadoop Wiki" for change notification.

The "Sending_information_to_Chukwa" page has been changed by AriRabkin.
The comment on this change is: move demux stuff to new page.
http://wiki.apache.org/hadoop/Sending_information_to_Chukwa?action=diff&rev1=3&rev2=4

--------------------------------------------------

        * Where <fileName> is the local path on your machine
     1. Close the socket
  
- 
- == Extract information from this new dataSource ==
- 
- === Using the default TimeStamp Parser ===
- 
- By default, Chukwa will use the default TsProcessor. 
- 
- This parser will try to extract the real log statement from the log entry using the %d{ISO8601}
date format.
- If it fails, it will use the time at which the chunk as been written to disk (collector
timestamp).
- 
- Your log will be automatically available from the Web Log viewer under the <YourRecordTypeHere>
directory 
-  
- === Using a specific Parser ===
- If you want to extract some specific information and perform more processing you need to
write your own parser.
- Like any M/R program, your have to write at least the Map side for your parser. The reduce
side is Identity by default.
- 
- ==== MAP side of the parser ====
- Your can write your own parser from scratch or extend the AbstractProcessor class that hides
all the low level action on the chunk.
- Then you have to register your parser to the demux (link between the RecordType and the
parser)
- 
- ==== Parser registration ====
-    * Edit ${CHUKWA_HOME}/conf/chukwa-demux-conf.xml and add the following lines
- 
-    <property>
-     <name><YourRecordType_Here></name>
-     <value><org.apache.hadoop.chukwa.extraction.demux.processor.mapper.MyParser></value>
-     <description>Parser class for <YourRecordType_Here></description>
-    </property>
- 
- (Tips: You can use the same parser for different recordType)
- 
- ==== Parser implementation ====
- 
- {{{#!java
- 
- public class MyParser extends AbstractProcessor
- {
-        protected void parse(String recordEntry,
- 			               OutputCollector<ChukwaRecordKey, ChukwaRecord> output,
- 			               Reporter reporter)
- 	{
- 
-            // Extract Log4j information, i.e timestamp, logLevel, logger, ...
-            SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm");
-            // Extract log timestamp & Log4j information
-            String dStr = recordEntry.substring(0, 23);
-            int start = 24;
-            int idx = recordEntry.indexOf(' ', start);
-            String logLevel = recordEntry.substring(start, idx);
-            start = idx + 1;
-            idx = recordEntry.indexOf(' ', start);
-            String className = recordEntry.substring(start, idx-1);
-            String body = recordEntry.substring(idx + 1);
- 
-            Date d = sdf.parse(dStr);
-            key = new ChukwaRecordKey();
-            record = new ChukwaRecord();
- 
-            key = new ChukwaRecordKey();
-            key.setKey("<YOUR_KEY_HERE>"));
-            key.setReduceType("<YOUR_RECORD_TYPE_HERE>");
-            
-            record = new ChukwaRecord();
-            record.setTime(d.getTime());
- 
-            // Parse your line here and extract useful information
-            // Add your {key,value} pairs
-            record.add(key1, value1);
-            record.add(key2, value2);
-            record.add(key3, value3);
- 
-            // Output your record
-            output.collect(key, record);
-         }
- }
- 
- 
- }}}
- 
- (Tips: see org.apache.hadoop.chukwa.extraction.demux.processor.mapper.Df class, for an example
of Parser class)
- 
- ==== REDUCE side of the parser ====
- You only need to implement a reduce side if you need to group records together.
- Here the interface that your need to implement:
- 
- The link between the Map side and the reduce is done by setting your reduce class into the
reduce type: key.setReduceType("<YourReduceClassHere>"); 
- 
- {{{#!java
- public interface ReduceProcessor
- {
-            public String getDataType();
-            public void process(ChukwaRecordKey key,Iterator<ChukwaRecord> values,
-                       OutputCollector<ChukwaRecordKey, 
-                       ChukwaRecord> output, Reporter reporter);
- }
- }}}
- 
- (Tips: see org.apache.hadoop.chukwa.extraction.demux.processor.reducer.SystemMetrics class,
for an example of Reduce class)
- 
- ==== Parser key field ====
- 
- Your data is going to be sorted by RecordType then by the key field.
- The default implementation use the following grouping for all records:
-    1. Time partition (Time up to the hour)
-    1. Machine name (physical input source)
-    1. Record timestamp
- 
- ==== Output directory ====
- The demux process will use the recordType to save similar records together (same recordType)
to the same directory:
- <Your_Cluster_Information>/<Your_Record_Type>/
- 

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