hadoop/hadoop-common-project/hadoop-common/src/site/markdown/Tracing.md

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Enabling Dapper-like Tracing in Hadoop

Dapper-like Tracing in Hadoop

HTrace

HDFS-5274 added support for tracing requests through HDFS, using the open source tracing library, Apache HTrace. Setting up tracing is quite simple, however it requires some very minor changes to your client code.

Samplers Configure the samplers in core-site.xml property: hadoop.htrace.sampler. The value can be NeverSampler, AlwaysSampler or ProbabilitySampler. NeverSampler: HTrace is OFF for all spans; AlwaysSampler: HTrace is ON for all spans; ProbabilitySampler: HTrace is ON for some percentage% of top-level spans.

  <property>
    <name>hadoop.htrace.sampler</name>
    <value>NeverSampler</value>
  </property>

SpanReceivers

The tracing system works by collecting information in structs called 'Spans'. It is up to you to choose how you want to receive this information by implementing the SpanReceiver interface, which defines one method:

public void receiveSpan(Span span);

Configure what SpanReceivers you'd like to use by putting a comma separated list of the fully-qualified class name of classes implementing SpanReceiver in core-site.xml property: hadoop.htrace.spanreceiver.classes.

  <property>
    <name>hadoop.htrace.spanreceiver.classes</name>
    <value>org.apache.htrace.impl.LocalFileSpanReceiver</value>
  </property>
  <property>
    <name>hadoop.htrace.local-file-span-receiver.path</name>
    <value>/var/log/hadoop/htrace.out</value>
  </property>

You can omit package name prefix if you use span receiver bundled with HTrace.

  <property>
    <name>hadoop.htrace.spanreceiver.classes</name>
    <value>LocalFileSpanReceiver</value>
  </property>

Setting up ZipkinSpanReceiver

Instead of implementing SpanReceiver by yourself, you can use ZipkinSpanReceiver which uses Zipkin for collecting and displaying tracing data.

In order to use ZipkinSpanReceiver, you need to download and setup Zipkin first.

you also need to add the jar of htrace-zipkin to the classpath of Hadoop on each node. Here is example setup procedure.

  $ git clone https://github.com/cloudera/htrace
  $ cd htrace/htrace-zipkin
  $ mvn compile assembly:single
  $ cp target/htrace-zipkin-*-jar-with-dependencies.jar $HADOOP_HOME/share/hadoop/common/lib/

The sample configuration for ZipkinSpanReceiver is shown below. By adding these to core-site.xml of NameNode and DataNodes, ZipkinSpanReceiver is initialized on the startup. You also need this configuration on the client node in addition to the servers.

  <property>
    <name>hadoop.htrace.spanreceiver.classes</name>
    <value>ZipkinSpanReceiver</value>
  </property>
  <property>
    <name>hadoop.htrace.zipkin.collector-hostname</name>
    <value>192.168.1.2</value>
  </property>
  <property>
    <name>hadoop.htrace.zipkin.collector-port</name>
    <value>9410</value>
  </property>

Dynamic update of tracing configuration

You can use hadoop trace command to see and update the tracing configuration of each servers. You must specify IPC server address of namenode or datanode by -host option. You need to run the command against all servers if you want to update the configuration of all servers.

hadoop trace -list shows list of loaded span receivers associated with the id.

  $ hadoop trace -list -host 192.168.56.2:9000
  ID  CLASS
  1   org.apache.htrace.impl.LocalFileSpanReceiver

  $ hadoop trace -list -host 192.168.56.2:50020
  ID  CLASS
  1   org.apache.htrace.impl.LocalFileSpanReceiver

hadoop trace -remove removes span receiver from server. -remove options takes id of span receiver as argument.

  $ hadoop trace -remove 1 -host 192.168.56.2:9000
  Removed trace span receiver 1

hadoop trace -add adds span receiver to server. You need to specify the class name of span receiver as argument of -class option. You can specify the configuration associated with span receiver by -Ckey=value options.

  $ hadoop trace -add -class LocalFileSpanReceiver -Chadoop.htrace.local-file-span-receiver.path=/tmp/htrace.out -host 192.168.56.2:9000
  Added trace span receiver 2 with configuration hadoop.htrace.local-file-span-receiver.path = /tmp/htrace.out

  $ hadoop trace -list -host 192.168.56.2:9000
  ID  CLASS
  2   org.apache.htrace.impl.LocalFileSpanReceiver

Starting tracing spans by HTrace API

In order to trace, you will need to wrap the traced logic with tracing span as shown below. When there is running tracing spans, the tracing information is propagated to servers along with RPC requests.

In addition, you need to initialize SpanReceiver once per process.

import org.apache.hadoop.hdfs.HdfsConfiguration;
import org.apache.hadoop.tracing.SpanReceiverHost;
import org.apache.htrace.Sampler;
import org.apache.htrace.Trace;
import org.apache.htrace.TraceScope;

...

    SpanReceiverHost.getInstance(new HdfsConfiguration());

...

    TraceScope ts = Trace.startSpan("Gets", Sampler.ALWAYS);
    try {
      ... // traced logic
    } finally {
      if (ts != null) ts.close();
    }

Sample code for tracing

The TracingFsShell.java shown below is the wrapper of FsShell which start tracing span before invoking HDFS shell command.

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FsShell;
import org.apache.hadoop.tracing.SpanReceiverHost;
import org.apache.hadoop.util.ToolRunner;
import org.apache.htrace.Sampler;
import org.apache.htrace.Trace;
import org.apache.htrace.TraceScope;

public class TracingFsShell {
  public static void main(String argv[]) throws Exception {
    Configuration conf = new Configuration();
    FsShell shell = new FsShell();
    conf.setQuietMode(false);
    shell.setConf(conf);
    SpanReceiverHost.getInstance(conf);
    int res = 0;
    TraceScope ts = null;
    try {
      ts = Trace.startSpan("FsShell", Sampler.ALWAYS);
      res = ToolRunner.run(shell, argv);
    } finally {
      shell.close();
      if (ts != null) ts.close();
    }
    System.exit(res);
  }
}

You can compile and execute this code as shown below.

$ javac -cp `hadoop classpath` TracingFsShell.java
$ java -cp .:`hadoop classpath` TracingFsShell -ls /