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From bra...@apache.org
Subject [2/3] hadoop git commit: HDFS-10889. Remove outdated Fault Injection Framework documentaion. Contributed by Brahma Reddy Battula
Date Tue, 27 Sep 2016 14:07:07 GMT
HDFS-10889. Remove outdated Fault Injection Framework documentaion. Contributed by Brahma Reddy

(cherry picked from commit df1d0f5d56f375e82b0219a19675a7b6052aaf30)

Project: http://git-wip-us.apache.org/repos/asf/hadoop/repo
Commit: http://git-wip-us.apache.org/repos/asf/hadoop/commit/61368c80
Tree: http://git-wip-us.apache.org/repos/asf/hadoop/tree/61368c80
Diff: http://git-wip-us.apache.org/repos/asf/hadoop/diff/61368c80

Branch: refs/heads/branch-2
Commit: 61368c8039bd28648b8c2cb94c5a473e84347c77
Parents: 86ec99e
Author: Brahma Reddy Battula <brahma@apache.org>
Authored: Tue Sep 27 19:33:10 2016 +0530
Committer: Brahma Reddy Battula <brahma@apache.org>
Committed: Tue Sep 27 19:34:38 2016 +0530

 .../src/site/markdown/FaultInjectFramework.md   | 254 -------------------
 1 file changed, 254 deletions(-)

diff --git a/hadoop-hdfs-project/hadoop-hdfs/src/site/markdown/FaultInjectFramework.md b/hadoop-hdfs-project/hadoop-hdfs/src/site/markdown/FaultInjectFramework.md
deleted file mode 100644
index 98bda50..0000000
--- a/hadoop-hdfs-project/hadoop-hdfs/src/site/markdown/FaultInjectFramework.md
+++ /dev/null
@@ -1,254 +0,0 @@
-  Licensed under the Apache License, Version 2.0 (the "License");
-  you may not use this file except in compliance with the License.
-  You may obtain a copy of the License at
-   http://www.apache.org/licenses/LICENSE-2.0
-  Unless required by applicable law or agreed to in writing, software
-  distributed under the License is distributed on an "AS IS" BASIS,
-  See the License for the specific language governing permissions and
-  limitations under the License. See accompanying LICENSE file.
-Fault Injection Framework and Development Guide
-* [Fault Injection Framework and Development Guide](#Fault_Injection_Framework_and_Development_Guide)
-    * [Introduction](#Introduction)
-    * [Assumptions](#Assumptions)
-    * [Architecture of the Fault Injection Framework](#Architecture_of_the_Fault_Injection_Framework)
-        * [Configuration Management](#Configuration_Management)
-        * [Probability Model](#Probability_Model)
-        * [Fault Injection Mechanism: AOP and AspectJ](#Fault_Injection_Mechanism:_AOP_and_AspectJ)
-        * [Existing Join Points](#Existing_Join_Points)
-    * [Aspect Example](#Aspect_Example)
-    * [Fault Naming Convention and Namespaces](#Fault_Naming_Convention_and_Namespaces)
-    * [Development Tools](#Development_Tools)
-    * [Putting It All Together](#Putting_It_All_Together)
-        * [How to Use the Fault Injection Framework](#How_to_Use_the_Fault_Injection_Framework)
-    * [Additional Information and Contacts](#Additional_Information_and_Contacts)
-This guide provides an overview of the Hadoop Fault Injection (FI) framework for those who
will be developing their own faults (aspects).
-The idea of fault injection is fairly simple: it is an infusion of errors and exceptions
into an application's logic to achieve a higher coverage and fault tolerance of the system.
Different implementations of this idea are available today. Hadoop's FI framework is built
on top of Aspect Oriented Paradigm (AOP) implemented by AspectJ toolkit.
-The current implementation of the FI framework assumes that the faults it will be emulating
are of non-deterministic nature. That is, the moment of a fault's happening isn't known in
advance and is a coin-flip based.
-Architecture of the Fault Injection Framework
-Components layout
-### Configuration Management
-This piece of the FI framework allows you to set expectations for faults to happen. The settings
can be applied either statically (in advance) or in runtime. The desired level of faults in
the framework can be configured two ways:
-* editing src/aop/fi-site.xml configuration file. This file is
-  similar to other Hadoop's config files
-* setting system properties of JVM through VM startup parameters or
-  in build.properties file
-### Probability Model
-This is fundamentally a coin flipper. The methods of this class are getting a random number
between 0.0 and 1.0 and then checking if a new number has happened in the range of 0.0 and
a configured level for the fault in question. If that condition is true then the fault will
-Thus, to guarantee the happening of a fault one needs to set an appropriate level to 1.0.
To completely prevent a fault from happening its probability level has to be set to 0.0.
-Note: The default probability level is set to 0 (zero) unless the level is changed explicitly
through the configuration file or in the runtime. The name of the default level's configuration
parameter is fi.\*
-### Fault Injection Mechanism: AOP and AspectJ
-The foundation of Hadoop's FI framework includes a cross-cutting concept implemented by AspectJ.
The following basic terms are important to remember:
-* A cross-cutting concept (aspect) is behavior, and often data, that
-  is used across the scope of a piece of software
-* In AOP, the aspects provide a mechanism by which a cross-cutting concern
-  can be specified in a modular way
-* Advice is the code that is executed when an aspect is invoked
-* Join point (or pointcut) is a specific point within the application
-  that may or not invoke some advice
-### Existing Join Points
-The following readily available join points are provided by AspectJ:
-* Join when a method is called
-* Join during a method's execution
-* Join when a constructor is invoked
-* Join during a constructor's execution
-* Join during aspect advice execution
-* Join before an object is initialized
-* Join during object initialization
-* Join during static initializer execution
-* Join when a class's field is referenced
-* Join when a class's field is assigned
-* Join when a handler is executed
-Aspect Example
-package org.apache.hadoop.hdfs.server.datanode;
-import org.apache.commons.logging.Log;
-import org.apache.commons.logging.LogFactory;
-import org.apache.hadoop.fi.ProbabilityModel;
-import org.apache.hadoop.hdfs.server.datanode.DataNode;
-import org.apache.hadoop.util.DiskChecker.*;
-import java.io.IOException;
-import java.io.OutputStream;
-import java.io.DataOutputStream;
- * This aspect takes care about faults injected into datanode.BlockReceiver
- * class
- */
-public aspect BlockReceiverAspects {
-  public static final Log LOG = LogFactory.getLog(BlockReceiverAspects.class);
-  public static final String BLOCK_RECEIVER_FAULT="hdfs.datanode.BlockReceiver";
-    pointcut callReceivePacket() : call (* OutputStream.write(..))
-      && withincode (* BlockReceiver.receivePacket(..))
-    // to further limit the application of this aspect a very narrow 'target' can be used
as follows
-    // && target(DataOutputStream)
-      && !within(BlockReceiverAspects +);
-  before () throws IOException : callReceivePacket () {
-    if (ProbabilityModel.injectCriteria(BLOCK_RECEIVER_FAULT)) {
-      LOG.info("Before the injection point");
-      Thread.dumpStack();
-      throw new DiskOutOfSpaceException ("FI: injected fault point at " +
-      thisJoinPoint.getStaticPart( ).getSourceLocation());
-    }
-  }
-The aspect has two main parts:
-* The join point pointcut callReceivepacket() which servers as an
-  identification mark of a specific point (in control and/or data
-  flow) in the life of an application.
-* A call to the advice - before () throws IOException :
-  callReceivepacket() - will be injected (see Putting It All
-  Together) before that specific spot of the application's code.
-The pointcut identifies an invocation of class' java.io.OutputStream write() method with
any number of parameters and any return type. This invoke should take place within the body
of method receivepacket() from classBlockReceiver. The method can have any parameters and
any return type. Possible invocations of write() method happening anywhere within the aspect
BlockReceiverAspects or its heirs will be ignored.
-Note 1: This short example doesn't illustrate the fact that you can have more than a single
injection point per class. In such a case the names of the faults have to be different if
a developer wants to trigger them separately.
-Note 2: After the injection step (see Putting It All Together) you can verify that the faults
were properly injected by searching for ajc keywords in a disassembled class file.
-Fault Naming Convention and Namespaces
-For the sake of a unified naming convention the following two types of names are recommended
for a new aspects development:
-* Activity specific notation (when we don't care about a particular
-  location of a fault's happening). In this case the name of the
-  fault is rather abstract: fi.hdfs.DiskError
-* Location specific notation. Here, the fault's name is mnemonic as
-  in: fi.hdfs.datanode.BlockReceiver[optional location details]
-Development Tools
-* The Eclipse AspectJ Development Toolkit may help you when developing aspects
-* IntelliJ IDEA provides AspectJ weaver and Spring-AOP plugins
-Putting It All Together
-Faults (aspects) have to injected (or woven) together before they can be used. Follow these
instructions: \* To weave aspects in place use:
-        % ant injectfaults
-* If you misidentified the join point of your aspect you will see a warning (similar to the
one shown here) when 'injectfaults' target is completed:
-            [iajc] warning at
-            src/test/aop/org/apache/hadoop/hdfs/server/datanode/ \
-                      BlockReceiverAspects.aj:44::0
-            advice defined in org.apache.hadoop.hdfs.server.datanode.BlockReceiverAspects
-            has not been applied [Xlint:adviceDidNotMatch]
-* It isn't an error, so the build will report the successful result. To prepare dev.jar file
with all your faults weaved in place (HDFS-475 pending) use:
-            % ant jar-fault-inject
-* To create test jars use:
-            % ant jar-test-fault-inject
-* To run HDFS tests with faults injected use:
-            % ant run-test-hdfs-fault-inject
-### How to Use the Fault Injection Framework
-Faults can be triggered as follows:
-* During runtime:
-            % ant run-test-hdfs -Dfi.hdfs.datanode.BlockReceiver=0.12
-    To set a certain level, for example 25%, of all injected faults use:
-            % ant run-test-hdfs-fault-inject -Dfi.*=0.25
-* From a program:
-package org.apache.hadoop.fs;
-import org.junit.Test;
-import org.junit.Before;
-public class DemoFiTest {
-  public static final String BLOCK_RECEIVER_FAULT="hdfs.datanode.BlockReceiver";
-  @Override
-  @Before
-  public void setUp() {
-    //Setting up the test's environment as required
-  }
-  @Test
-  public void testFI() {
-    // It triggers the fault, assuming that there's one called 'hdfs.datanode.BlockReceiver'
-    System.setProperty("fi." + BLOCK_RECEIVER_FAULT, "0.12");
-    //
-    // The main logic of your tests goes here
-    //
-    // Now set the level back to 0 (zero) to prevent this fault from happening again
-    System.setProperty("fi." + BLOCK_RECEIVER_FAULT, "0.0");
-    // or delete its trigger completely
-    System.getProperties().remove("fi." + BLOCK_RECEIVER_FAULT);
-  }
-  @Override
-  @After
-  public void tearDown() {
-    //Cleaning up test test environment
-  }
-As you can see above these two methods do the same thing. They are setting the probability
level of `hdfs.datanode.BlockReceiver` at 12%. The difference, however, is that the program
provides more flexibility and allows you to turn a fault off when a test no longer needs it.
-Additional Information and Contacts
-These two sources of information are particularly interesting and worth reading:
-* <http://www.eclipse.org/aspectj/doc/next/devguide/>
-* AspectJ Cookbook (ISBN-13: 978-0-596-00654-9)
-If you have additional comments or questions for the author check [HDFS-435](https://issues.apache.org/jira/browse/HDFS-435).

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