[jira] Commented: (HADOOP-5071) Hadoop 1.0 Compatibility Requirements

["Sanjay Radia (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HADOOP-5071?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12678531#action_12678531 ] 

Sanjay Radia commented on HADOOP-5071:
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In the email discussions, we had decided not to support rolling upgrades for 1.0.
Below I am documenting the discussion.
We had decided to go with 5a. for Hadoop 1.0 and do 5b (stronger than 5a) _*after*_ 1.0.

- 5. Intra Hadoop Service Compatibility
The HDFS Service has multiple components (NN, DN, Balancer) that communicate
amongst themselves. Similarly the MapReduce service has
components (JR and TT) that communicate amongst themselves.
Currently we require that the all the components of a service have the same build version and hence talk the same wire protocols.
This build-version checking prevents rolling upgrades.

- 5.a HDFS and MapReduce require that their respective sub-components have the same build version in order to form a cluster.
[ie. Maintain the current mechanism.]

- 5.b- (ie stronger than 5a). Intra-service wire-protocol compatibility
Wire protocols between internal Hadoop components are compatible across minor versions.
Examples are NN-DN, DN-DN and NN-Balancer, etc.
Old m.x components can talk to new m.y components (x<=y)
Wire compatibility can break across major versions.
Motivation: Allow rolling upgrades.
Note this will not give us rolling upgrades automatically but allow us to build rolling upgrade.
Essentially it allows a cluster to have components of different versions (e.g. an HDFS cluster with datanodes at different versions
allowing the operator to roll the older data nodes to a newer version lazily.



> Hadoop 1.0 Compatibility Requirements
> -------------------------------------
>
>                 Key: HADOOP-5071
>                 URL: https://issues.apache.org/jira/browse/HADOOP-5071
>             Project: Hadoop Core
>          Issue Type: Sub-task
>            Reporter: Sanjay Radia
>            Assignee: Sanjay Radia
>
> The purpose of this Jira is to decide on  Hadoop 1.0 Compatibility requirements
> A proposal is described below that was discussed on email alias core-dev@hadoop.apache.org
> Release terminology used below:
> *Standard release numbering: major, minor, dot releases*
> * Only bug fixes in dot releases: m.x.y
> ** no changes to API, disk format, protocols or config etc. in a dot release
> * new features in major (m.0) and minor (m.x.0) releases
> *Hadoop Compatibility Proposal*
> - *1 API Compatibility*
> No need for client recompilation when upgrading across minor releases (ie. from m.x to m.y, where x <= y)
> Classes or methods deprecated in m.x can be removed in (m+1).0
> Note that this is stronger than what we have been doing in Hadoop 0.x releases.
> 	This is fairly standard compatibility rules for major and minor releases.
> - *2 Data Compatibility*
> -- Motivation: Users expect File systems preserve data transparently across releases.
> -- 2.a HDFS metadata and data can change across minor or major releases , but such changes are transparent to user application. That is release upgrade must automatically convert the metadata and data as needed. Further, a release upgrade must allow a cluster to roll back to the older version and its older disk format. (rollback needs to restore the orignal data not any updated data).
> -- 2.a-WeakerAutomaticConversion:
> Automatic conversion is support across a small number of releases. If a user wants to jump across multiple releases he may be forced to go through a few intermediate release to get to the final desired release.
> - *3 Wire Protocol Compatibility*
> We offer no wire compatibility in our 0.x release today.
> -- Motivation: The motivation *isn't* to make the hadoop protocols public. Applications will not call the protocol directly but through a library (in our case FileSystem class and its implementations). Instead the motivation is that customers run multiple clusters and have apps that access data across clusters. Customers cannot be expected to update all clusters simultaneously.
> -- 3.a Old m.x clients can connect to new m.y servers, where x <= y but the old clients might get reduced functionality or performance. m.x clients might not be able to connect to (m+1).z servers
> -- 3.b. New m.y clients must be able to connect to old m.x server, where x< y but only for old m.x functionality.
> Comment: Generally old API methods continue to use old rpc methods. However, it is legal to have new implementations of old API methods call new
> rpcs methods, as long as the library transparently handles the fallback case for old servers.
> -- 3.c. At any major release transition [ ie from a release m.x to a release (m+1).0], a user should be able to read data from the cluster running the old version.
> --- Motivation: data copying across clusters is a common operation for many customers. For example this is routinely at done at Yahoo; another use case is HADOOP-4058. Today, http (or hftp) provides a guaranteed compatible way of copying data across versions. Clearly one cannot force a customer to simultaneously update all its Hadoop clusters on to a new major release.  We can satisfy this requirement via the http/hftp mechanism or some other mechanism.
> -- 3.c-Stronger
> Shall we add a stronger requirement for 1. 0 : wire compatibility across major versions? That is not just for reading but for all operations. This can be supported by class loading or other games.
> Note we can wait to provide this when 2. 0 happens. If Hadoop provided this guarantee then it would allow customers to partition their data across clusters without risking apps breaking across major releases due to wire incompatibility issues.
> --- Motivation: Data copying is a compromise. Customers really want to run apps across clusters running different versions.

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