Hadoop 1.0 Compatibility Requirements
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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
[email protected]
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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