Resource Manager Automatic Failover YARN-149.Support for HDFS Rolling upgrades HDFS-5535.Security for the timeline server YARN-1935.Support for Docker containers in YARN YARN-1964.Support for automatic, shared cache for YARN application artifacts YARN-1492.Support for admin-specified labels in YARN YARN-796.Support for long-running services on YARN YARN-896.Support for rolling upgrades in YARN YARN-666.AES support for faster wire-encryption HDFS-6606.Hot swap storage volumes in Datanodes HDFS-6740.Support APIs for using storage tiers by the applications HDFS-5682.Support NodeGroup layer topology on YARN YARN-18.Dynamic Resource Configuration YARN-291.Support disk as a resource in YARN for scheduling and isolation YARN-2139.YARN-1197 Support changing resources of an allocated container: Alpha feature. YARN-3611 Support Docker Containers In LinuxContainerExecutor: Alpha feature.YARN-1963 Support priorities across applications within the same queue: Alpha feature.YARN-3214 Supporting non-exclusive node-labels: Alpha feature.HDFS-8009 Signal congestion on the DataNode.HDFS-8008 Support client-side back off when the datanodes are congested.HDFS-6200 Create a separate jar for hdfs-client.HADOOP-11090 Support *both* JDK7 and JDK8 runtimes.YARN Timeline Service Next generation: YARN-2928.Early work for disk and network isolation in YARN: YARN-2139, YARN-2140.Classpath isolation for downstream clients HADOOP-11656.This also involves resurrecting jdiff (HADOOP-11776/YARN-3426/MAPREDUCE-6310) and/or investing in new tools. Compatibility tools to catch backwards, forwards compatibility issues at patch submission, release times.Derive heap size or mapreduce.*.memory.mb automatically MAPREDUCE-5785.Support for Erasure Codes in HDFS HDFS-7285.Support for more than two standby NameNodes HDFS-6440.Removal of hftp in favor of webhdfs HDFS-5570.Move default ports out of ephemeral range HDFS-9427.Classpath isolation on by default HADOOP-11656.Hadoop 3.x Releases Planned for hadoop-3.0.0 All new features must be added to trunk prior to the branch date.įor more details on how releases are created, see HowToRelease. No new features or other improvements are added to branches. After this, only patches for issues rated "blocker" are applied to the branch. On the branch date, a branch is created for the minor release cycle. The release date in Jira is then updated to the expected date that the release will be available. The proposed branch date is set as the release date Jira. Release Processįor major and minor releases, a branch date is selected for the release. Prior to 1.0, minor releases follow the rules for major releases, except they are still made every few months. Note: The above rules do not apply until the 1.0 release. They do not introduce new features or make other improvements other than fixing bugs. Point releases are made to fix blocker bugs from an operational perspective. Thus every release with the same major version is both API and 'on the wire' compatible. Also, across minor releasesĪcross all releases with the same major version, user-applications work without the need for 'any' change. Their APIs are back-compatible with prior minor releases, but might include new features, improvements and bug fixes. Minor releases are made regularly, every few months. Major releases are made as needed, perhaps annually or even further apart. Thus, to upgrade to a new major release, one should update ones code so that it compiles without deprecation warnings in the final minor release of the prior major cycle.Īcross all releases with the same major version, user-applications work without the need for 'any' change. We try to facillitate API upgrades by introducing new APIs in the prior major version, deprecating APIs that will be removed.Ī major release primarily just removes APIs and features that were deprecated in the prior major release. Upgrading between major releases will generally require changes to user code. Major releases signify incompatible API changes. Hadoop release numbers are of the form major. Use the "Roadmap" tab to see specific plans for upcoming releases.įor ideas about what you might contribute, please see the ProjectSuggestions and HowToContribute pages. Release planning is primarily coordinated through Hadoop's JIRA database. This page describes Hadoop's release policies.
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